As a 25-year-old who has traversed the path from designer to full-stack developer, I've found myself increasingly immersed in what I call the "AI bubble." Inside this bubble, ChatGPT, Claude, Perplexity, and dozens of specialized AI tools are everyday companions—so commonplace that it's easy to forget that not everyone shares this reality.
The Revelation
I had my wake-up call during a family dinner last month. My aunt, a seasoned corporate lawyer with 20 years of experience, was complaining about spending hours drafting preliminary case analyses. When I casually mentioned she could use ChatGPT to create initial drafts, her expression shifted from exhaustion to confusion.
"You mean that robot thing that makes pictures?" she asked.
This wasn't an isolated incident. My uncle, who meticulously researches investment opportunities, spent weeks gathering information about gold monetization schemes. When I showed him how Perplexity could compile and synthesize that research in minutes, he was simultaneously amazed and slightly irritated at the hours he'd wasted.
These moments made me realize: the gap in AI literacy isn't just between tech and non-tech sectors—it's a chasm.
The Surprise Within Tech
What's more surprising is finding this gap within the technology industry itself. In my previous role, I discovered that one of my managers—a senior developer—wasn't even aware of GitHub Copilot and how it integrates with VS Code. When I used it to accelerate my coding, he expressed concern that the company would reprimand me for "using AI to generate code and not writing it on my own."
This disconnect extended to our business analyst who had no idea about any AI tools. Instead of comprehensive documentation, I received random notes strung together with basic diagrams (she didn't know Figma either).
The most egregious example came when our company, despite limited knowledge about generative AI, decided to build their own LLM from scratch. They wasted countless months and substantial resources on this venture when all they really needed was a helpful chatbot trained on company data to help users learn more about their products. A pre-trained model with some fine-tuning would have accomplished this goal in a fraction of the time.
It wasn't just about wasting time but also squandering money. These valuable resources could have been directed toward more pressing needs, like rewriting legacy code for current frameworks. The irony reached its peak when the company later initiated massive layoffs, citing how "AI reduces the workload of employees, hence we need fewer employees to do the same amount of work"—all while most of the decision-makers demonstrated a fundamental misunderstanding of the very technology they used to justify cuts.
This contradiction reflects a broader pattern in the industry: organizations racing to implement AI technologies—or use them as justification for restructuring—while many of their decision-makers don't understand what these tools actually do or how they could be effectively integrated into existing workflows.
Bridging the Gap
I've started to see this awareness gap as a responsibility for those of us inside the bubble. Not in a condescending "let me show you the future" way, but through practical demonstrations that connect directly to people's daily challenges.
When I showed my aunt how to use an AI assistant to create the first draft of a standard cease and desist letter, she didn't just see a cool technology—she saw 45 minutes of her day reclaimed. That's the language that matters.
The most effective bridge-building moments haven't come from explaining how large language models work or discussing transformer architectures. They've come from simply sitting next to someone struggling with a repetitive task and saying, "Can I show you something that might help?"
Looking Forward
As AI tools become more powerful and more specialized, this awareness gap risks widening rather than narrowing. The sheer volume of new applications makes it challenging even for those within the bubble to stay current.
Perhaps the most important conversation isn't about artificial intelligence at all—it's about human communication. How do we translate the benefits of these tools into terms that resonate with daily human experiences? How do we ensure that technological literacy becomes a bridge rather than another dividing line in society?
For now, I'm starting small. I've scheduled a "Tech Thursday" lunch with my team where we each share a tool we've discovered. I'm helping my aunt create templates for her most common legal documents. And I'm learning to step outside my bubble more often, to remember that what seems obvious within my daily context remains mysterious—and potentially transformative—to many others.
The AI revolution isn't just about building better models or more impressive applications. It's about ensuring that the benefits reach beyond the bubble, into courtrooms, classrooms, small businesses, and family dinner tables. That's the gap we need to close.
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