2025 is the year of the AI Agent. Or so it would seem. But I have another belief, it will be, or maybe it should be, the year of the AI - enabled employee.
Let me explain.
The most interesting thing about generative AI isn't what it can do now, but how it's changing the way we think about work.
It's like the early days of the internet when most people saw it as a fancy way to send mail or share photos. They weren't wrong, but they were missing the bigger picture.
I've been watching startups and big companies grapple with AI, and there's a clear pattern emerging.
The ones who succeed aren't the ones with the biggest AI budgets or the most sophisticated models. They're the ones who understand that AI is fundamentally a tool for amplifying human capability.
Think about the first time you used a calculator.
It didn't make you worse at math; it freed you to focus on higher-level mathematical thinking. Generative AI is like that, but for knowledge work.
The best companies aren't using it to replace humans but to eliminate the boring parts of their jobs.
Here's what most people get wrong about AI strategy: they treat it like a magical solution that will automatically transform their business.
But technology doesn't work that way.
The steam engine didn't automatically create the Industrial Revolution, it required new ways of organizing work, new skills, and new business models.
I remember talking to a CEO who spent millions on AI initiatives without much to show for it. When I asked about their approach, it became clear they were trying to AI-ify everything at once.
Another CEO, with a fraction of the budget, achieved remarkable results by focusing on one critical problem: helping their support team respond to customer queries.
The difference? The second founder understood that AI is a multiplier, not a substitute.
The most successful implementations of generative AI share three characteristics:
- They start with real problems, not solutions looking for problems.
- They focus on augmenting human capabilities rather than replacing them.
- They invest as much in training and process changes as they do in technology.
This brings us to an important question: what's the right way to introduce AI into an organization?
The answer is counterintuitive: start small, but think big.
Pick a specific problem where AI can have a measurable impact, solve it well, and use that success to build momentum.
Consider how Google grew.
They didn't start by trying to organize all the world's information. They started with one thing: better search. Everything else came later. The same principle applies to AI strategy.
The companies that will win in the AI era aren't necessarily the ones with the most advanced technology. They're the ones that understand how to integrate AI into their existing workflows in ways that actually make sense.
It's like the difference between knowing how to use a hammer and knowing how to build a house.
One particularly effective approach I've observed is what I call the "AI sandwich" - human judgment on both ends, with AI doing the heavy lifting in the middle.
A content team might have humans deciding what to write about and editing the final product while using AI to generate initial drafts. This preserves human creativity and judgment while dramatically increasing productivity.
The biggest mistake companies make with AI isn't technical - it's cultural.
They fail to prepare their people for the change. The best AI implementations include significant investment in training and change management.
It's not enough to give people access to AI tools; you need to help them understand how these tools change their role.
Looking ahead, the organizations that will thrive aren't the ones treating AI as a cost-cutting measure or a way to automate existing processes. They're the ones using AI to imagine entirely new possibilities.
Just as the internet enabled business models that would have been impossible before, generative AI will enable new ways of working that we're just beginning to understand.
The strategic use of AI isn't only about replacing human intelligence and agents - it's about augmenting it.
The goal isn't to have AI do our thinking for us, but to free us to think about more interesting problems. That's where the real opportunity lies.
The companies that understand this will do more than survive the AI revolution - they'll lead it. And the ones that don't?
Well, they'll probably still be around, but they'll be like companies that missed the internet revolution: still doing business, but increasingly irrelevant.
The key is to start now, start small, and focus on problems that actually matter.
The rest will follow naturally. That's how important technologies always work: not through grand initiatives, but through practical solutions to real problems.