AI governance for boards

By Ari Magalhaes FGIA GAICD, Founder and Principal - OmniStrategic

AI strategy connects investment to organisational priorities and measurable value. Governance establishes accountability for how AI is used, with controls proportionate to the risk. Each engagement begins with expectations and the organisation's current state.

Board oversight requires visibility of AI use and its implications for data, people and service delivery. Advice addresses privacy and bias, supplier dependence, and errors in automated decisions. Decision rights and escalation requirements are incorporated into existing governance.

Assessment covers current AI use and the data, systems and skills needed to deliver proposed initiatives. The free AI Readiness Assessment offers an initial view. Wharton training and committee oversight of data and emerging technology inform the advisory work.

Pilots validate priority uses before wider investment. Business cases and a funded adoption roadmap guide delivery, with capability building and benefits reporting carried through implementation.

Common questions

Does a board need an AI expert?

Not necessarily. Every director now needs enough AI and digital literacy to oversee how the organisation uses it.

Where should a board start?

With an inventory of where AI is already in use, including tools staff use without approval.

What should a board request before a pilot is expanded?

Request evidence of the pilot's performance and costs, unresolved risks and the controls required for wider use. The decision should also address delivery capacity and how benefits will be monitored.