When we discuss AI-led digital transformation with executives, we often hear a familiar theme: “We’ve invested a lot, but the payoff isn’t what we hoped for.” It’s not just one or two organizations making this claim. Across industries, the pattern is consistent. Companies have invested significant time, money, and energy in transformation initiatives, yet the value unlocked often feels incremental at best.
When it comes to Artificial Intelligence (AI), I can’t think of a time in recent history when so many leaders were aligned in their conviction that a technology would be transformative. I share that conviction. The potential is enormous. At the macro level, AI should unleash massive productivity gains, lower costs, and open up entirely new opportunities for value creation.
However, the paradox we keep running into is that very few organizations are actually realizing these benefits today. They’ve invested in pilots, platforms, and proofs of concept. They’ve staffed up new AI teams. They’ve experimented with automation and agents. And yet, AI has not fundamentally changed their business outcomes – at least not yet.
What’s Really Going On?
I believe the problem isn’t with AI itself. The technology works. The challenge lies in how organizations are trying to apply it. Too many are approaching AI the same way they approached past technologies – layering it onto their existing processes and hoping for better results.
But AI is different. It doesn’t just automate a task or streamline a workflow. To understand it, you have to recognize that AI changes many of the underlying assumptions about how we do business and how a process operates. It redefines the skills required, the role of data, the way customers and stakeholders interact, and the interdependencies across functions. It’s a very extensive set of changes. Simply put, AI forces us to rethink the operating model, and that’s where most organizations are falling short.