DEV Community: Emma Wilson

When AI Removes Friction Instead of Replacing Expertise: A Conversation with Pamela Wagner

Emma Wilson — Mon, 13 Jul 2026 07:57:40 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

Knowledge work has never been limited only by knowledge.

It's limited by everything wrapped around it: communication, administration, coordination, formatting, revisions, context switching, and hundreds of tiny decisions that slowly drain energy before the real work even begins.

AI is beginning to change that equation.

Not because it knows more than experts, but because it increasingly absorbs the work that experts were never uniquely qualified to do in the first place.

That's exactly where Pamela Wagner's experience stands out. As a founder, educator, and AI trainer, she isn't using AI to replace expertise. She's using it to remove everything that kept her expertise from moving as quickly as her ideas.

Meet the Interviewee

Pamela Wagner is the Founder and CEO of Ajala Digital, a Google Ads consultant, university lecturer, and corporate AI educator based in Austria. Alongside helping businesses grow through digital marketing, she trains organizations on practical AI adoption and leads initiatives focused on helping more women confidently build with AI.

The Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

Before AI became widely adopted, my work was split between core expertise and operational friction. Running Ajala Digital and teaching Google Ads and global branding at Vienna and Hult, I delivered the same business outcomes I do now: measurable campaign results for clients and teaching students how to build effective strategies. But I spent enormous amounts of time on tasks that had nothing to do with actual expertise. Procrastinating on social media design, blog decoration, email writing. Either outsourcing these (expensive) or letting them slide (costly in other ways). I also struggled with written communication generally. Email etiquette, client correspondence. I was probably making a worse impression than I realized, losing potential partnerships in the process.
The other bottleneck was operational dependency. I kept switching developers because I couldn't communicate what I needed and couldn't make simple changes myself. Across both businesses, the pattern was the same: I had real expertise in my domains, but I was blocked by operational and communication gaps that had nothing to do with my skill. That friction also meant I had less mental space for the strategic thinking and connection work that actually required me.

How does AI currently intersect with your work or personal life?

AI solved my operational bottlenecks, hence allowed me to have more free time and do more of other things that I love as well. For example, just this month, I've started doing a TMJ (temporomandibular) massage course.
Email communication, content decoration, website management, social media graphics are all tasks that used to drain time and money are now handled efficiently. This freed capacity for what actually requires my expertise: client strategy, teaching at universities, and running various trainings and events. I've integrated AI workflows and tools into my Google Ads and global branding courses so students learn to work alongside these systems rather than compete with them. As a result, I am able to grow my business with fewer resources, in less time, and with an increased output for clients.

Professionally, I'm witnessing a different intersection through the hundreds of women and corporate teams I work with directly. I train 120 Salesforce executives annually and just delivered a keynote to roughly 1,000 Infineon employees on stress and trauma release. What I hear consistently from women is professional grief at watching skills they spent years mastering become commoditised, plus pressure to suddenly be AI-fluent on top of everything else. My work has evolved to help people process both the operational and identity impacts of this shift."

What AI tools, if any, do you regularly use?

Claude for writing and strategic thinking. Google's AI tools for research and content direction. Video editing and content automation platforms for production and scaling across different business funnels and needs. The stack is practical, not trendy.

Each tool solves a specific problem. Claude handles intellectual work, Google handles breadth and research, and the platform stack handles production scaling and may also change over time depending on business needs. It's about efficiency aligned to business outcome, not novelty."

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

The first specific moment was using Claude to rewrite an email I would have otherwise agonized over for days. I'd normally second-guess myself, ask multiple people for advice, lose nerves. Claude did it in two minutes and captured what I meant better than I would have written it myself. That single experience shifted something fundamental: I realized a process I'd thought required human emotional judgment and days of deliberation could be cut down to 2 minutes without losing authenticity. That moment forever changed how I approached professional communication.
From there, I tested other apps. I had Claude impersonate Tony Robbins to coach me through business strategy problems, and it was genuinely better than his actual paid AI version. It helped me get strategic clarity fast, solve problems I'd usually procrastinate on, and bypass decision paralysis.

Lastly, as someone whose native language isn't English, AI has also been a practical tool for improving my writing quality, which directly elevates how clients and partners perceive my professionalism. The impact wasn't just about speed. It was about removing the psychological and linguistic friction that was limiting my actual effectiveness.

What was your initial reaction? Please explain why you experienced that emotion?

Excitement because the AI gave me something so much better I could've never thought of myself.

What has been the biggest positive impact AI has had on your life or work?

To produce more outcomes for our clients in less time and with less effort on my side, hence being able to grow the business more efficiently. As a result, I have more time for my mental and physical well-being.

What has been the biggest challenge, frustration, or downside?

Finding employees who are better at using AI than me!

Has AI changed how you think about your skills, value, creativity, or professional identity?

Yes, absolutely - AI is an expansion and an acceleration of the skills, value and creativity I bring to my work!

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

No. And, that's probably because I genuinely enjoy learning about and with it.

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

Yes. On the mental health and psychology side, you have to be intentional about how you use AI. It can reinforce what you want to hear rather than challenge you. I use guardrails with Claude: be straight up, honest, push back on my thinking rather than validating it. That's a fairness issue. AI can become a mirror that only reflects what you want to see, which is dangerous when making decisions about wellbeing or identity.

The bigger unfairness I'm observing is structural. Through my event series ""Women Build with AI"" and my corporate training, women without built-in tech backgrounds are experiencing pressure to ""catch up"" to AI without the same resources or support that tech-adjacent roles have. There's also an unexpected opportunity flip side: some women who aren't traditionally trained in tech are more creative with AI because they're not constrained by conventional thinking. But that advantage only exists for those with time and access to experiment. The opportunity gap is real.

Do you think AI has affected expectations at work (productivity, speed, output, hiring, promotions, etc.)?

Absolutely. Through my corporate training with Salesforce and across companies like Infineon, I hear the same contradiction repeatedly: employees are expected to catch up with AI and become fluent in it. But IT blocks them. No access to tools, security restrictions, corporate policies preventing installation or experimentation. The expectation is "figure it out," but the infrastructure actively prevents it.

The result is fear instead of enablement. People get blocked from accessing tools, so they either don't learn or develop anxiety around AI rather than competence. There's a structural unfairness: companies demand adaptation but don't provide access or permission to actually adapt. I'm seeing this pattern across different industries and company sizes, and it's particularly damaging for women who are already experiencing pressure to "catch up" without the same mentorship or psychological safety."

What is one thing about AI that most people misunderstand?

That it is similar to social media: it's not going away, and almost everyone will have access to it. Whether it has a positive or negative effect on you depends entirely on how you choose to use it.

What advice would you give other women navigating AI's growing influence in their careers or lives?

Keep learning about it - it won't go away. And, keep asking questions. Whatever is stopping you is never a real reason anymore, because you've the world's knowledge at your hand to solve it.

Are you more optimistic or more concerned about AI's future impact? Why?

I'm optimistic because I believe people, especially women, can develop healthy, intentional relationships with AI if given the right support and permission to experiment. The tool isn't the problem. The structure around access and education is.

Complete this sentence: "AI has changed my life by __________."

...100% for the better.

Final Thoughts

One of the more interesting shifts AI may create isn't a world where humans work less. It may be a world where more people finally spend their time on the work they're uniquely qualified to do.

For years, expertise came bundled with dozens of unrelated responsibilities. The strategist also had to be the copy editor. The founder also had to be the designer. The consultant also had to manage every operational detail. AI is beginning to separate those layers.

Pamela's story suggests that the future may belong less to those who simply produce more, and more to those who understand where their real value lies. If AI can quietly remove the friction around that value, it doesn't diminish expertise. It gives it more room to matter.

Are you a woman using AI in your work, business, studies, or daily life? I'd love to hear your perspective. If AI has changed how you work, create, learn, lead, or think about your future, share your story in the comments. I'm always looking for new voices and would be happy to interview you for a future edition of this series.

From Vision to Visuals: Gail Scott on Using AI to Finally Bring Creative Ideas to Life

Emma Wilson — Mon, 13 Jul 2026 07:38:33 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

Most conversations about AI revolve around speed, automation, or replacing work. But one theme that has quietly surfaced throughout this interview series is something different: many women aren't talking about AI replacing creativity. They're talking about AI removing the barriers that prevented their creativity from becoming reality in the first place.

For many entrepreneurs and creators, the hardest part isn't having ideas. It's finding the time, skills, budget, or confidence to execute them. AI doesn't necessarily make them more creative. It gives them the ability to finally express ideas that had been sitting in notebooks, mood boards, or simply inside their heads.

That was exactly the direction my recent conversation with Gail Scott took. Rather than describing AI as a replacement for creative work, she describes it as the assistant that finally helped her match the quality of her output to the quality of her imagination.

Meet the Interviewee

Gail Scott is the Style & Beauty Director at Your Color Style, where she helps women discover confidence through personal style, color analysis, and beauty education. As both an educator and entrepreneur, she uses AI to accelerate creative work while keeping her own artistic vision firmly at the center.

The Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

Taxing. We had so many ideas and not enough time, energy, or prowess to execute them with the excellence we desired.

How does AI currently intersect with your work or personal life?

AI is like having an assistant. It has helped us to think through and create marketing campaigns, course outlines, pitches, website layout, and social media content. Everything is faster and at the level of excellence we desire. We would eventually get there on our own, but the hours to do so would be enormous. We find it to be a huge time saver.

What AI tools, if any, do you regularly use?

Image creation, writing our thoughts into presentable content, magazine page creation, information gathering. We also use Codex for our website and app.

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

When it took me 20 minutes to create an entire content post with graphics. This would have taken me an hour or more on my own. I also realized that I did not need to invest in a new creation tool, so I avoided that cost and the time to educate myself on using it. Such a relief.

What was your initial reaction? Please explain why you experienced that emotion?

Excitement because content creation became much less taxing and I did not dread working on it. It's become pleasurable, as I can create what is in my mind in minutes.

What has been the biggest positive impact AI has had on your life or work?

Time savings and quality of content.

What has been the biggest challenge, frustration, or downside?

Learning to use AI for the best results. Training AI to do what we need and give us content in our style.

Has AI changed how you think about your skills, value, creativity, or professional identity?

I feel more confident. Hiring design assistants to create what was in my head always felt expensive and risky. I can now do it myself in minutes for little cost. I feel more confident in putting out my content, as it lives up to how I imagined it. I get to be creative, AI brings it to life.

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

It is frustrating when AI alters images in ways you did not ask for. It's concept of beauty is distorted and unrealistic.

Do you think AI has affected expectations at work (productivity, speed, output, hiring, promotions, etc.)?

Yes! We feel the need for less outside help and we bring our ideas to fruition much faster.

What is one thing about AI that most people misunderstand?

That it isn't your voice or your work.

What advice would you give other women navigating AI's growing influence in their careers or lives?

Try it! Experiment. Use it to bring your ideas to life.

Are you more optimistic or more concerned about AI's future impact? Why?

Optimistic, but cautious. I can see the negative aspects, and am concerned about the environmental impact and how this technology will be used by nefarious characters.

Complete this sentence: "AI has changed my life by __________."

... helping me to bring my ideas to life in less time.

Final Thoughts

One thing that stood out to me in Gail's responses is that AI didn't simply make her faster. It made creative work feel enjoyable again. That distinction matters. We often measure AI by how many hours it saves, but we rarely ask what it gives back emotionally. In Gail's case, it removed the dread from repetitive creative tasks and replaced it with excitement. That's a very different way of thinking about productivity.

Her interview also highlights another important conversation that deserves more attention. AI-generated images have made creating visuals dramatically easier, but they have also introduced new questions about beauty standards and representation. Gail's observation that AI often defaults to unrealistic ideas of beauty is something I haven't heard discussed nearly enough. As more women rely on these tools for creative work, they won't just shape workflows. They'll also shape aesthetics, culture, and expectations. The opportunity isn't simply to create faster. It's to ensure we train and use these tools in ways that reflect more authentic, diverse, and human perspectives.

When AI Writes the First Draft, Human Judgment Matters More: A Conversation with Attorney Jaklin Sookiassian

Emma Wilson — Mon, 13 Jul 2026 06:37:00 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

One of the biggest promises surrounding AI is that it can replace knowledge work. It can draft documents, summarize research, answer questions, and produce content within seconds. That's exciting—but it also creates a dangerous illusion: that generating something is the same as understanding it.

After speaking with dozens of women across industries, I've noticed that many aren't using AI simply to move faster. They're learning where AI should stop and where human judgment has to begin.

My recent conversation with attorney Jaklin Sookiassian captures this perfectly. As AI-generated contracts, emails, and legal documents become increasingly common, she finds herself spending just as much time protecting clients from AI mistakes as she does using AI to improve her own work. Her perspective isn't anti-AI at all. In fact, she's optimistic about its future. But she also believes we're entering an era where expertise isn't becoming less valuable—it's becoming far more important.

Meet the Interviewee

Jaklin Sookiassian is the Managing Attorney at The Sookiassian Firm in the United States. She advises businesses and individuals on complex legal matters while embracing AI as a productivity tool—without losing sight of the professional judgment that technology cannot replace.

The Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

My work consisted of drafting everything manually, responding to clients manually, strategizing about things with my team, and digging through internet research for hours to find answers to questions that now get answered in seconds. There have been many advantages to having AI as a tool, without a doubt. I can save time on research and draft professional emails in a fraction of the time it would take normally. These are all cost benefits to our clients, who pay for our work by the hour.

However, not everyone uses AI as a tool, and that is where the problem lies. On the surface it feels like a shortcut, but in reality it often creates bigger (and more expensive) problems down the line when those gaps come back to bite them

How does AI currently intersect with your work or personal life?

AI certainly intersects with my work life because it is a great tool to use, but I find myself often needing to protect my clients from it who lean on it irresponsibly. I can’t tell you the amount of AI drafted contracts I’ve been presented by clients who say “I already did the contract, can you just briefly review it to make sure it’s legit” and I usually can tell in an instant that it’s AI generated. And to be honest, they’re awful. AI is nowhere near drafting documents at an attorney level, but unfortunately that’s only recognized by attorneys. A lay person cannot differentiate between a good contract and a bad one.

I also find myself using AI in my personal life for different reasons. I use it mainly for fun or tedious projects like when I need to plan out a birthday party, need help with ideas for gifts, creating invitations for my kids birthday party, planning a trip itinerary, or find the best stroller on the market. I think it’s a great tool for tedious endeavors but I try to limit my use of AI to things that don’t actually require intellectual backing.

What AI tools, if any, do you regularly use?

I use Claude, Gemini and Chat GPT

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

I had a client ask me to review a purchase agreement for the purchase of a business in Las Vegas. They had already signed an LOI, which was a short AI-generated LOI. They signed this before engaging me and that LOI was missing key provisions. The deal ultimately died because while we were in the process of reviewing the agreement, the seller went shopping around for a better offer from another buyer. He was able to do this because the LOI didn't restrict him from doing so.

What was your initial reaction? Please explain why you experienced that emotion.

I was concerned when I saw the LOI because I knew it didn't have the necessary language to protect the buyer from the seller going and shopping around for better offers while my client spent time and money on attorneys fees reviewing and revising the main contract.

What has been the biggest positive impact AI has had on your life or work?

AI has benefited my life and my work by cutting time doing tedious tasks, but I cannot rely on it to do anything that requires judgment or intellectual backing.

What has been the biggest challenge, frustration, or downside?

It's very frustrating when I see my clients suffer because of their reliance on AI. It is not reliable in the way people think it is and I saw a client spend thousands of dollars on a deal that ended up falling through because his AI-generated LOI was missing key provisions.

Has AI changed how you think about your skills, value, creativity, or professional identity?

It's certainly made me think about the value I have, and I've realized that lawyers are more valuable now than ever before because we're some of the few people who can recognize AI mistakes and shortfalls. Most people won't recognize a bad contract from a good one, and that's scary. I think creatively, AI has definitely helped with that. Like coming up with ideas for marketing and logo designs, I think AI has made those parts of my business much easier and more efficient.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

I think I wanted to learn AI to know how to use it as a tool due to personal preference rather than external pressure. I'm a fan of utilizing resources and if there's a resource that can aid my work and business in a healthy way, and also sometimes minimize costs for my clients, then I'm all for it.

Do you think AI has affected expectations at work (productivity, speed, output, hiring, promotions, etc.)?

Not yet, but I think it definitely will in a few years when more businesses incorporate AI as part of its regular operations and employees are expected to use AI for various tasks for efficiency and accuracy.

What is one thing about AI that most people misunderstand?

I think people don't realize that AI engines like Chat GPT store their information. AI systems generally learn from human information to improve their accuracy, capabilities, and safety. They analyze collective user prompts, conversations, and feedback to refine model weights. This means that everything you've ever asked, photos you've attached, documents you've attached, are all stored in the AI database and are no longer private. Additionally, all of that is discoverable if ever subject to a court subpoena.

What advice would you give other women navigating AI's growing influence in their careers or lives?

I would advise them to learn to use it to their benefit where it's appropriate and within reason. There are many things AI can help with and many things that AI cannot be relied upon for. People need to be sure they understand the difference when using it.

Are you more optimistic or more concerned about AI's future impact? Why?

I'm optimistic because I know it's only going to continue to improve over time. I know that AI today versus AI 12 months ago has come a very long way. I am optimistic that 5 years from now AI will be extremely advanced and people will be able to rely upon it with more ease and confidence than they are today. I am worried about the jobs that AI may eliminate, particularly the jobs where human interaction is not an element of the job duties. That does concern me. As a parent, I think about what professions will be prevalent in society in 20 years, and I think there will definitely be a shift in popular career paths that my generation grew up pursuing.

Complete this sentence: "AI has changed my life by __________."

... streamlining certain aspects of my life while complicating others.

Final Thoughts

One idea kept coming back to me while reading Jaklin's responses: AI isn't just changing how work gets done, it is also changing where expertise becomes indispensable.

The legal profession is a powerful example. AI can draft a contract in seconds, but it cannot understand the commercial context, anticipate future disputes, or protect someone from the consequences of missing a single clause. That distinction only becomes obvious after something goes wrong.

That's a broader lesson that extends far beyond law. As AI becomes more capable, human judgment doesn't become less important—it becomes the quality that determines whether AI creates value or creates expensive mistakes. The professionals who thrive won't necessarily be the ones who use AI the most. They'll be the ones who know when to trust it, when to question it, and when experience must take over.

From Burnout to Breakthrough: A Conversation with Dr Negin Rajaipour, MD. on AI, Medicine, and Building Without Limits

Emma Wilson — Fri, 03 Jul 2026 07:03:53 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

Ever since AI went mainstream, the conversation has centered on productivity: doing more work in less time. But what if that's asking the wrong question? What is productivity is just the surface-level benefit? What if AI's biggest impact isn't helping people do more but helping them build things they never could have built before?

That's exactly what my recent conversation with Dr Negin Rajaipour, MD. explored.

As a physician, founder, author, and single mother, she wasn't searching for another productivity tool. She was trying to turn years of ideas into reality without the team, funding, or infrastructure that would normally make that possible. Our conversation quickly moved beyond prompts and productivity into something much more interesting: how AI can remove the bottleneck between thinking and execution.

Her perspective is one of the most thought-provoking, not because of what AI can do, but because of what it enables people to build.

Meet the Interviewee

Dr Negin Rajaipour, MD. is a board-certified family medicine physician, U.S. Navy veteran, and founder of VitaRegen Medical, a multi-state cash-pay telehealth practice. She also advises physician leaders and healthcare executives, combining clinical expertise, military discipline, and operational strategy to help them navigate complex transitions and high-stakes decisions.

Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

I was a full-time employed family medicine physician seeing 20+ patients a day inside a system built for volume, not depth. My days were documentation, referrals, and managing chronic conditions that the system had no real framework to address. Outside of clinical hours, I was building my own practice, writing a book, and developing a clinical framework — all of it manually, nights and weekends, as a single mother of two. The infrastructure required to do what I was trying to build would have taken a team and years. I had neither.

How does AI currently intersect with your work or personal life?

AI is the reason I was able to leave employed medicine in December 2025 and launch a functioning multi-state telehealth practice, a published bestseller, a trademarked clinical framework, and three branded platforms — without a partner, without venture capital, and without the staff this would have required a decade ago.

Clinically, it has changed how I research, document, and build patient education. As a founder, it functions as my strategist, copywriter, systems architect, social media content creator and thinking partner. It does not replace my clinical judgment — it removes every barrier that used to sit between my thinking and execution..

What AI tools, if any, do you regularly use?

Claude (Anthropic) is my primary tool — I use it for clinical content, strategic planning, brand development, legal drafting, and complex problem-solving. I also use it through Claude Code for building and deploying web infrastructure.

Additionally: HeyGen for AI video, ElevenLabs for audio, Skriber for charting patient encounters, Otter AI for meeting notes and various automation tools that connect my patient platform, email systems, and content pipeline.

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

The moment that reoriented everything was a night in early 2025 when I was still employed, sitting with a document I had been trying to finish for weeks — a clinical framework I had been building in my head for years but could never fully articulate on paper because I had no time, no team, and no one to think alongside.

I opened Claude and started talking through it.

Within two hours, what had lived in my head as a fragmented idea became a structured, named, deployable framework.

That was The E3 Method™ — now pending trademark clinical IP that anchors everything I build. I realized that night that the bottleneck had never been my thinking. It had been the infrastructure required to translate thinking into output. AI removed that bottleneck entirely.

What was your initial reaction? Please explain why you experienced that emotion?

Curiosity.

I am a physician trained to follow evidence before forming a conclusion. My first instinct with any new tool is to understand its mechanism before assigning it a value. I did not react with fear because fear requires a perceived threat, and I did not see AI as a threat to clinical judgment — I saw it as a tool that would either prove useful or not.

Curiosity was the honest response.

What I did not anticipate was how quickly that curiosity would convert into structural dependency — not because AI replaced my thinking, but because it finally gave my thinking somewhere to go.

What has been the biggest positive impact AI has had on your life or work?

Speed of execution without sacrifice of depth.

I left employed medicine in December 2025 and built a functioning multi-state telehealth practice, a published international bestseller, a trademarked clinical framework, a course ecosystem, and three branded websites — as a solo founder and single mother, without venture capital or a team. That is not a productivity story. That is an infrastructure story.

AI collapsed the gap between vision and execution in a way that has no equivalent in any tool I have used before.

What has been the biggest challenge, frustration, or downside?

The most honest answer is pacing — specifically, the pressure it creates to move faster than is always wise. AI can produce in an hour what used to take a month. That capability is extraordinary, but it also collapses the natural friction that used to force reflection. Decisions that previously had built-in processing time — because execution was slow — now happen at the speed of a prompt. For a founder, that requires a new kind of discipline: not the discipline to do more, but the discipline to slow down intentionally when speed is available.

The second challenge is one I see clinically more than personally. The women I work with are not struggling because AI is replacing them. They are struggling because the pace AI has introduced into their industries is landing on nervous systems that were already dysregulated. The body does not distinguish between productive acceleration and threat. It reads the speed the same way. That is a physiological problem, and no productivity framework addresses it. That is the conversation medicine needs to be having — and largely isn't.

The third is cognitive overload — and it is directly tied to that same speed. When a tool can generate endless options, variations, and outputs in seconds, the decision-making burden shifts entirely to the human. You are no longer limited by what you can produce. You are limited by what you can evaluate. That is a different kind of exhaustion — not physical, not emotional, but cognitive — and it accumulates quietly until the quality of your decisions starts to degrade without you noticing. The bottleneck moved. It didn't disappear.

Has AI changed how you think about your skills, value, creativity, or professional identity?

It clarified them. Before AI, a significant portion of my cognitive bandwidth went toward execution tasks — formatting, drafting, researching, building. Those tasks consumed time that belonged to thinking. When AI absorbed the execution layer, what remained was unmistakably mine: clinical judgment, pattern recognition, framework development, the ability to hold complexity without collapsing it into something simple. AI did not threaten my professional identity. It stripped away everything that was obscuring it.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

No — and I think that is worth examining. The pressure most people describe around AI adoption is a nervous system response to perceived obsolescence. I did not feel that because I approached AI as a tool to evaluate, not a threat to outrun. What I have felt is the opposite pressure: the temptation to move faster than my own discernment could keep up with. The risk for high-functioning women is not falling behind. It is accelerating past the point where their own judgment is still in the driver’s seat.

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

The unexpected opportunity has been the great equalizer effect. I am a Persian-American woman, a single mother, a physician who left a stable system to build something from scratch — without the network, the capital, or the institutional backing that typically accelerates this kind of venture. AI neutralized most of those structural disadvantages. The quality of what I produce is no longer limited by the resources I have access to. That is not a small thing. For women building outside traditional power structures, AI is genuinely redistributive — if they know how to use it.

Do you think AI has affected expectations at work?

Yes, and the effect is largely unacknowledged in its physiological cost. AI has raised the baseline expectation for output volume and speed across virtually every knowledge-work environment. What one person used to produce in a week is now expected in a day. That recalibration is happening faster than human nervous systems can adapt to it — and no organization is measuring the allostatic load that accumulates when people are asked to operate indefinitely at AI-augmented pace. Burnout is about to look very different, and most workplace wellness programs are not built for what is coming.

What is one thing about AI that most people misunderstand?

That it is a threat to human expertise. The more precise framing is that AI is a threat to the performance of expertise — the execution layer that people built their professional identity on. The thinking, the judgment, the synthesis of complex information into a decision that matters: AI does not do that. What it does is expose whether that capacity was ever there to begin with. For people whose value was always in their depth of thinking, AI is an amplifier. For people whose value was in their volume of output, it is a displacement. Most people are not afraid of AI. They are afraid of that distinction being made visible.

What advice would you give other women navigating AI's growing influence in their careers or lives?

Stop asking whether AI will replace you and start asking whether you are using it to build something only you could build. The women who will struggle are the ones waiting to see how AI settles before they engage with it. The women who will lead are the ones who pick it up now, learn its edges, and integrate it as an extension of their own thinking. You do not need to be technical. You need to be clear about what you think, what you know, and what you are trying to create. AI cannot give you that. But if you already have it, AI will multiply it faster than any other tool in history.

Are you more optimistic or more concerned about AI's future impact? Why?

Optimistic — with a specific concern. The optimism is structural: AI is the first technology in my lifetime that genuinely redistributes access to execution. You no longer need a team, a budget, or institutional permission to build something meaningful. That is a net positive for women, for independent thinkers, and for anyone who has been kept outside the systems that previously controlled output. The concern is physiological. We are accelerating the pace of knowledge work faster than human nervous systems were built to sustain. No one is governing the biological cost of that. If we do not build regulation — internal regulation, not just policy — into how we engage with AI-accelerated environments, we will see a health crisis that makes current burnout rates look modest.

Complete this sentence: "AI has changed my life by ______."

removing the gap between what I was capable of thinking and what I was able to build — and in doing so, made it possible for me to leave a system that was too small for what I came here to do.

Final Thoughts

What struck me most about this interview wasn't the list of things she built with AI. It was the way she described what AI actually changed. She doesn't see it as a writing assistant or productivity tool. She sees it as infrastructure. A bridge between thought and execution.

That distinction matters. Many of us still measure AI by how quickly it completes a task. Dr Negin Rajaipour, MD. measures it by whether it allows ideas that would otherwise remain trapped in our heads to become real. That's a fundamentally different way of thinking about the technology.

Her perspective also introduces an important caution. As AI accelerates what we're capable of building, it also accelerates the demands we place on ourselves. The challenge is no longer producing more; it's ensuring our judgment keeps pace with our ability to execute. If we can pair AI's speed with human discernment, empathy, and wisdom, its greatest contribution won't be replacing expertise, it will be amplifying it.

Your Business Doesn't Need More Hours. It Needs Better Systems: A Conversation with Laura MacGregor

Emma Wilson — Fri, 03 Jul 2026 06:30:21 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

Much of the conversation around AI focuses on what it can create. We compare models, debate prompts, and marvel at how quickly AI can write, design, or generate ideas.

But for many business owners, AI's greatest value isn't creating content. It's creating capacity.

When AI can organize calendars, monitor projects, summarize information, surface priorities, and connect the tools you already use, it becomes more than another productivity app. It starts functioning like an operational partner, quietly handling the work that keeps a business running.

That's exactly how Laura MacGregor approaches AI.

Rather than using it simply to produce more marketing content, she has built a connected AI workflow that helps her run a one-person business with the support of systems that would once have required additional staff. Her story shows that for many entrepreneurs, the biggest opportunity isn't working longer or even working faster. It's building smarter systems that make every hour count.

Meet the Interviewee

Laura MacGregor is the CMO and Principal of Savvy Marketing Works, a U.S.-based marketing consultancy specializing in strategic marketing leadership and business growth.

Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

I own a business and deliver marketing strategy work to clients. This means I'm doing everything from triaging email to CRM admin to categorizing financial transactions to invoicing to project management to actual strategic planning. As a team of one, there is nobody reminding me of things I may have missed or flagging issues. I am generally an organized person, but I was spending more time on those tasks than I should.

How does AI currently intersect with your work or personal life?

It now acts as an assistant, planner, and COO for my business at different times. For example, AI gives me a daily brief, a rundown of news in my key topics, plus client mention monitoring, calendar review, flagging relevant journalist queries from my inbox, and Asana queue checks. It keeps me up to date without needing to review those systems separately. I can ask it to do a task and I can do something else while that work is done in parallel. As a business owner, AI is helping keep my overhead low while at the same time optimizing processes and freeing up my own time.

What AI tools, if any, do you regularly use?

Claude (including Claude Cowork), Perplexity, and Lovable. I use AI features of tools like HubSpot, Descript, Zapier, and Otter. And I connect many tools to Claude so Claude becomes the interface for making updates to them, including Asana and Notion.

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

When AI went mainstream, it was touted for replacing marketing, or at least for exponentially increasing the output of what marketing can produce. Now anyone would have the ability to produce written content, a video, or a marketing plan. And that is possible... but we've since learned a few things.

First, context and prompting are key to getting the best possible output. Those without marketing experience might not know what to ask for and might not know whether the result is any good.

Second, we've since learned that generative AI usually does not produce high-enough quality content on the first go. The human element is still very much needed so you avoid the risk of publishing what's perceived as AI slop.

What was your initial reaction? Please explain why you experienced that emotion?

Skepticism. AI can give you words and ideas. But at least for now, it cannot replace years of experience, depth of product or audience expertise, and the gut feelings you have based on the combination of those. It is a helpful tool but it is not a replacement.

AI can give you words and ideas. But at least for now, it cannot replace years of experience, depth of product or audience expertise, and the gut feelings you have based on the combination of those. It is a helpful tool but it is not a replacement.

What has been the biggest positive impact AI has had on your life or work?

One of my favorite AI use cases is my weekly prep skill. It looks at all 6 of my calendars plus Asana and identifies priorities for the week, potential roadblocks (overbooked days), and then time blocks the work I need to do on a dedicated calendar around my meetings.

It plans my week so I don’t have to review all those systems and it points out problems before they happen and helps me prepare/adjust. Yes, I could manage my own calendar, but the benefit here is that it happens more quickly and it's able to look at both the very big picture and the details simultaneously. It doesn't simply shove everything that needs to be done in the time blocks. It takes into account how many hours I want to work that week and personal appointments and obligations, too. It recommends what might need to adjust. That is when I realized how impactful that it is.

As someone who balances family caregiving, chronic illness, and work, the "balance" part of this sentence can be hard to achieve. AI helps me ensure I'm not taking on too much while still meeting my deadlines. It keeps my workload reasonably aligned with everything that's going on.

What has been the biggest challenge, frustration, or downside?

The consistent quality of AI's output is frustrating. I spent a lot of time calibrating my tone of voice for writing. Sometimes content comes out spot-on. Other times it sounds like generic, AI-generated content. If I ask AI about it, it recognizes that I'm right and apologizes. It's almost like a human employee that's having an off-day, which of course you'd understand. But I think we expect machines to be consistent because they are machines!

Has AI changed how you think about your skills, value, creativity, or professional identity?

I can move faster and delegate work that isn't the best use of my time. I think about the best ways to do that.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

Yes, there is definitely a lot of hype about being left behind or replaced. I have a goal to spend 15 minutes a day learning or trying something new in an AI tool. I don't use it for things that feel to risky or potentially insecure.

Do you think AI has affected expectations at work?

Yes, there is an expectation that everyone use it. In my last job, the only AI tool we had access to was Copilot. People were sending back and forth emails that were read and responded to by Copilot. They were longwinded and often a waste of time. Those who can truly learn how to harness AI for analysis, efficiency, and the like will come out stronger.

What is one thing about AI that most people misunderstand?

That it has all the right answers. At the end of the day it's making its best guess, and it can still be wrong. Some of the mathematical calculations it makes can be incorrect. It is a tool. You still need to review and finalize what it gives you.

What advice would you give other women navigating AI's growing influence in their careers or lives?

Just try it. I went from basic research to 25+ use cases that integrate across my systems this year. Start with things you already know how to do or know the answer to so that you can verify whether it's working as expected. Context is important. My favorite piece of advice is to treat it like an intern on their first day - you'd give them the instructions and expectations for the task, not just tell them to "do x" and be disappointed when it's not right.

Are you more optimistic or more concerned about AI's future impact? Why?

Mostly optimistic, but it's going to be interesting when the profitability and true cost of AI levels out. I wonder whether the things I'm using it for today will still be affordable.

Complete this sentence: "AI has changed my life by ________."

empowering me to accelerate and optimize what I do as a solopreneur.

Final Thoughts

One idea from Laura's interview stayed with me is that while most people think about AI in terms of tasks, Laura thinks about it in terms of systems.

That's a subtle but important distinction.

Writing an email faster is useful. Having AI monitor six calendars, identify scheduling conflicts before they happen, prioritize work based on deadlines, family commitments, and available hours, and then build a realistic week around all of it? That's operating at an entirely different level.

It also highlights something I've seen repeatedly throughout this interview series. The women benefiting most from AI aren't necessarily using the most sophisticated prompts or chasing every new tool that launches. They're thoughtfully integrating AI into the realities of their lives and work.

Laura's story also serves as an important reminder that AI isn't a substitute for expertise. Marketing strategy, judgment, experience, and understanding customers still belong to people. AI can accelerate execution, but it can't replace years of accumulated knowledge or instinct.

Perhaps the most inspiring part of her experience is that AI isn't helping her become a bigger company. It's helping her become a better one.

For entrepreneurs, consultants, freelancers, and anyone running a business alone, that's an exciting possibility. You don't necessarily need to hire more people to gain operational leverage. Sometimes, you simply need better systems.

And increasingly, AI is becoming one of the most powerful systems available.

When AI Took Over Content, Olga Lany Doubled Down on Being Human [Interview]

Emma Wilson — Sun, 28 Jun 2026 17:53:48 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

One of the biggest fears surrounding AI is that it will eventually replace the work humans have spent years mastering. Writers worry about writing. Designers worry about design. Marketers worry about content. Communications professionals worry about messaging.

But the professionals getting the most value from AI aren't the ones trying to compete with it. They're the ones who have become even more intentional about the uniquely human parts of their work. That's exactly what stood out during my conversation with Olga Lany.

Working in public relations and partnerships means your reputation is built on credibility, communication, and authentic human connections. At first glance, it might seem like AI would threaten that kind of work. Instead, Olga sees the opposite happening. By taking repetitive tasks off her plate, AI allows her to spend more time where she creates the greatest value. She focused on building relationships, thinking strategically, and focusing on meaningful conversations rather than administrative work.

Meet the Interviewee

Olga Lany is a PR & Partnerships Manager at Admind Branding and Communications, a global branding agency headquartered in Poland that works with brands across Europe and beyond.

Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

Throughout most of my career, I have worked in the fields of language and human connection rather than with tools.

As a Senior PR & Partnerships Manager at Admind, a global branding and communications agency, my days revolved around media relations across Poland and Europe, building partnerships, organising events and conferences, and shaping how our experts present themselves publicly, particularly on LinkedIn.

I placed enormous value on the work of journalists, their judgement, credibility and the relationships I built with them, ideally face-to-face, formed the real foundation of what I did.

Everything else was manual, too: I drafted pitches and press materials by hand, did my own research and wrote and rewrote copy until the voice felt right. This approach was slower, but it meant that every text carried a point of view that I had shaped myself, and every relationship was built in person.

How does AI currently intersect with your work or personal life?

It of course touches almost everything I do, but in a variety of ways.

In practice, it has become my daily work partner. I use it to structure texts, speed up research and free up hours that I previously lost to repetitive tasks. This has taken me in a direction I never expected: I taught myself to 'vibe code'. Within a few days, I had built my first small app: one that reads several of my Outlook newsletters, filters the content and sends me Slack notifications with the important information. I had no idea what an API was before, so I'm genuinely proud of that achievement.

On the professional side, however, AI also forces me to confront some uncomfortable questions about my own field. Creating an authentic presence on LinkedIn is part of my job, so when I come across a post that is entirely AI-generated (AI headshot, AI comments, and the author replying to all of it via ChatGPT), I don't just notice it as a user; as a PR professional, I feel it too.

The flood of AI-generated 'slop' is impossible to ignore: many journalists have lost their jobs, and much of today's content is produced mainly to game SEO and SERP rankings rather than to express real opinion or expertise.

However, I see a silver lining in this. In a world flooded with synthetic content, building credibility for brands and individuals has to happen differently, and PR value and a genuinely authentic voice are becoming valuable again. That credibility increasingly comes from real human judgement, not volume. I think people in my profession, copywriters and others whose work is based on relationships and a genuine network rather than just output, are entering the most valuable period we have seen.

In my personal life, I mostly use AI to research family trips and to create quizzes and learning tools to help my daughter with her schoolwork.

It's funny, though, that I still don't have a single AI app or tool installed on my phone.

What AI tools, if any, do you regularly use?

I started with ChatGPT, mainly to help me structure texts and speed up my research. I also regularly use other tools to reformat or rework text outside the ChatGPT environment. I use Perplexity for research and Copilot and Gemini to compare results across models.

However, I feel most at home with Claude, together with all its connectors. I'm not a developer by background, so these tools aren't about replacing expertise for me — they're about giving someone without a technical background the confidence to build something useful anyway.

A recent example that I'm still excited about is as follows: I used a single prompt in Claude to automatically create a FigJam board, ran a live workshop with my team on that board and then asked Claude to read the board, summarise it and automatically send the summary to every workshop participant. Ultimately, it transformed the essence of the framework we had developed into a PowerPoint presentation for the management board.

My Claude is connected to pretty much every tool I use day to day, including Microsoft (especially Outlook), Slack, Canva, Google Drive, FigJam and more, which is exactly why it's become my go-to tool, including for the newsletter-to-Slack app I mentioned.

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

To be honest, I can't pinpoint one specific moment. It all happened organically. I'm still hit with that mix of amazement and shock almost every week. Just today, for example, I watched Adobe Firefly transform two photos and a single prompt into an impressive short animation with great resolution, the idea for which I wouldn't necessarily have come up with myself.

What was your initial reaction? Please explain why you experienced that emotion?

Excitement

That mix of fascination and unease stems from two different sources, but fascination has always been the stronger of the two for me.

I've never been afraid of technology, and I think that dates back to my childhood. My father was an electrical engineer who finished his studies around 1979, when computers first started appearing in Poland, and I grew up with Ataris and Commodores at home. I still remember experimenting with the earliest 'drawing' features on the Atari text editor on our old TV's black-and-white monitor...

I'm genuinely curious about change and enjoy streamlining my work so that I can devote more time and energy to creativity and the skills that depend on real human interaction - the tasks that only a person can perform.

I've never feared that technology would take my job or opportunities away. Quite the opposite, in fact, I see technology as something that expands my capabilities. I'm also happy (and a little proud) that I get to be the technology expert for my teenage daughter. As any parent of a teenager knows, that's not necessarily guaranteed!

But it is also important to recognise how much power something so exciting could carry and how quickly the line between 'creative tool' and 'tool that can manipulate reality' can blur. Change excites me and I enjoy learning new things, but that doesn't mean I stop considering what's at stake.

What has been the biggest positive impact AI has had on your life or work?

Honestly, the biggest impact has been the confidence it has given me to build things myself.

However, the real value isn't just the time saved, but it's what that time gets reinvested into. Every hour that AI takes off research, formatting or repetitive admin is an hour that I can spend on the things that I still think matter most in PR: building real relationships, reading a room and telling a story that lands because it was shaped by a human.

For me, that's the biggest positive impact: AI hasn't replaced the human part of my work; it's protected it.

What has been the biggest challenge, frustration, or downside?

What frustrates me most is the flood of poor-quality AI-generated content.

The hardest part is the impact on trust. My job is to build credibility for brands and individuals, and credibility used to be earned through consistency and authenticity over time. Now, I have to assume that a significant proportion of what I read, including comments and replies, may not be written by a real person. This makes distinguishing a genuine voice from a synthetic one more difficult and exhausting than it used to be, and it's frustrating to see something that's supposed to bring people closer together making us more sceptical of each other instead.

There's also a more personal, and almost amusing, downside that I've experienced a few times: a small wave of panic when I run out of tokens in Claude mid-task or when ChatGPT freezes. In those moments, I have to remind myself consciously that I have the competence, knowledge and know-how to do this work without AI. I did it for nearly two decades before any of these tools existed. Although, to be fair, without a computer or phone, I'd have zero chance of producing any results these days!

Has AI changed how you think about your skills, value, creativity, or professional identity?

AI has made me more aware of where my actual value lies.

Seeing content flooded with poor-quality AI-generated material and journalists losing work to it has made me far more deliberate about what I can offer that machines can't: real relationships, judgement about the meaning of a story, and a distinctive voice.

I used to take some of these things for granted as just 'part of the job'. Now, however, I recognise these as my core assets - things that will become more valuable as everything around them becomes automated.

So, if anything, AI has clarified my professional identity rather than diminishing it. My job isn't to compete with AI on speed or output volume. My job is to be the human credibility behind the work, the part that can't be prompted into existence.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

No, I've never actually felt that kind of pressure. In fact, it's usually the other way around. I'm often the one encouraging my team to experiment with new tools and ways of using them, rather than being pushed to keep up.

At Admind, the branding and communications agency where I work, everyone (designers, strategists and marketers) is encouraged to use AI.

However, the approach feels more inspirational than mandatory. Nobody sets you a deadline to 'learn AI by Friday'; people share what they've found useful and show each other what's worked, and this curiosity spreads naturally throughout the team.

Honestly, my own curiosity and excitement about new tools has always outweighed any external pressure. By the time anyone might think to encourage me to try something new, I've usually already been experimenting with it for a while. :)

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

While I haven't personally experienced AI creating direct bias or exclusion against me, I have definitely seen unfair practices play out in my industry. The clearest example of this is what has already happened to journalists. Many have lost their jobs as AI-generated, SEO/GEO-optimised content has flooded the space that used to belong to real reporting and expertise.

It feels genuinely unfair that people with real judgement and credibility are losing ground to content produced by a machine.

Do you think AI has affected expectations at work (productivity, speed, output, hiring, promotions, etc.)?

Definitely, particularly with regard to productivity and speed. Tasks that used to take hours, such as drafting a first version of a text, doing research or summarising a workshop, now take minutes, and this naturally resets expectations. Nobody has explicitly told me to 'do more, faster', but once you have experienced how much AI can compress, it becomes the new baseline against which you measure yourself, and probably what others expect from you too.

I see this most clearly in terms of output volume and turnaround time. Whereas a press pitch or a recap deck used to take a day, it is now expected within hours simply because the tools make that possible. The flip side is that this speed sets the floor, not the ceiling. You're still expected to contribute strategic judgement, relationships and polish. Output alone isn't enough anymore; it has to be both fast and genuinely good.

What advice would you give other women navigating AI's growing influence in their careers or lives?

My biggest piece of advice is not to wait until you feel 'technical enough' to start. Curiosity matters far more than a technical background ever will.

Secondly, focus on what makes you irreplaceable rather than trying to compete with AI on its own terms. AI can write and summarise quickly and produce a lot, but it can't build real relationships, read a room or earn someone's trust over time.

These are the very skills that many people have built entire careers on - communication, empathy and judgement - and they're becoming increasingly valuable as the internet fills up with synthetic content. Don't see AI as a threat to these skills; see it as something that finally frees up time to utilise them more.

Start exploring, stay curious, and never stop :)

Are you more optimistic or more concerned about AI's future impact? Why?

To be honest, I'd say I'm more optimistic than concerned.

Not in a naive way. I've seen the real downsides.

However, I'm optimistic because I think the flood of synthetic content makes real human voices more valuable, not less. For any of this to keep working, something has to stay real - these models need real stories, real data and real trust to train on.

People get tired of sameness. So I think the demand for authenticity will only grow.

For people like me, whose work is based on relationships and judgement, I believe there will always be a place. So yes, I'm optimistic, but this optimism depends on people choosing to continue building the human element rather than assuming AI will do it for them.

Complete this sentence: "AI has changed my life by __________."

...turning me, completely unexpectedly, into a confident "vibe coder" and giving me back the time to focus on the human relationships and creativity that originally attracted me to this line of work.

Final Thoughts

What I found most compelling about Olga's story is that it flips one of the biggest narratives around AI on its head.

We're constantly told that AI will replace writers, marketers, designers, communicators, and creative professionals. Yet Olga's experience points in a different direction.

The more AI takes over repetitive execution, the more valuable distinctly human qualities become.

Trust cannot be generated with a prompt.

Relationships cannot be automated.

Credibility cannot be synthesized.

These are things that are earned over years through judgment, consistency, empathy, and genuine human interaction. AI may accelerate the mechanics of communication, but it still relies on people to decide what is worth saying, who needs to hear it, and why it matters.

Reclaiming Time in the Age of AI: A Conversation with Sarah Gallucci

Emma Wilson — Wed, 24 Jun 2026 05:39:00 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

What Happens When AI Doesn't Help You Work More—But Helps You Work Less?

Much of the conversation around AI focuses on productivity, efficiency, and output. The assumption is that if AI helps us complete tasks faster, we'll simply use that time to do even more work.

But what if the real value of AI isn't producing more?

What if it's reclaiming time?

For many women, professional responsibilities don't end when the workday ends. Emails, grading, planning, administration, caregiving, household responsibilities, and personal commitments often blur the lines between work and life. As a result, free time becomes increasingly difficult to protect.

In this interview, writer, speaker, and professor Sarah Gallucci shares how AI transformed her relationship with work—not by changing what she does, but by helping her stop bringing work home. Her story explores productivity, balance, creativity, education, and why some of the most important parts of being human should remain untouched by AI.

Meet the Interviewee

Sarah Gallucci is a writer, speaker, and college professor based in the United States. Working independently while balancing teaching, writing, and speaking engagements, Sarah has embraced AI as a practical tool for reducing administrative burden and creating more space for both professional growth and personal fulfillment.

Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

Before I adopted AI into my work at the college, my work responsibilities and tasks would not be able to be completed during the work day. I was often bringing my work home (responding to emails, grading, and providing feedback) in the evenings when I would have preferred to turn work off and be with my family more presently.

How does AI currently intersect with your work or personal life?

AI intersects with my work and personal life by freeing me from tasks at work- so I’m more productive at work and more relaxed in the evenings and on weekends.

What AI tools, if any, do you regularly use?

Currently, I use Chat Gpt, Claude, Google translate.

Can you describe a specific moment when you realized AI was directly affecting your work, career, or personal life?

There was a week I stopped bringing home grading to do after dinner. It was two weeks into using Chat Gpt prompts for student emails, lesson planning, and feedback that I realized my life-work balance was profoundly going to change. From there, my AI curiosity grew and I used it for resumes, cover letter writing, meal plans, exercise plans and budgeting.

What was your initial reaction? Please explain why you experienced that emotion?

I was excited about AI because I saw the speed of it working- without compromising quality (in many cases, not all).

What has been the biggest positive impact AI has had on your life or work?

Using AI at work has helped me work on passion projects- I’ve done a TEDx talk since using it, published a book (that I wrote before the popularity of AI), ran my first half-marathon and lost over 20 pounds!

What has been the biggest challenge, frustration, or downside?

The downside is being an educator embracing exploration ethically, but seeing young people (my students) being unable to think or write without it.

Has AI changed how you think about your skills, value, creativity, or professional identity?

AI has made me lean more into the human things and cherish them- writing, art, music, nature, and my relationships. Those are areas of my life I don’t allow AI to touch.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

No, I’ve not felt any pressure to adapt AI- I have gone at my own pace. There are no rules with AI- not really. The playbook for how we used to work is gone. Therefore, I have been able to design my own journey with AI.

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

AI is inherently racist and the language it uses reflects that. The sentences (structurally) are bias towards upper class, white English language patterns.

Do you think AI has affected expectations at work (productivity, speed, output, hiring, promotions, etc.)?

For me, productivity and speed were always pressures I have felt as a college professor in higher education. The expectations before AI were unrealistic and remain so, they are also directly at odds with work-life balance and valuing of self care and family time. AI is the bandaid right now for a much larger issue- hustle and grind culture.

What is one thing about AI that most people misunderstand?

It does not make anyone’s writing better- it makes it worse. The friction of the writing process is necessary because without it people wouldn’t go on wonderful tangents, be curious and explore.

What advice would you give other women navigating AI's growing influence in their careers or lives?

Women need to get familiar with using AI, or they will be left behind. They should ask colleagues how they use it, friends and family. It’s a skill likely needed for higher paying jobs, promotions, or entrepreneurship.

Are you more optimistic or more concerned about AI's future impact? Why?

I am an optimist for AI.

Complete this sentence: "AI has changed my life by __________."

Giving me my life back

Final Thoughts

What resonated most with me about Sarah's story is that it challenges one of the most common assumptions about AI. Many people view AI as a productivity tool. Sarah views it as a freedom tool.

The difference matters.

For decades, technology has promised to save us time. Yet somehow, most professionals feel busier than ever. Work expands to fill every available hour, and the boundary between professional and personal life becomes increasingly difficult to maintain.

Sarah's experience offers a different perspective. Instead of using AI to squeeze more work into each day, she used it to reclaim evenings with family, pursue personal goals, publish a book, deliver a TEDx talk, improve her health, and invest time in the parts of life that matter most.

I also appreciated the nuance in her perspective. She's optimistic about AI while remaining thoughtful about its risks. As an educator, she sees both the opportunities and the dangers. She embraces AI's ability to remove administrative friction while defending the importance of critical thinking, creativity, curiosity, and authentic human expression.

Perhaps that's one of the most important lessons emerging from this interview series: the women benefiting most from AI aren't outsourcing their humanity. They're using AI to create more space for it.

As AI continues to evolve, its greatest impact may not be helping women work harder. It may be helping them spend more time on the people, passions, and pursuits that make life meaningful.

How AI Helped Jazz Cole Eliminate Decision Fatigue While Balancing a Startup, a Nonprofit, and a Full-Time Job

Emma Wilson — Mon, 22 Jun 2026 09:35:32 +0000

Part of an ongoing series exploring how women are experiencing the rise of AI in their work and personal lives.

AI's Most Underrated Benefit May Be Mental Clarity

When people talk about AI, the conversation usually revolves around productivity gains, automation, or job disruption.

But those discussions often miss a more subtle benefit.

For many women balancing multiple responsibilities, AI isn't just helping them work faster. It's helping them think more clearly.

Whether it's organizing schedules, reducing administrative burden, summarizing information, or removing hundreds of small daily decisions, AI can create something increasingly valuable: mental space.

That's what stood out in my conversation with Jazz Cole. Her story isn't about replacing employees, creating content at scale, or building the next AI-powered business. It's about using AI to bring order to a demanding life that includes a full-time job, a nonprofit organization, and a newly launched company.

Meet the Interviewee

Jazz Cole is the CEO of Cole International Enterprises LLC and a business operations professional based in the United States.

Interview

Before AI became widely adopted, how would you describe your work and daily responsibilities?

Before AI, I was doing a lot of manual admin tasks considering my business recently launched in 2026. I had to go through my emails one-by-one and deciding which ones were worth reading. Whenever I needed research done, I had to decipher through what I really needed given that google or whatever search engine would be feeding me information that wasn't actually relevant. I also had to create all of my documents and content from scratch rather than having templates I can reference.

How does AI currently intersect with your work or personal life?

Gemini will summarize emails for me when needed, I had a strategic assistant to help with marketing and sales which was an area of improvement for me in the beginning), Gemini will create my scheduled timetables so I don't have to organize my day.

I also run a nonprofit organization outside of my start up and it's helpful to plan my weeks so I can switch gears strategically without confusion. I no longer have to create templates from scratch, I can reference another document in my Google Drive and generate a new document and all I have to do is go through and create the content therein.

In my personal life, it's helpful to use AI for me to process anything from a logical point of view or if I need advice on a certain situation where I'm overthinking and I need to get it out of my head outside of my usual journalling.

I don't take everything it says at face value since I'm a critical thinker, but if it makes sense I'll conduct a trial and error experiment and see if it its suggestions work.

What AI tools do you regularly use?

Primarily Gemini because it connects to all my Google accounts, and the Notion AI agents.

Can you describe a specific moment when you realized AI was directly affecting your life?

In a negative way, I think there was a moment where I really needed to go to bed. I go to bed around 7:30-8pm, but I remember it being almost midnight on a Friday because my analytical brain kept coming up with questions I wanted to ask especially since I'm an otherthinker and I'm naturally curious and I kept going over specific scenarios about social dynamics.

What was your initial reaction?

Curiosity

I have a natural need to know things and anyone who has ever met me in person knows that I love to ask questions.

I'm an operations specialist so I'm constantly looking at how things work and I enjoy dissecting events, people, and places. I think there's a lot to learn about the world around us and I can't help myself, but keep asking questions.

What has been the biggest positive impact AI has had on your work?

Time tables have been a game changer!

I'm an HSP and I get decision-fatigue quite often and it took the guesswork out of how I'm going to get all my work done. I had a 9-5 job, running a nonprofit for almost 10 years and starting up a new business venture based on skills I developed. It's so easy to be overwhelmed by all that.

In a matter of months, I was able to juggle all three things and make it look easy.

What has been the biggest challenge or downside?

On a personal level, the challenge is to make sure it doesn't replace my faith.

It's easy to just ask ChatGPT or Gemini, or any other AI tool to answer all my questions, but I don't want AI to be the first thing I run to when I encounter life challenges or obstacles without consulting God.

I don't want it to take His place because I think if I were to rely on Gemini to solve all my problems, it's not going to allow me to trust myself when it comes to decision-making, and I don't want to make decisions from potentially biased information. Not to mention, that AI tools, from my perspective, look at things logically and sometimes a logical approach to certain circumstances are not required.

Has AI changed how you think about your skills, value, or professional identity?

I don't think it has, it's been more of an assistant to help me expand my ideas into something feasible.

Have you ever felt pressure to learn or adapt to AI faster than you were comfortable with?

Not at all. I was actually very anti-AI for the longest time. I heard people talking about how AI was going to take over everything, and I didn't believe that. I think AI is helpful and is not going away, but I started looking into it with a skeptical lens. I did my research to ensure it wouldn't take over my life.

Have you experienced any situations where AI created unfairness, bias, exclusion, or unexpected opportunities?

Not at all.

Do you think AI has affected expectations at work?

It actually sped up my productivity when it comes to building templates and data recycling for documents and forms I use consistently.

It saved me a lot of time to where I could focus on the content and not figuring out how to outline what I'm doing.

What is one thing about AI that most people misunderstand?

That AI is going to take over everything. I'm not a fear mongerer. I originally was skeptical about AI because I wasn't familiar with it, I'm not an early adopter of anything. I usually like to see how it works out for others and then that's how a build up my trust. I think that AI requires the willingness to learn how to use it responsibly and having the discipline to not rely on it all the time for everything.

What advice would you give other women navigating AI?

I would say that you need to educate yourself on what it does and what it can do for you. You don't want to adopt an AI tool and you don't even know what to do with it.

From a business operations perspective, I would say to look at what aspect of my business and/or life is unorganized or chaotic and look into what AI tools can do to help you and even ask friends/colleagues what they might be using it for so you can get an idea of what it can do for you. I remember asking some business mentors of mine how I could use it in my life and business and they said they use it to plan out their day as to what gets done.

Are you more optimistic or more concerned about AI's future?

Given what I know now, I'm a little bit of both. I'm optimistic about how it can help people, but I'm concerned about the younger generation and that they're taught how to use AI responsibly as they navigate our digital landscape, not to simply do their homework for them, but to use it as a tool to help them grasp concepts in their course work like an AI coach.

Complete this sentence: "AI has changed my life by..."

"...taking the guesswork out of my schedule."

Final Thoughts

What struck me most about Jazz's story is that she views AI very differently from many business leaders.

She doesn't talk about replacing work.

She doesn't talk about cutting costs.

She doesn't talk about building an AI-first company.

Instead, she talks about reducing mental clutter.

That's a perspective we don't hear often enough.

Many professionals today aren't struggling because they lack capability. They're struggling because they're carrying too many competing priorities at once. Work. Family. Side projects. Community commitments. Endless notifications. Endless decisions.

In that environment, AI's greatest contribution may not be helping us do more. It may be helping us decide what deserves our attention in the first place.

I also appreciated Jazz's emphasis on balance. She embraces AI without surrendering her judgment to it. She uses it extensively while remaining thoughtful about its limitations. In a world that often treats AI as either a miracle or a menace, that middle ground feels refreshingly practical.

Perhaps that's the real lesson from this conversation: the most successful AI users won't be the people who ask it to think for them. They'll be the people who use it to create enough clarity and structure that they can think better for themselves.

Are you a woman using AI in your work, business, studies, or daily life I'd love to hear your perspective. If AI has changed how you work, create, learn, lead, or think about your future, share your story in the comments. I'm always looking for new voices and would be happy to interview you for a future edition of this series.

How AI Gave a Solo Founder the Output of an Entire Team: A Conversation with Indre Saveike

Emma Wilson — Fri, 19 Jun 2026 05:36:01 +0000

Artificial intelligence is reshaping work for everyone, but its impact is not always experienced equally. Women often navigate different career expectations, leadership challenges, caregiving responsibilities, and workplace dynamics than men. As AI becomes embedded in our professional and personal lives, those differences deserve to be documented and understood.

This interview is part of an ongoing series exploring how women across industries are experiencing the rise of AI—not through headlines or predictions, but through real stories. The goal is to capture the opportunities, concerns, adjustments, and insights that emerge when AI becomes part of everyday life and work.

Meet the Interviewee

Indre Saveike is the Founder and Creative Director of Inprint Designs, a Lithuania-based wall art brand. As a solo founder responsible for everything from marketing and content creation to customer communication and business strategy, Indre has embraced AI as a way to expand her capabilities without expanding her team.

In Conversation With Indre

Before AI became widely adopted, how would you describe your work and daily responsibilities?

I was doing everything manually—writing product descriptions, drafting social content, researching competitors, and handling customer communication, all while managing design and fulfilment logistics. As a solo founder, the bottleneck wasn't creativity; it was execution capacity. There was always more to do than hours to do it.

How does AI currently intersect with your work or personal life?

AI is now embedded in almost every part of my workflow. I use it to develop content strategy, write and refine blog articles, generate ad copy variations, structure SEO outlines, and think through business decisions.

It functions less like a tool and more like a second brain—one that's available at any hour and doesn't need context repeated twice.

What AI tools do you regularly use?

Claude is my primary tool for writing, strategy, analysis, and problem-solving.

For visuals, I use ChatGPT to create interior mockups that show how my wall art looks in real-world settings. I also use Kling 3.0 for AI-generated videos and ElevenLabs for audio content.

Can you describe a specific moment when you realized AI was directly affecting your work?

The moment I realized AI had genuinely changed my work was when I produced a full content strategy, three blog article outlines, and a set of ad copy variations in a single afternoon—work that would have previously taken me the better part of two weeks.

I was a solo founder with no team, no agency, and a limited budget. That afternoon made it clear that the gap between what I could execute alone and what a funded competitor could execute with a team had significantly narrowed.

What was your initial reaction?

Curiosity.

My first instinct was to understand how far it could actually go—not just for basic tasks, but for nuanced creative and strategic work. I started testing the boundaries: could it understand brand voice? Could it reason through positioning decisions?

The answer was largely yes, and that kept me curious rather than comfortable.

What has been the biggest positive impact AI has had on your work?

It gave me execution capacity I couldn't have afforded otherwise.

As a solo founder running a wall art brand across multiple markets, I now operate with the output of a small team—without the overhead. That access has been genuinely levelling.

What has been the biggest challenge or downside?

The invisible labour.

When people see polished content or a well-structured campaign, they assume it was effortless because AI was involved. What disappears from view is the brief, the direction, the editing, the brand judgement—all the decisions that make the output actually good.

AI doesn't replace creative thinking; it just makes the execution faster.

Has AI changed how you think about your skills or professional identity?

Yes. It forced me to get clearer about what actually constitutes my value.

The skills that matter now aren't about execution speed; they're about taste, direction, and judgement. AI can produce content, but it can't decide what the brand should stand for, or know when something is off.

That clarity has been useful, even if it took some discomfort to arrive at.

Have you felt pressure to adapt?

Yes.

The pace of change creates a constant low-level pressure—not from a specific person or employer, but from the general sense that if you pause, you fall behind.

At times it felt less like opportunity and more like a treadmill that keeps accelerating.

Have you experienced any unexpected opportunities because of AI?

Absolutely.

AI gave me access to capabilities that would previously have required a funded team. For a solo founder in a smaller market, that access was significant and not something I take for granted.

Has AI affected expectations at work?

Absolutely.

The baseline for what one person can produce has shifted dramatically. That raises the floor for everyone—which sounds positive, but it also means the effort behind good work becomes increasingly invisible.

What is one thing people misunderstand about AI?

That using it means less human involvement.

In practice, the quality of AI output is almost entirely dependent on the quality of human input—the brief, the context, the editing, and the decisions about what to keep.

The human doesn't disappear; they just move upstream.

What advice would you give other women navigating AI?

Start using it before you feel ready.

The learning curve is real but short, and the gap between those who engage and those who wait is widening faster than most people realise.

Focus on what you bring that AI can't replicate—your perspective, your standards, your context—and use AI to amplify that, not replace it.

Are you optimistic or concerned about AI's future?

Cautiously optimistic.

The access it provides to people who previously couldn't compete on resources is genuinely meaningful. My concern is about the pace—both in terms of how quickly expectations shift, and how little time there is to think carefully about what we're building toward.

Complete this sentence: "AI has changed my life by..."

"...making it possible to run a serious business alone, without compromising on quality or ambition."

Final Thoughts

One theme stood out throughout my conversation with Indre: AI's biggest impact isn't replacing people—it's expanding what individuals can accomplish.

For years, scaling a business often required hiring teams, agencies, consultants, and specialists. Today, AI is allowing founders, creators, and professionals to access capabilities that were previously out of reach. That shift is especially significant for women building careers and businesses in environments where resources, funding, or support systems may not always be equally available.

At the same time, Indre's story highlights an important reality. The value of human judgement, creativity, taste, and strategic thinking hasn't diminished. If anything, those qualities have become more important. AI can accelerate execution, but people still decide what is worth creating and why.

As I continue this interview series, I'm increasingly convinced that the future belongs neither to humans alone nor to AI alone. It belongs to people who learn how to combine their unique perspectives with increasingly powerful tools.

And for many women like Indre, that future is already here.

Are you a woman using AI in your work, business, studies, or daily life?
I'd love to hear your perspective. If AI has changed how you work, create, learn, lead, or think about your future, share your story in the comments. I'm always looking for new voices and would be happy to interview you for a future edition of this series. The more experiences we document, the better we'll understand how AI is shaping the lives of women around the world.

Why Legacy Application Modernization Is No Longer Optional for Businesses That Want to Survive

Emma Wilson — Sun, 14 Jun 2026 11:12:59 +0000

Why this matters in 2026: Running outdated systems isn't just a technical inconvenience — it's a strategic liability. This blog breaks down exactly why modernizing your legacy applications has become a non-negotiable business decision, what the real stakes are, and why the companies investing now are pulling ahead of those still waiting.

Every week, somewhere in an enterprise boardroom, a CTO gets asked a version of the same question: "Can't we just keep the old system running a little longer?"

The honest answer is: yes, you can. But the cost of that decision compounds faster than most leaders realize. A 2023 report by Rimini Street found that organizations spend up to 75% of their IT budgets just maintaining legacy systems — leaving barely a quarter for innovation, new capabilities, or competitive differentiation. That's not a maintenance budget. That's a survival tax.

The businesses that understand this — and act on it — are the ones building distance between themselves and their competitors. Those that don't are slowly accumulating a technical debt that eventually becomes impossible to repay without a crisis forcing the hand.

The good news? There's a clear path forward. Understanding the step-by-step process of legacy application modernization is what separates organizations that modernize strategically from those that modernize reactively — usually at twice the cost and half the control.

Read on.

Why Legacy Application Modernization Has Become a Defining Business Imperative

Legacy systems don't announce their obsolescence. They degrade quietly — performance creeps slower, integrations become more fragile, the engineers who originally built them retire or leave, and one day you realize that a competitor launched a feature in two weeks that would take your team six months. At that point, the conversation about modernization is no longer optional.

Here's what's actually at stake.

1. Competitive Agility Determines Market Position

Speed to market is a function of your technology stack. Organizations running modern, cloud-native architectures can deploy new features in hours. Those running monolithic legacy systems — where every change risks cascading failures across tightly coupled components — measure deployment in weeks or months.

According to the 2024 DORA State of DevOps Report, elite-performing technology organizations deploy changes 973 times more frequently than low performers. That's not a slight edge. That's an entirely different class of business capability. Legacy systems are what put organizations in the low-performer category, not a lack of talent or ambition.

2. Security Vulnerabilities in Legacy Systems Are Existential Risks

Vendors stop releasing security patches for outdated platforms. When that happens, every unpatched vulnerability becomes an open invitation. The IBM Cost of a Data Breach Report 2024 found that the average cost of a data breach has reached $4.88 million — a 10% increase over the prior year. Organizations running legacy infrastructure with known unpatched vulnerabilities face disproportionately higher exposure.

This isn't a theoretical risk. In 2023, multiple healthcare and financial organizations were breached specifically through unpatched vulnerabilities in legacy ERP and CRM systems that vendors had stopped supporting years prior.

3. Talent Retention Becomes Harder with Every Year

Developers don't want to build their careers on COBOL, AS/400, or decade-old .NET frameworks. When your engineering team is spending most of its time patching and maintaining outdated code rather than building new things, turnover accelerates. The 2024 Stack Overflow Developer Survey found that working with modern technology stacks ranks among the top three factors influencing developer job satisfaction.

Losing experienced engineers from a legacy system is also uniquely painful — institutional knowledge about undocumented system behavior walks out with them.

4. Customer Experience Is Directly Constrained by What Your Systems Can Do

End users — whether they're your enterprise customers or consumers — have expectations shaped by the best digital experiences they've ever had. They aren't comparing your portal to your industry average; they're comparing it to what they experienced last on Amazon, Stripe, or their favorite mobile app. Legacy applications rarely produce the kind of fluid, responsive, personalized experiences modern users expect.

The downstream effect on customer retention, NPS scores, and revenue is real. Gartner estimates that poor customer experience tied to technology constraints costs enterprises an average of 5–15% of annual revenue in lost retention.

5. Regulatory Compliance Is Becoming Harder to Maintain on Legacy Infrastructure

Data privacy regulations — GDPR, CCPA, HIPAA, and emerging AI governance frameworks — are changing fast. Legacy systems were not designed with modern compliance requirements in mind. Retrofitting compliance controls onto aging infrastructure is expensive, error-prone, and often incomplete. Regulatory penalties for non-compliance are rising: GDPR fines alone reached €2.1 billion in 2023 across European regulators.

The Path Forward: Modernize with Clarity, Not Panic

None of this is an argument for reckless, wholesale replacement of your systems overnight. The smartest organizations approach this methodically — assessing their portfolio, prioritizing systems by business impact and risk, and executing modernization in structured phases.

Understanding the planning for and the step-by-step process of legacy application modernization is what gives leadership teams the confidence to commit to this path without catastrophic disruption. Modernization doesn't have to mean a complete rewrite. For some systems, re-platforming to the cloud is sufficient. For others, refactoring specific components or encapsulating legacy functionality behind modern APIs can buy years of additional runway while a longer-term strategy is executed.

The point is this: every month of inaction has a compounding cost. Security exposure accumulates. Technical debt deepens. Competitor agility increases. Talent gets harder to retain.

The organizations winning right now are not the ones that waited until crisis struck. They are the ones that treated modernization as a continuous, strategic practice — not a one-time project.

If your legacy systems are slowing you down, the most important step is the first one: get a clear-eyed assessment of where you stand and build a roadmap that matches your business priorities with executable technology strategy. That starts today.

Why Your Gen AI POC Keeps Dying Before Production

Emma Wilson — Sun, 31 May 2026 11:59:25 +0000

70% of enterprise AI initiatives fail to make it past the proof-of-concept stage. That number has been cited across research from McKinsey, Gartner, and a half-dozen other analyst groups. And yet the AI spend keeps climbing and the POC graveyard keeps growing. The paradox is almost embarrassing: enterprises are allocating more budget than ever to generative AI development services for enterprises, and fewer projects are making it to production than most people will admit in public.

The reason isn't a technology gap. The models are capable. The tooling has matured considerably. The failure pattern is almost always structural, and it almost always starts with the same misdiagnosis: people treat a POC as a scaled-down version of the real thing, when it's actually a completely different kind of problem.

The POC Was Never Designed to Survive Contact With Your Organization

A typical POC is built for one thing: demonstrating that a capability is technically feasible. You pick a clean slice of data, limit the scope, move fast, and show stakeholders something that works. That's the right approach for a POC. The problem is that most teams then try to take that artifact and scale it, rather than treating the pilot phase as a rebuild with different constraints.

I've watched this happen on more projects than I'd like to count. A team spends six weeks building a document Q&A assistant on a curated subset of internal documents. The demo is impressive… fast, accurate, coherent answers. Leadership approves a broader rollout. Three months later, the system is still not in production.

What happened? The real document corpus has permission layers no one mapped. The enterprise search system it needs to pull from has rate limits nobody factored in. The legal team has questions about what data the model is seeing. The IT security review alone takes six weeks.

The issue is structural, not experimental. The POC was optimized for a best-case scenario that doesn't exist in production.

Five Things That Actually Kill Gen AI Projects After the Demo

These aren't hypothetical failure modes. They are patterns that come up repeatedly in production-stage engagements, regardless of company size or industry.

1. Data infrastructure that was never meant to support real-time retrieval

POCs usually work off pre-processed, static datasets. In production, you need fresh data, access control enforcement, and semantic search at a scale that most enterprise data infrastructure wasn't built to support. RAG pipelines over 100,000+ documents with freshness requirements under 24 hours are a different engineering problem than anything a POC answers.

2. Integration debt with existing systems

The AI component is rarely the bottleneck. Connecting it cleanly to your CRM, ERP, or knowledge management system — while respecting existing authentication, roles, and data contracts — is where timelines explode. Pre-built connectors help, but most enterprise environments have enough customization that integration work consistently runs 40-60% longer than estimated.

3. No evaluation framework beyond 'it felt right in the demo'

Production systems need measurable quality thresholds — hallucination rates, retrieval precision, latency at percentiles, cost per query. Most POCs have none of this. When accuracy degrades in production on queries that weren't in the demo set, the team has no baseline to compare against and no automated way to catch regression. You end up doing manual spot-checks indefinitely, which is not a sustainable operating model.

4. Security and compliance reviews treated as an afterthought

In regulated industries especially, the gap between what's technically possible and what can be deployed is substantial. PII handling, audit logging, access controls, AI Act compliance obligations in EU markets — none of this can be bolted on at the end. Teams that don't build these in from the architecture phase routinely spend more time on compliance remediation than on the original build.

5. No ownership of the system post-deployment

LLMOps is not optional. Models drift. Retrieval quality degrades as underlying data changes. Prompt performance shifts when the base model gets updated by the vendor. Without a monitoring layer and a team responsible for ongoing optimization, production systems quietly deteriorate over weeks and months. The 2024 AI Adoption Report from Wharton AI & Analytics Initiative found that four in five organizations expect ROI from AI investments within two to three years — but that timeline assumes the system keeps working, which requires active maintenance, not just deployment.

The Architecture Decisions Made During a POC That Are Nearly Impossible to Undo

Some of the most expensive production problems I've seen traced back to decisions made in week two of a six-week POC, when the priority was moving fast. Model selection is the obvious one — teams pick a vendor API because it works well for the prototype, then discover they're locked into token pricing that doesn't survive scale or compliance requirements that don't fit their industry. Switching models mid-project is not a find-and-replace operation.

Orchestration architecture is another. Building directly against a foundation model API without an abstraction layer means every infrastructure change, model upgrade, or vendor switch touches the application layer. Teams that invest a few weeks upfront in clean orchestration patterns — LangChain, LlamaIndex, or a custom pipeline depending on the use case — spend dramatically less time firefighting later.

The same logic applies to vector database choices. Not all retrieval architectures perform equally at scale, and migrating embeddings from one vector store to another after 200,000 documents have been indexed is not a small operation. That assumption no longer holds that you can defer these decisions until production.

"Most enterprises come to us having already run a POC somewhere internally. The challenge is rarely the AI capability itself — it's that the POC was built without the governance, data architecture, or integration scaffolding that production systems actually require. We're often rebuilding from the ground up, not extending what already exists." explained Maitray Gadhavi, VP of Sales at Radixweb, an organization that offers gen AI development services.

What a Production-Ready Gen AI Initiative Actually Looks Like From the Start

The teams that consistently get from POC to production in under six months share a few operational habits that others don't. First, they treat the POC and the production pilot as two separate workstreams with different success criteria. The POC answers: can this work? The pilot answers: can this work here, with our data, integrated with our systems, at the required accuracy, within our cost model?

Second, they establish evaluation datasets before they write a line of application code. A set of 500 to 2,000 representative queries with known expected outputs becomes the continuous benchmark. Every architecture decision gets tested against it. This sounds obvious. Most teams skip it because it requires upfront work that doesn't produce a visible demo.

Third, they involve security and platform teams in week one, not week eight. Not because it's bureaucratically correct, but because the architectural constraints those teams surface — about data residency, network topology, authentication models — fundamentally shape what you build. Finding out about them after the fact is one of the most reliable ways to blow a deadline.

The organizations getting real production throughput from their AI investments are treating this as a systems engineering problem, not a machine learning problem. The model is almost never the hard part. The hard part is everything the model sits inside of.

Teams considering serious investments in this space (whether building internally or working with a development partner) should be asking for production references, not demo credentials. The question to ask any vendor or internal team lead is: show me a system you built six months ago that's still performing at spec today. That answer tells you more than any architecture diagram.

Your Organizational AI Adoption Metrics Are Lying (Plus How to Measure Real Adoption)

Emma Wilson — Sat, 23 May 2026 18:43:20 +0000

Most enterprise AI dashboards look healthy right now. Login counts are rising. Pilot programs are multiplying. Internal copilots have thousands of registered users. Executive updates show “AI-enabled productivity gains” across multiple functions.

Then you look closer.

Teams are still routing work through old workflows. Engineers bypass approved AI tooling and use consumer models instead. Analysts copy outputs into spreadsheets because downstream systems were never redesigned. Support teams experiment with AI during quiet periods but revert to manual processes under operational pressure.

The metrics say adoption is accelerating. Operational behavior says otherwise.

That contradiction is becoming one of the defining enterprise technology problems of 2026. AI usage is easy to measure. AI dependency is not. Most organizations are conflating exposure with operational integration, and that distinction matters far more than leadership teams currently admit.

According to McKinsey’s State of AI research, 88% of organizations report AI use in at least one business function, but only about one-third say they have scaled AI beyond experimentation. That gap is the real story. The industry has largely solved AI access. It has not solved operational adoption.

That assumption no longer holds: deploying AI tools does not mean the organization has become AI-capable.

Most Enterprise AI Metrics Measure Activity, Not Dependence

The first generation of enterprise AI metrics emerged from SaaS adoption playbooks. Monthly active users, prompt counts, session duration, license utilization, and completion rates became default reporting layers because they were easy to collect.

Those metrics are not useless. They are just incomplete.

An employee opening an AI assistant twice a week tells you almost nothing about whether AI has materially changed delivery speed, decision quality, process design, or cost structure. In many organizations, employees are experimenting with AI while core operational systems remain structurally unchanged.

This is why so many executive AI reviews feel disconnected from business outcomes. The reporting emphasizes interaction volume rather than workflow substitution.

A large insurance enterprise may report that 70% of underwriters use AI summarization tools. That sounds impressive until you discover policy review throughput improved by only 4%, because legal validation, claims escalation, and document routing were never redesigned around AI-assisted workflows.

AI adoption only becomes economically meaningful when workflows start assuming AI participation by default. Until then, the organization is mostly funding parallel experimentation.

This is where the distinction between optional use and operational use becomes critical. Optional use improves convenience. Operational use changes system behavior.

According to recent industry reports, nearly 1 in 3 AI systems are used optionally, not operationally.

That pattern is increasingly visible across enterprises deploying copilots, internal assistants, and retrieval-based knowledge systems. Employees try them. Some employees even like them. But the business process itself remains fundamentally human-routed.
In practice, this becomes the real bottleneck.

What Real AI Adoption Actually Looks Like

Real adoption is visible operationally before it is visible culturally. Mature organizations stop debating whether employees “like” the tools because AI participation becomes embedded into execution paths.

You can usually identify real adoption through five observable shifts.

1. Workflow orchestration changes

The strongest indicator is not usage volume. It is process redesign.
If AI-generated outputs still require manual copying, manual approvals, or disconnected validation steps, the organization has not operationalized AI. It has added an assistant layer on top of existing operational debt.

Mature implementations redesign workflows so AI outputs become native system inputs. Ticket triage routes automatically. Knowledge retrieval feeds directly into service workflows. Engineering copilots integrate with testing pipelines and policy controls rather than existing as isolated interfaces.

That transition requires architecture work, not just tooling procurement.

2. Human review becomes targeted instead of universal

Early-stage AI deployments force humans to review everything equally because trust models are immature. That approach does not scale.
Operational adoption appears when organizations develop confidence segmentation. Low-risk outputs move autonomously. Medium-risk outputs receive selective review. High-risk decisions remain fully supervised.
This is how scalable AI operations actually emerge in practice. Not through blind automation, but through calibrated operational trust.
Research around developer AI adoption increasingly supports this model. Human-AI collaboration dominates successful enterprise usage patterns, while fully autonomous workflows remain limited outside tightly scoped domains.

3. AI usage survives operational pressure

Pilot behavior collapses during stress events. Real adoption does not.
One of the most reliable indicators of maturity is whether teams continue using AI during peak operational load. Customer escalations, release incidents, financial close cycles, and compliance reviews expose whether AI systems are genuinely trusted.

If teams abandon AI under pressure, the organization never operationalized trust.

That is only part of the story, though. Many enterprises misdiagnose this as a model quality problem when the actual issue is governance ambiguity. Employees revert to manual execution when accountability boundaries remain unclear.

4. Metrics move beyond productivity theater

“Hours saved” has become the vanity metric of enterprise AI.

Most organizations cannot validate those estimates rigorously because they rarely measure downstream operational effects. Faster content generation means little if review queues expand. Faster code generation means little if defect remediation rises six weeks later.

Real measurement frameworks track system-level outcomes:

Cycle-time compression across complete workflows
Reduction in escalation frequency
Error-rate changes under operational load
Margin improvement tied to process redesign
Decision latency reductions
Dependency reduction on scarce expert roles

Those are harder metrics to capture because they require cross-functional instrumentation rather than isolated AI telemetry.

But those metrics reflect operational change instead of interface activity.

5. Governance becomes invisible infrastructure

Immature organizations treat AI governance as a review committee. Mature organizations treat governance as execution infrastructure.

Access controls, retrieval boundaries, prompt logging, policy enforcement, model routing, and auditability become embedded into platforms instead of existing as separate oversight functions.

This distinction matters because operational adoption collapses when governance introduces friction. Employees will always route around systems that slow execution.

According to Deloitte’s enterprise generative AI research, more than two-thirds of respondents say fewer than 30% of their AI experiments will scale operationally in the near term. That is not primarily a model problem. It is an organizational systems problem.

Why So Many AI Programs Stall After Initial Success

Most stalled AI programs share the same structural pattern. Leadership teams optimize for visible deployment rather than workflow redesign.
The first phase looks successful because experimentation creates immediate novelty and localized productivity improvements. Then complexity emerges.

Data boundaries become inconsistent. Compliance requirements expand. Integration work slows execution. Teams discover that model quality is only one variable inside a much larger operational chain.

This is where many enterprises quietly enter what can best be described as “adoption inflation.” Reported usage remains high while operational dependency plateaus.

Recent industry reporting reflects this tension clearly. Surveys continue showing rising AI investment, yet many organizations admit adoption decisions were driven more by competitive pressure than operational readiness.

Radixweb's recently released field intelligence report on AI failure highlights a similar trend emerging across enterprise delivery environments: organizations consistently underestimate the operational redesign required to move from experimentation into durable workflow integration.

That observation aligns with what many technology leaders are now seeing internally. AI does not fail because employees resist it. AI stalls because enterprise operating models were never rebuilt around machine participation.

The Next Phase of Enterprise AI Will Be Measured Differently

The market is already shifting away from deployment metrics toward operational dependency metrics.

Boards increasingly want evidence that AI changes cost structures, delivery velocity, resilience, or strategic capacity. “Users onboarded” no longer answers that question. Neither do prompt counts. The next generation of enterprise AI measurement will likely focus on operational substitution rates:

What percentage of workflows assume AI participation?
Which business processes fail without AI augmentation?
How much decision latency disappears because AI is embedded upstream?
Which teams materially changed staffing models because workflows evolved?

Those are more uncomfortable questions because they expose whether the organization actually transformed its operating model.

The companies seeing meaningful AI returns are becoming more selective, not less selective. McKinsey’s recent research suggests high-performing enterprises concentrate AI efforts into fewer, strategically important domains instead of spreading pilots across the entire organization.

That shift signals where the industry is heading next.
Enterprise AI maturity will not be defined by how many employees touched an AI system this quarter. It will be defined by how many critical workflows became economically or operationally dependent on AI participation without sacrificing governance, reliability, or accountability.
Everything else is activity reporting.