While searching for a new director, board members at an S&P 500 company recognized the need to bring in AI expertise. The only question is: what kind of expertise do you have? Did you want a P&L leader who has successfully scaled AI products, or someone with experience leading employees through complex technology transformations?
As the corporate world continues to bet big on artificial intelligence, boards are adding AI expertise at unprecedented levels. In fact, 38% of directors say deploying AI across the business is a top priority this year, and 42% say technology adaptation and integration will be a focus for capital allocation. corporate director's “2026 Directors' Thoughts'' report.
However, with 40% of boards not using AI in their boardrooms, there is often a lack of understanding of the suitability of AI for what boards really need. Just as when cybersecurity became a governance and audit issue and companies scrambled to fill their boards with technology credentials, many boards today can't articulate the type of AI expertise they really need.
To help with this, Korn Ferry developed four AI director archetypes to clarify the skills and competencies boards need depending on their AI-enabled efforts. Using these archetypes, directors can better evaluate candidates and their overall AI strategy.
1. AI Builder
At its core, AI Builder provides technical AI product execution. They have experience building and delivering AI-native products with enterprise-grade reliability. These transform advanced AI models into customer-facing capabilities, provide insights into customer trust, and help boards understand what AI can and cannot do. Additionally, you can assess whether your product/service roadmap is aligned with long-term strategic priorities and delivers true customer value.
Companies may look to AI builders to dig deep into product and engineering questions about systems and strategy that are difficult for most directors with finance or legal backgrounds to address.
2. AI scaler
AI scalers often focus on expanding commercial and customer-facing capabilities, turning AI into a market advantage through M&A and ecosystem partnerships. This is important in boardrooms because they often reframe the discussion from “Can we build this?” “Can we sell this at scale?” They shift their focus beyond incremental automation to long-term competitive differentiation.
AI scalers understand that AI-native products often fail in the market rather than in the pilot stage. The reason is either the pricing model is wrong or the sales team can't explain the value. A good scaler can navigate these gaps to ensure the company captures market share before the market closes.
3. AI impact driver
This is a director who has overseen a complex digital transformation within the company. They implemented a system-wide solution that resulted in operational efficiencies and significant cost savings. We also have expertise in cybersecurity and risk, and understand how AI can transform workflows and business performance. AI Impact Drivers helps boards level up their operational resiliency by providing deep insights into enterprise-scale AI deployments.
These directors have the experience to ensure that legacy systems, regulatory constraints, or a risk-averse culture don't delay implementation. They are often domain experts who sit at the intersection of what companies most need to understand to impact their bottom line.
4. AI Champion
AI Champions have taken AI from idea to market to enterprise-level strategic transformation. By changing operating models and overseeing acquisitions, we created new revenue streams, expanded customer value, and enabled new business models through AI. They are often early adopters who have turned ambition into reality and executed AI strategies in a way that boards see the value. They also serve as the central figure with operational responsibility for AI-driven results.
AI champions are valuable because they can hold executives accountable in a way that other directors cannot, by recognizing when a strategy is reliable and when it is a pipe dream. They can tell when a company is truly transforming and when it's dressing up incremental automation as a strategy.
next step
By understanding these four archetypes, boards can begin to understand what kind of expertise they need. Some questions will help guide them.
- How will AI-native products and services change business models?
- How will the company manage and oversee AI risks?
- What impact does talent have on an organization?
These are not small decisions. But as AI reshapes roles, workflows, and entire operating models, boards without the right expertise will struggle not only to evaluate their AI strategy, but also their executive team's ability to execute it. Getting archetypes right is about more than just board configuration. It's an early signal of whether the organization itself is ready for whatever happens next.
