The G.A.M.E.™ Framework
Four pillars that turn AI risk into a structured, auditable, board-ready system. Built for enterprise teams that need to move fast without moving recklessly.
Guardrails
Policies, boundaries, and safety mechanisms that keep AI operating within acceptable limits across the organization.
Authority
Clear ownership, decision rights, and accountability structures for every AI system deployed.
Monitoring
Continuous oversight, audit trails, performance tracking, and drift detection for AI systems in production.
Enablement
Training, tooling, and culture that empower teams to adopt AI responsibly and effectively.
Written for the people
accountable for AI outcomes.
Inside the book:
- How to build AI governance from scratch without slowing innovation
- The board's role in AI oversight and what questions to ask
- Sector-specific guidance: Healthcare/HIPAA, Financial Services (SR 11-7), Employment (Title VII, ADA, NYC Local Law 144)
- How to create accountability structures that scale with AI adoption
- Monitoring frameworks that catch drift, bias, and risk before they become crises
- The difference between AI policy and AI governance, and why most companies have one without the other
- How PE operating partners should evaluate AI risk in portfolio companies
Billy Sticker
Entrepreneur, AI strategist, and founder of HireZim AI and ChiroCandy. Billy has spent over 15 years helping business owners solve their most expensive problems at the intersection of strategy, technology, and execution. Author of The Blessed Entrepreneur.
Lenon Magwenjere
Co-founder of HireZim AI and co-architect of the G.A.M.E.™ Framework. Lenon brings deep technical expertise in AI systems design, governance architecture, and enterprise risk management.