The play most companies run with AI: hand it to IT

Most companies I talk to are running the same play with AI - hand it to IT, set adoption KPIs, measure how many people opened Copilot this week. The results are predictably shallow: meeting transcriptions, advanced search, usage dashboards that measure nothing useful. Mollick calls this "de-weirding" and the framing is sharp.

Where I'd adjust is on IT as the place AI goes to die. The pattern is more specific: IT defaults to restricting what it can't fully control, functions default to waiting for someone else to figure it out, and together they produce a comfortable limbo where AI stays safely incremental. Infrastructure gets locked down before anyone knows what to build on it. Experimentation requests sit in backlogs. Nobody owns the product layer.

The Leadership-Crowd-Lab model in the article is the exact ambition I'm working to bring to life - direction from senior leadership, experimentation distributed across functions, a dedicated team connecting the two, with IT at the table as an infrastructure partner.

The structural problem is that neither side has been forced to operate this way before. AI is forcing the shift whether they're ready or not.