Most AI projects fail because teams understand tech OR people – but not both. Expensive automation sits unused when nobody considers how humans actually work. The fix isn’t better tech, it’s designing AI that serves people instead of forcing people to serve AI.
The story
Most AI integration projects fail because they’re led by people who understand tech OR people – but rarely both.
Here’s the uncomfortable truth: your team can build sophisticated AI workflows, but if they don’t match how people actually work, you’ve just created expensive digital paperweights.
We see this constantly. Companies spend six figures on automation projects that gather dust because nobody considered the human side of adoption.
Scott Howard Swain does this differently. He’s spent 30 years in tech, but his real edge is cognitive empathy – designing AI systems people actually want to use. Not because they’re forced to, but because the workflows make sense.
Results? Teams see triple efficiency. Not from fancier algorithms, but from AI that fits the business instead of forcing business to fit the AI.
Most AI consultants sell what’s technically possible. Scott focuses on what’s practically useful. He mentors teams while translating complexity into business results – a player-coach bridging both worlds.
The controversial part? Your AI project doesn’t need more features. It needs someone who understands technology serves people, not the other way around.
If automation keeps stalling at implementation, the problem isn’t your team’s capability. You’re missing the person who makes AI feel less like disruption and more like the obvious next step.
