After a year consulting enterprises on AI strategy, I’ve noticed something that keeps me up at night.
The companies investing millions in AI pilots, governance frameworks, and “centers of excellence” are moving slower than individuals teaching themselves to build in a weekend.
This isn’t a criticism—it’s an observation with consequences.
The Enterprise Paradox
Large organizations are doing what large organizations do: piloting, assessing risk, replacing individual processes, building consensus. This is rational behavior. It’s also dangerously slow.
Most enterprises I’ve worked with don’t have an AI vision. They have AI activity. Pilots without purpose. Implementation without imagination. They’re learning what AI can do, but they haven’t asked what they want AI to be.
Meanwhile, the infrastructure costs for AI-native startups are collapsing. The talent barrier is lowering. The gap between “Fortune 500 resources” and “two engineers with clarity” is narrowing faster than boardrooms realize.
I’m not predicting mass disruption tomorrow. I’m observing that the moat many enterprises assume they have—scale, data, capital—may matter less than speed and vision in the next decade.
What Actually Changes When You Use AI Daily
I don’t just advise on AI. I use it constantly, because theory without practice is consulting malpractice.
Here’s what shifted for me: a website that would have taken a month now takes less than an hour. Understanding and researching a completely new market, from multiple months, cut down to hours. Not because I’m cutting corners—because I’m operating at a higher level of abstraction. AI handles implementation. I handle intent, architecture, refinement.
The quality is better, not just faster. I can translate technical theory into working output, then optimize. I’m not letting AI drive—I’m letting it accelerate while I steer.
This is the unlock most people miss. AI doesn’t replace your judgment. It gives your judgment more leverage.
The Question No One Wants to Answer
Here’s where I’ll be honest: I don’t have this figured out.
I need complex, creative work for my sense of purpose. Building, designing, solving hard problems—that’s not just my job, it’s where I find meaning. I worry about a future where AI handles the interesting work and humans get relegated to oversight of tasks that don’t matter.
But I also recognize that at a macro scale, AI might produce better outcomes than I ever could. More efficient systems. Fewer errors. Broader access.
These two things are in tension. I want creative control and I want optimal outcomes. I haven’t resolved it. Neither has anyone I’ve talked to who’s thinking seriously about this.
What I Want AI to Be
My vision isn’t AI as a tool. It’s AI as an extension of self—a digital partner that holds my context, surfaces what I don’t know I don’t know, and helps me escape local optimums.
Not just reminders and productivity hacks. Something that understands me well enough to challenge my thinking, address my blind spots, and do it in ways I’m actually receptive to.
We have the technology to build this. The models exist. The infrastructure exists. What’s missing is intentionality—and the collective voice to shape what gets built.
This Is Being Decided Right Now
The architecture of AI—what it optimizes for, who it serves, what it enables—is being shaped in real time. By companies, by engineers, by market forces.
Your input isn’t optional. It’s essential.
If you’re not using AI tools in your work yet, start. Not because you’ll be replaced if you don’t—but because you can’t have an informed opinion on something you don’t understand. And your opinion matters.
The question isn’t whether AI will change how we work and live. It’s what we want that change to look like.
That’s not a question technologists should answer alone.
Gabriel Giangi 
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