Velocity Partners
Get your AI investments out of the demo and onto the P&L.
Most AI initiatives stall between a promising pilot and real revenue. The model usually isn't the problem. Nobody owns the business result, success was never defined before the build, and there's no plan for running the thing after launch. I fix those three gaps.
Signs you need this
- You have several AI pilots and none in production.
- No business leader is accountable for what AI is supposed to earn or save.
- You can't say whether a launched AI feature is working.
- Teams have AI tools but work the same way they did before.
What I do
- Rank AI use cases by value and feasibility, and cut the ones that won't pay back.
- Assign a business owner and a P&L target to each use case that survives.
- Agree on the experiment design and success metrics before anything is built.
- Plan operations after launch: monitoring, retraining, support and adoption.
- Line up the organization around the new way of working.
What you get
- A ranked AI use-case portfolio with a business case for each
- An experiment charter for the top use cases
- A launch and operating plan, with owners
Proof
- Launched a patent-pending AI natural-language platform at FordDirect, built on the company's customer data platform.
- Led teams that operationalized 800+ machine learning models at Polk (IHS Markit).
- I build with current AI tools myself, including a working web-app prototype built with AI coding tools.
Have AI pilots that aren't paying off? Book a 20-minute call.
Why pilots stall before production: read From the Range to the Course →