Adopting AI presents significant challenges for many businesses. While the technology is transformative, moving beyond the buzz and implementing AI meaningfully across an organization is where most companies fall short.
Shopify’s journey, however, offers a powerful example of how to scale AI successfully. This success is not only due to the right technology but also the alignment of culture, leadership, and infrastructure.
Here’s what we can learn from Shopify’s approach to AI adoption.
A Foundation Built on Leadership and Culture
In April 2025, Shopify’s CEO, Tobi Lütke, issued a memo calling for the reflexive use of AI across the company.
This decision wasn’t made on a whim, it was the culmination of years of groundwork.
Shopify had already been embracing AI long before that memo, making it a logical next step for the company.
The key takeaway here is the importance of leadership alignment. At Shopify, leadership had already been actively working to make AI a company-wide priority long before the memo was sent.
By defaulting to “yes” on new tools and technologies, they removed the typical barriers that slow AI adoption in most organizations.
This alignment made it easier for employees at all levels to adopt and use AI tools effectively without having to wait for the politics of vendor choice and lengthy approvals.
Building the Right Infrastructure
AI adoption is rarely about finding the right tool or model. More often, it’s about creating the infrastructure to support it.
Shopify’s infrastructure-first approach ensured the company could scale AI adoption smoothly across teams without chaos.
They built a centralized LLM (large language model) proxy and an MCP (Model Context Protocol) system that enabled easy access to AI tools while managing them effectively.
This infrastructure is crucial for scaling AI within any organization. Rather than simply deploying new AI tools, Shopify’s team focused on creating a foundation that allowed them to integrate these tools across different departments.
Extending AI Across Functions
At many companies, AI is often confined to engineering teams, with other departments left out of the conversation.
Shopify flipped this model. They gave employees from sales, marketing, and revenue teams access to the same AI tools as engineers.
This democratization of AI meant that creative use cases could emerge from anywhere in the company.
This jives well with my experience over the last 2-3 years; some of the most impactful AI implementations are actually outside of product and engineering, often in Operations or Marketing.
For example, non-technical sales representatives started using AI to automate site audits and generate detailed performance comparisons between prospective merchants' websites and Shopify's benchmarks.
This broad access to AI is a key lesson. If you want AI to drive real business results, it needs to be a tool that everyone in the company can use.
Fostering AI fluency across all departments unlocks new opportunities and creates an environment where innovation can flourish and you avoid the pitfalls of inadvertently looking like you are prioritizing one team over another.
AI as a Tool for Deeper Insights
Many companies view AI as a tool for automation. At Shopify, however, the real value of AI lay in its ability to surface deeper insights.
This is what we in the AI engineering world refer to as "context engineering." It involves using AI to provide insights that encourage critical thinking and continuous improvement.
For instance, Shopify used AI to automatically generate updates on project progress, helping teams stay on track. However, these AI-generated updates weren’t final.
Team members were encouraged to engage with the output, challenging the AI’s conclusions and improving the final result.
This process drove deeper engagement with the work and empowered employees to think critically about how AI could be used to enhance their decision-making.
The lesson here is simple, when implemented correctly, AI can provide insights that push employees to rethink how they approach their work, making them more effective in their roles and an accelerant.
The Role of Interns and Early-Career Hires
One unexpected but valuable aspect of Shopify’s AI transformation was the role played by interns and early-career hires.
These employees, often referred to as “beginners,” brought a fresh perspective and a willingness to experiment with new AI tools.
Their ability to adopt new technologies quickly and without bias led to some of the most creative AI use cases within the company.
The key takeaway here is hiring for a mindset.
Interns and early-career hires often have fewer preconceived notions about “how things should be done,” which enables them to find new and innovative ways to apply AI tools.
They naturally become “AI natives,” unafraid to experiment with new technologies and explore their potential.
We’ve seen this at our own company, Bottega8…our junior engineers, product, and operations team members redefine workflows with AI in mind in ways that we would have never imagined.
It creates an awesome work culture where fresh approaches motivate employees to see things anew!
AI as a Tool for Process Optimization
One of the most powerful insights from Shopify’s AI adoption was how AI helped the company uncover process power.
AI can completely transform how work gets done by revealing inefficiencies and reordering tasks to eliminate waste, giving humans more leverage.
Take Shopify’s automated site audit tool, for example. What used to be a time-consuming manual process is now automated, saving time and providing valuable insights much earlier in the sales funnel.
By rethinking when and how site audits are conducted, Shopify changed the way it approached prospects, which resulted in more efficient sales processes.
Scaling AI for Long-Term Success
This is a true case study for understanding how, and when, AI delivers real business impact.
By revealing hidden inefficiencies, AI helps companies optimize operations and improve productivity in ways that compound over time.
Shopify’s shared team success was driven by its focus on building a culture that supported AI at every level, symbiotically between human and AI in ways that felt empowering.
By following Shopify’s lead, businesses can ensure that AI adoption can move beyond the “doom and gloom” narratives of dystopian sci-fi novels and instead become a fundamental driver of success that keeps employees happy.
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Nick Talwar is a CTO, ex-Microsoft, and a hands-on AI engineer who supports executives in navigating AI adoption. He shares insights on AI-first strategies to drive bottom-line impact.
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