Leadership & Innovation in the Age of AI
summary
Argues that fixed multiyear plans fail as AI speeds change and claims competitive advantage comes from organizational learning cycles not tech. Recommends a continuous strategy with feedback loops — example: portfolio reviews every eight months or a six‑month keep/kill review tied to measurable impact — and treating governance as a decision‑making playbook. Advises budgeting innovation (e.g., an innovation fund as a percent of revenue) and building AI deployments with explicit feedback loops so models actually improve.
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chapters (14)
- 0:00AI leadership introduction
- 1:10Dan Toma's journey
- 3:07AI project mistakes
- 4:47Five-year plans fail
- 6:19Learning speed advantage
- 7:11Banking innovation feedback
- 8:45AI governance implementation
- 10:14Innovation governance playbook
- 11:41Protected innovation budget
- 12:47Balancing core and future
- 14:03AI mindset shift
- 15:41AI transformation steps
- 16:55AI business goals
- 18:01Closing remarks
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