Enterprise AI Unlocked

The real story of AI in the enterprise isn’t about hype or bubbles. It’s about potential that has yet to be fully unlocked. While commentators argue about whether the “AI boom” is real, the web itself is evolving into an agentic web—a fabric where AI acts as invisible infrastructure for how we work, transact, and make decisions.

Enterprises sit at the center of this transformation. They’ve already invested tens of billions into GenAI, and while most projects haven’t yet produced measurable returns, this is less a sign of failure than a sign of adjustment. The models are strong, the infrastructure is robust, and the demand is real. What’s missing is alignment—between technology and organizational design, between vendors and enterprise realities, between what’s possible and how change is managed.

That gap is what I call the GenAI Divide. And crossing it is the defining enterprise challenge of the next decade.

The encouraging news is that we already see what works. The companies making progress aren’t necessarily the biggest or best-funded; they’re the ones willing to rethink how decisions get made, who holds authority, and how employees can guide adoption. They succeed by embracing experimentation, learning from shadow AI usage, and partnering with vendors as collaborators rather than software suppliers.

This book is structured around that journey.

Part I unpacks the organizational shifts required—how to move past central labs and pilots to real deployment, how to build trust across teams, and how to create conditions where frontline managers can lead adoption.

Part II examines the technical building blocks—conversational flexibility, persistent memory, seamless integration, and continuous evolution—that distinguish tools people actually use from tools that sit idle.

Part III offers a playbook for startups and vendors: how to build trust in the enterprise ecosystem, scale adoption without losing user experience, and become indispensable to operations over time.

The lesson is clear: enterprise AI doesn’t fail because the technology isn’t ready—it stalls because the systems around it aren’t yet designed to capture its value. But design can change. The billions already spent are not wasted—they are the down payment on a transformation that will take shape over decades.

For enterprises, the opportunity is to reorganize in ways that let AI compound value across every function. For startups, it’s to position themselves as the partners who make that possible. For both, the GenAI Divide is not a wall—it’s a bridge waiting to be crossed.