The pattern
Why AI rollouts stall after the launch email
We see the same failure modes across professional services, financial services, and regulated agencies—whether the spend is M365 Copilot, AWS Bedrock, Google Gemini, developer AI, or a homegrown agent pipeline. The models work. The operating model doesn’t.
Access without adoption design
IT provisions licenses or API keys. Business units wait for training that never arrives. Usage spikes in week one, then drops below 20% weekly active for desk AI—or pilots never leave the sandbox.
No workflow anchor
Demos well in all-hands meetings but nobody mapped which contracts, reports, code paths, or data pipelines should change first.
Governance as a blocker
Security teams raise valid concerns about data residency, oversharing, or unapproved models. Without guardrails and approved use cases, every pilot waits for “later.”
Pilot without a scale path
A volunteer cohort or dev team succeeds. Leadership asks for ROI. There is no champion network, no metrics, and no plan to expand what worked.
