Developing Semiconductor Leaders for the AI Era

A year ago, a leading global chipmaker set out to enter the high-performance computing market to capture AI-driven growth. It had strong capabilities in leading-node, high-performance processors, but AI compute demand had advanced faster than expected. The company urgently needed leaders across engineering, software, operations, marketing, sales, and HR to support a growing global platform. In response, it expanded its search for proven AI talent externally, only to find that the talent shortage demanded a different approach. 

They are not alone.  

Across the semiconductor value chain, AI-driven demand is pushing companies once only peripherally focused on AI to reposition around AI-led growth. This shift has outpaced traditional planning cycles and transformed leadership hiring. Expertise in previously niche domains is now highly prized, creating a severe imbalance between talent supply and demand. 

Except for the best-funded companies, competing effectively requires more than buying missing capabilities. Instead, leading organizations are combining selective external hiring with accelerated internal development. They are building structured ways to identify leaders who can learn quickly, adapt, and drive change at scale. The critical question is whether companies have the priorities, methodology, and discipline to embed accelerated assessment and development into their AI talent strategy, and to do so quickly.

For the above-mentioned chip maker, the external search quickly exposed a hard truth: Few candidates possessed the breadth of AI capabilities the company desired. Those who did were commanding premium compensation, drawn into bidding wars, or reluctant to join a newer entrant. While external hiring could fill selected gaps, it could not build the leadership bench at the speed required. The company realized it must do better with talent it already had inside. 

What it found was an underused source of advantage. Like many organizations, the company had treated structured development as useful rather than essential. Leadership decisions rested largely on managerial judgment and past performance, without a consistent approach to assessing potential. That model overlooked leaders who lacked a conventional AI track record but had the capacity to move rapidly into emerging domains.  

Our team worked with the company to assess its existing talent through an AI-specific lens, evaluating both current capability and the potential to succeed in unfamiliar territory. A one-month pilot produced a striking result: Several leaders with the right foundations were already in adjacent roles. With targeted exposure and support, they could be accelerated into critical AI mandates. 

The lesson from this client extends well beyond one company. Leading organizations are redefining “ready now.” Instead of screening only for proven AI experience, they are identifying adjacent leaders with strong fundamentals, learning agility, and the ambition to take on unfamiliar challenges. Rigorous assessment reveals who can make the leap; focused exposure, coaching, and decision rights help them make it faster. The payoff is a stronger talent bench, fewer critical vacancies, and less risk of placing the wrong leader in a pivotal role.

In periods of rapid change, experience alone is an unreliable predictor of success. The more important question is how a leader will perform when precedent is limited. Drawing on decades of work across industry and economic transitions, Egon Zehnder assesses leadership potential through its Potential Drivers Profile, which focuses on four indicators of sustained learning and behavioral adaptation: 

• Curiosity: the drive to explore, question, and continuously learn.  
• Insight: the ability to connect disparate signals and anticipate implications before they become obvious.  
• Determination: the resilience to navigate ambiguity, setbacks, and sustained pressure.  
• Engagement: the capacity to energize, align, and mobilize others around a common direction.  

Assessing these dimensions helps organizations distinguish leaders who will merely cope with AI-driven change from those who can adapt quickly and shape it. The findings can then inform focused development plans for high-potential leaders.

AI leadership roles require different capabilities. To clarify these distinctions, we identified three AI leadership archetypes: AI Industry Shapers, AI Builders, and AI Transformers. Combined with our Potential Model, they provide a common foundation and sharper lens for assessment. For our semiconductor client, two archetypes were especially critical: 

• AI Builders, technical leaders who drive AI initiatives from the inside out by developing platforms, models, data foundations, and scalable engineering capabilities. 
• AI Transformers, business-oriented leaders who integrate AI into enterprise strategy and operating models, connect technical and commercial stakeholders, reshape priorities, and embed AI into decision-making. 

Defining the required archetype is the starting point for rigorous assessment. Leaders can then be evaluated against the capabilities most relevant to the mandate, with different weightings for Builders and Transformers. This clarity shows where strengths can have the greatest impact and where focused development is needed. 

Egon Zehnder combines decades of leadership assessment experience with current insight into effective AI leadership. Working with clients, we have adapted our models to evaluate the competencies required across technical and business roles, helping identify and develop leaders equipped for the next wave of change. 

Core capabilities include strategic vision, change leadership, technical curiosity, data-driven decision-making, customer insight, organizational leadership, and cross-functional collaboration. Their relative importance depends on the role, mandate, and whether the leader is a Builder or Transformer. Anchoring assessment in strategy clarifies the required competency mix, the strengths to leverage, and the gaps to address. 

As AI adoption matures, many organizations are gauging whether their broader leadership population is prepared to support AI-driven transformation. In our work with clients, we increasingly see organizations seeking to identify leaders who can accelerate adoption, as well as those who may require additional development to thrive in AI-enabled environments. 

To address this need, we have developed AI-specific assessment approaches that evaluate more than technical expertise. The focus is on how leaders engage with AI, challenge established assumptions, translate technological possibilities into business opportunities, and champion adoption across the enterprise. These capabilities often prove just as important as AI experience itself when organizations are navigating rapid transformation.

Organizations should first identify the roles that most directly influence AI-related revenue, product differentiation, cost, or cycle time. This clarifies where leadership investment will create the greatest value. 

Next, they should assess leaders for potential and indicative AI competencies, and from there create structured development pathways. High-stakes rotations and mission-based assignments of 90 to 180 days expose high-potential leaders to AI customers, product trade-offs, and cross-functional decisions, accelerating growth beyond what formal programs alone could achieve. 

Individual capability is not enough. Leadership acceleration also requires decision rights, governance, and resources aligned with the speed and complexity of AI. Developing leaders without adapting the operating model limits their impact.

Semiconductors sit at the foundation of the AI era, but demand for proven AI leadership far outstrips supply. During this phase of accelerated market transformation, speed is essential. Companies best positioned to capture this growth treat targeted external hiring and accelerated internal development as complementary strategies. Grounded in disciplined implementation of rigorous assessment and focused development, this “build-plus-buy” approach creates the leadership bench needed to move at market speed.