AI continues to dominate the headlines driving board conversations and strategic planning. Boards have been encouraged to learn and adapt their thinking and processes to account for AI-driven changes. Now, the time has come to get much more specific about how boards should handle AI’s impact on three familiar core board oversight functions:
Management and compensation
AI adoption requires new standards and metrics against which to evaluate and hold accountable executives who are themselves managing through entirely novel business conditions, introducing novel technologies and employing hybrid human/AI teams. Because the context and substance of operating is changing so quickly, traditional indicators of performance—of management and the organization—almost certainly do not fit.
Illustrative questions: How and when will new performance standards emerge? Does your board have a process for setting new expectations and determining or assessing new performance standards? What will that transition look like? Mistakes and missteps are a certainty. How will the board evaluate these events and those overseeing them?
Key themes: new metrics, redefining success, revising incentives, accumulating expertise, best practices.
Corporate strategy and risk management
The economics of labor, capital and competitive differentiation are shifting, challenging traditional business models and assumptions, market position and organizational capabilities. Strategic roadmaps are obsolete even before adoption. Likewise, risks associated with AI—reputational, operational, competitive and increasingly legal—are complex and interrelated, requiring risk management that is front-footed and goes beyond a compliance mindset. New visions are needed to drive organizations’ new directions and to begin their transformations.
Illustrative questions: What type of transformation must occur? What are the driving forces beyond AI adoption—market disruption, competitive forces, supply chain or customer demand? What are the elements to be successful? How often and where will strategic planning take place? How will it be communicated and tested? What resources and information flows do boards need from the inside and externally? How are boards and management sorting signal from noise? Are strategic planners thinking boldly enough? Are systemic risks being considered properly? How are new risks being classified and mitigated? What is the communication plan for key stakeholders—customers, suppliers, employees and regulators? Are incident response plans updated and ready?
Key themes: innovation, impact, agility, tradeoffs, supply chain, interdependencies, resilience, risk management.
Corporate budgets
Budget and capital decisions must now account for the real costs of AI readiness, adoption and resilience. Traditional (and limited) budget allocations will need to adapt. Plus, the true costs associated with AI adoption are still murky and shifting. As access to energy and compute become scarcer, the models for procuring AI capacity and costs will also shift. Infrastructure and security will demand more investment, as will demands for serious data and AI governance, workforce training and organizational redesign.
Illustrative questions: How and where will the organization invest in AI solutions and readiness? Where will the capital come from? How will capital be allocated between innovation, training, security and resilience? What existing programs should be cut to free up funds? How and when will investments be evaluated and how will success be defined? Are financial incentives aligned with the organization’s values, strategy and risk tolerance?
Key themes: tradeoffs, cost of capital and organizational redesign.
Beyond these traditional duties, many boards also will be asked to advise on novel decisions, where there are genuine tensions regarding timing, resources or capital. Good board engagement requires education and deeper attention to the substantive impact of AI on board functions and board processes.
Board duties haven’t changed. The terrain has. The boards that treat AI as a new condition of doing the work rather than as a novel agenda item are the ones that will provide the kind of leadership their organizations genuinely need.
