One company successfully implemented AI by repurposing its existing Stage-Gate new product development process. The key shift was treating internal teams as the "customer." This structured approach avoids chaotic, ad-hoc "guerrilla" adoption efforts that often fail.

Effective AI adoption requires a structured approach. Instead of ad-hoc experimentation, teams should identify, document, and prioritize potential AI use cases based on business value and feasibility. This 'use case workbook' provides a clear roadmap, ensuring that time is spent on high-impact applications.

Avoid vague, company-wide AI mandates. Instead, apply a maturity framework to individual processes (e.g., account research). This approach builds a practical roadmap, moving specific use cases up the maturity ladder as needed and preventing costly over-engineering.

An effective AI strategy pairs a central task force for enablement—handling approvals, compliance, and awareness—with empowerment of frontline staff. The best, most elegant applications of AI will be identified by those doing the day-to-day work.

To truly benefit from transformative AI, leaders are advised against running small, tactical pilots. Instead, they should develop a clear strategy, make a decisive commitment to a platform, and integrate it as a core strategic initiative. This approach avoids incrementalism and achieves significant results much faster.

Effective AI adoption requires a three-part structure. 'Leadership' sets the vision and incentives. The 'Crowd' (all employees) experiments with AI tools in their own workflows. The 'Lab' (a dedicated internal team, not just IT) refines and scales the best ideas that emerge from the crowd.

Bill Glenn suggests a phased AI rollout for teams. Phase 1 focuses on efficiency and automating repeatable tasks to gain productivity. Phase 2 moves to strategic work, using AI for insights and decision-making assistance. This provides a clear, manageable roadmap for adoption.

The Goldman Sachs CEO differentiates between two types of AI adoption. Giving employees AI tools to make them more productive is relatively easy. The much harder, yet more impactful, challenge is fundamentally re-engineering long-standing, complex processes like customer onboarding from the ground up.

To make "AI Ready" tangible, Unum uses a two-pronged approach. "Everyday AI" (e.g., Copilot) is rolled out to the entire company to foster citizen development and reduce fear. "Embedded AI" involves deep, mandatory training for engineers to integrate AI directly into their core workflows and boost productivity.