Executives must build AI governance structures now rather than waiting for perfect frameworks, or risk falling behind competitors

AI deployment is already happening inside organizations without governance oversight — employees are running customer data through consumer tools, engineers are deploying unreviewed models, and procurement is signing contracts with embedded AI — creating real-time risk regardless of formal authorization.

Companies need to establish a senior, cross-functional AI Governance Committee with authority and accountability (including the Chief AI Officer, CISO, Chief Compliance Officer, Chief Privacy Officer, and Chief Audit Executive) that meets regularly and reports to the board, rather than delegating to lower-level taskforces.

Organizations must build separate oversight frameworks for two distinct branches of AI activity — AI embedded in customer-facing product features and AI for back-office operations — because they carry different reputational, legal, and competitive stakes and require different risk tolerances.

Early committee outcomes should include clarity on scope, a full inventory of current AI systems running in the organization, an assessment of what existing policies cover, and a regular reporting cadence to leadership and the board.