The board members of a S&P 500 company, in the midst of a new director search, knew they had to bring on some AI expertise. The only problem: What kind of expertise? Did they want a P&L leader who had scaled AI products successfully? Or someone with experience leading a workforce through a complex technology transformation?
As the corporate world continues to bet heavily on artificial intelligence, boards are adding AI expertise at unprecedented levels. Indeed, 38 percent of directors say deploying AI across the business is a top priority for this year, and 42 percent say technology adaptation and integration will be a focus of capital allocation, according to Corporate Board Member’s 2026 What Directors Think report.
But with 40 percent of boards not using AI in the boardroom, there’s often a lack of understanding as to what AI aptitude a board truly needs. Like when cybersecurity became a governance and audit issue, and companies scrambled to put anyone with technology credentials on the board, many directors today can’t articulate what type of AI expertise they really need.
To help, Korn Ferry developed four AI director archetypes to clarify the skills and capabilities boards want depending on their AI-enabled journey. By using these archetypes, directors can better assess candidates and their overall AI strategy.
1. The AI Builder
At their core, AI Builders deliver technical AI product execution. They’ve had experience building and delivering AI-native products with enterprise-grade reliability. They translate advanced AI models into customer-facing capabilities, provide insight into customer trust and help boards understand what AI can and can’t do. In addition, they can evaluate whether the product/service roadmap matches long-term strategic priorities and delivers real customer value.
A company may seek an AI Builder to go deep on product and engineering questions around systems or strategy that most directors from a finance or legal background may have difficulty navigating.
2. The AI Scaler
Often focused on scaling commercial and customer-facing functions, AI Scalers turn AI into market advantages via M&A or ecosystem partnerships. They’re critical in boardrooms because they often reframe discussions from “Can we build this?” to “Can we sell this at scale?” They move the focus past incremental automation to longer-term competitive differentiation.
AI Scalers understand that AI-native products often fail not in the pilot phase, but in the market—because pricing models are wrong or because sales teams can’t explain their value. The best Scalers can navigate those gaps to ensure a company captures market share before the window closes.
3. The AI Impact Driver
This is the director who’s overseen internal complex digital transformations. They’ve implemented system-wide solutions that deliver operational efficiency or significant cost savings. They also have expertise in cybersecurity or risk and understand how AI alters workflows and operational performance. AI Impact Drivers help boards level up their operational resilience by providing deep insight on enterprise-scale AI deployment.
These directors have experience ensuring legacy systems, regulatory constraints or risk-averse cultures don’t slow down adoption. They often are domain experts who sit at the intersection of what a company most needs to understand to impact its bottom line.
4. The AI Champion
AI Champions have taken AI from an idea to a market-facing, enterprise-level strategic transformation. By shifting operating models or overseeing acquisitions, they’ve created new revenue streams, expanded customer value or enabled new business models via AI. They often are the early adopters who’ve turned ambition into reality—and, crucially, executed the AI strategy so that boards understand the value. They also serve as the point person to take on operational accountability for AI-driven outcomes.
AI Champions are valuable because they can hold management accountable in ways other directors can’t by recognizing when a strategy is credible and when it’s a pipe dream. They can tell when a company is genuinely transforming and when it’s dressing up incremental automation as a strategy.
Next Steps
With an understanding of these four archetypes, boards can start to decipher what expertise they need. A few questions can help guide them:
- How are AI-native products and services going to change the business model?
- How will the firm govern and oversee AI risk?
- What are the talent implications for the organization?
These aren’t small decisions. But as AI reshapes roles, workflows and entire operating models, boards that lack the right expertise won’t just struggle to evaluate their AI strategy—they’ll struggle to evaluate their leadership team’s ability to execute it. Getting the archetype right isn’t just a board composition; it’s an early signal of whether the organization itself is ready for whatever comes next.
