In the last article, we saw how short-term thinking hollowed out workforce development and brought in AI systems that leaders don’t fully understand or control. But even leaders who want to do the right thing face another problem. The system itself won’t let them.
Stephen Parry, founder of the Sense and Adapt Academy, calls this the AI adaptation gap. Companies want to use AI, but their systems can’t handle it. Airlines, banks, and logistics firms run on technology built decades ago. Parry compares it to installing a smart home in a house with 1950s wiring. It doesn’t matter how good the technology is if the foundation can’t support it.
This is not a small problem. It’s a crisis of capability. When one airline system fails, planes stop flying. Passengers get stuck. Cargo is delayed. Hotels get blocked. Security problems spread across five continents. The mess involves 20 technologies and thousands of people. No one person understands it all. Finding the root cause is almost impossible.
The human side is just as broken. Companies cut jobs while looking for AI talent. They aren’t training their own people. Instead, they hire big firms that already have the skills. This concentrates power. A few large companies control the work and take the profits. Smaller businesses lose influence. Economies become weaker.
Parry warns this goes beyond business. When AI connects transport, healthcare, energy, and finance, one failure can crash everything else. And when a crisis hits, AI won’t save you. People will. But only if those people know the systems, can work together, and understand what’s happening. Decades of short-term thinking cut away that capability.
Then there’s the environmental cost. AI needs massive data centers. Those centers use huge amounts of energy and water. Some U.S. data centers have already drained local water supplies dry. AI runs on power, not magic. Communities pay the price.
Here’s the trap. Leaders get systems built for short-term profits. Those systems can’t handle AI responsibly. Fixing them takes time and money that boards won’t approve. Meanwhile, competitors move fast. Fear pushes leaders to use AI anyway, even when the systems aren’t ready. They outsource what they can’t build and cut jobs to pay for it. The cycle keeps repeating.
Even leaders who see the problem clearly find themselves stuck. Legacy systems box them in. Impatient investors pressure them. A workforce they never trained can’t help them adapt. The short-term thinking of the past now traps everyone in the present.
The real question isn’t whether leaders understand the problem. Many do. The question is whether they have the courage to build something different, even when the system fights them every step of the way.
Next time, we will explore what that different kind of leadership looks like and how it can break the cycle.
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