S5 Episode 27 How to Tell Your AI Rollout Is in Trouble

In this episode of The LowCode Podcast, we break down why so many mid-market companies are spending heavily on AI without seeing measurable returns. The issue is not that AI does not work; it is that many companies are buying tools before defining what those tools are supposed to replace, improve, or eliminate. With billions wasted annually on disconnected AI spend, the real question is no longer “Which AI platform should we buy?” It is “What business outcome are we trying to create?”

We walk through five warning signs that your AI adoption strategy may be burning budget instead of creating leverage. From tool lists disguised as strategy to custom AI builds launched before teams are properly trained, these patterns show up when companies chase software instead of operational impact. We also look at why AI budget should not live only in IT, and why operations leaders need a bigger role in deciding where automation can actually remove friction.

Finally, we unpack what better AI adoption looks like: mapping workflows first, tying every tool to a clear outcome, training employees role by role, and building a roadmap that leadership can explain in plain English. Successful AI integration is not about collecting licenses or chasing the latest agent demo. It is about sequencing the work correctly, focusing on measurable outcomes, and making sure every AI investment has a job to do.