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Ready to harness the power of AI? These strategic pillars will help you ask better questions and make smarter decisions.
AI is reshaping business models and decision making, exposing gaps in traditional governance. For directors, the challenge is overseeing how AI interacts with people, systems, strategy and decision making, and determining how AI can support the work of the board.
This framework offers an AI governance structure organised around five domains (oversight, boardroom wisdom, strategy, ESG, resilience and risk) that trace AI’s governance footprint from internal operations to systemic dependencies. Anchored in established governance principles, it highlights where traditional tools are under pressure and where issues may be overlooked. It offers boards a coherent way to navigate that shift — connecting the five domains in a unified governance approach. Each organisation will weight these domains differently, but examining them together supports better oversight.
#1 Oversight: Building awareness & assurance
Effective oversight begins with a clear understanding of where AI operates, how it shapes decisions and how outcomes can be explained and assured.
But this can be hard to achieve. When employees use AI tools without approval or disclosure — known as “shadow” AI — it creates data and compliance risks, and may signal that staff feel unsafe disclosing AI use. Directors could end up governing what they cannot see.
The challenge deepens with agentic AI (systems that act autonomously, taking sequential actions without human intervention). Their dynamic behaviour requires directors to understand how agents are constrained and managed.
Beyond awareness, boards need assurance across the AI lifecycle — training data quality, permissible use and escalation pathways, for example. These activities should sit within the three lines of defence (frontline controls, risk and compliance, internal audit) with assurance functions resourced and competent to cover AI.
Oversight doesn’t stop at the organisation’s boundaries. Errors can enter through external counsel, auditors and other third parties — as the recent incident involving Deloitte submitting a government report filled with AI-generated fake references and fabricated court quotes demonstrated. Third-party assurance now requires AI-specific scrutiny.
Yet underpinning all of this is director education. Boards cannot govern what they do not understand. Directors need not become technologists, but hands-on familiarity with AI tools makes for better questioning and challenge.
#2 Boardroom wisdom: Generating sharper director thinking
Recent AICD resources show how AI can act as an intelligence partner, augmenting judgement, not replacing it.
Early endeavours demonstrate the potential. A pilot at a University of Sydney Senate meeting used a closed model (a private AI model that operates independently within secure boundaries) in a dedicated AI session to generate post-discussion summaries, including a “Six Thinking Hats” analysis. These outputs prompted directors to ask, “What alternatives did we not consider?”
A second pilot in a mock board meeting explored how AI might support bias detection, director evaluation and decision audit — helping directors to scrutinise their own thinking.
These trials illustrate how AI can illuminate overlooked perspectives and highlight cognitive narrowing — enhancing judgement in an increasingly complex environment.
Challenges of boardroom use include uneven familiarity with AI tools among directors, over-reliance on outputs and a lack of confidentiality and transparency regarding AI use.
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#3 Strategy: Shaping long-term value
This domain moves beyond AI as an input. AI becomes a thinking partner — expanding directors’ strategic imaginations, testing alternate futures and challenging assumptions.
AI-assisted scenario planning allows boards to explore multiple futures across technological, environmental, regulatory and geopolitical horizons, synthesising information, surfacing flow-on effects and generating counterfactuals. In its board strategy day, Women for Election used a closed model for a red-team/blue-team exercise that tested assumptions and challenged director perspectives.
The deeper strategic question is how AI reshapes what is possible. Are boards asking crucial questions to shift thinking toward business model reinvention and value creation? “If this organisation were designed today as AI-enabled, what would we build?”
#4 ESG: Reframing culture
Organisational AI use carries workforce and environmental consequences. It demands a rethink of people and culture oversight — work design, supervision and reward. Workforce dislocation, skills polarisation and unequal access to training are already evident — and AI-natives entering the workforce will expect seamless collaboration with AI. How many organisations are ready for this fundamental shift?
As agentic systems scale, managers will oversee mixed teams of humans and agents. Boards will need to ensure managers can lead these teams — navigating performance evaluation when agents contribute to outcomes, accountability when they err and psychosocial risks such as displacement anxiety and surveillance concerns.
The environmental impacts are equally profound. Directors must understand how AI use aligns with climate commitments, emissions reporting and nature-related regulation, and whether use is consistent with stated sustainability positions.
#5 Resilience: Managing dependency & risk
Traditional risk frameworks don’t anticipate the dependencies AI creates — concentrated compute supply, geopolitical vulnerabilities and cross-jurisdictional infrastructure. Resilience requires rethinking national capability, external dependencies and business continuity.
A critical starting point is understanding where inference — AI models processing inputs to generate outputs — is housed. The jurisdictions hosting AI models shape exposure to legal regimes, data-governance laws and continuity of access. Vendor concentration heightens these risks. When a small number of global providers control frontier models, chip fabrication and cloud access, organisations become vulnerable to changes, outages or restrictive commercial terms. Infrastructure dependencies — subsea cables, specialised chips and cloud region availability — present multiple chokepoints.
The governance question is clear. If access to key AI systems were withdrawn, how long could the business continue and what effects would this have on people, revenue and systems?
This article first appeared as 'Ready to harness the power of AI?' in the February/March 2026 Issue of Company Director Magazine.
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