I've Scaled Tech for 25 Years. Don't Miss These 3 AI Steps

"AI isn't just another tool you plug in; it should be seen more as a stress test on how your business actually runs. And in most cases, that test is revealing gaps leaders didn't know they had. If you're thinking about implementing AI or scaling what you've already started, there are three things I recommend that should be in place first that will save you a lot of time and trouble in the long run."

"One of the biggest misconceptions I see is that AI will smooth out inefficiencies. It won't. That's because AI depends on real-time data and consistent networks that perform the same exact way every time. And if your applications lag, your connectivity fluctuates or your teams are already working around performance issues. AI does not fix that; it speeds it up. Instead of getting better decisions, you get faster, bad ones."

"Companies aren't struggling because they picked the wrong AI tools, they're struggling because they're trying to layer AI on top of systems that weren't built to support it. AI feels familiar in a different way. Each wave of innovation promised to move faster, operate smarter and gain an edge. AI is no different, but the expectations are just much higher, where many business leaders expect to see better and faster results right away."

"Layering AI onto fragmented, complex stacks adds friction. Simplification and integration must come first. From what I've seen recently, AI feels familiar in a different way. Companies aren't struggling because they picked the wrong AI tools, they're struggling because they're trying to layer AI on top of systems that weren't built to support it."

AI does not correct weak infrastructure or inefficiencies; it relies on real-time data and consistent network performance. When applications lag or connectivity fluctuates, AI produces faster, worse decisions rather than better ones. Layering AI onto fragmented, complex technology stacks adds friction and slows progress. AI should be treated as a stress test that reveals operational gaps leaders may not recognize. Before implementing or scaling AI, businesses should ensure stable networks, simplify and integrate systems, and address underlying performance and data issues to avoid compounding problems.

Read at Entrepreneur