Sequencing Matters in AI Leadership: What to Get Right Before the Search

Early adoption can create a real competitive advantage with emerging technologies. That helps explain the urgency around AI, as companies across industries are quickly embracing the technology, sometimes without a clear plan for how it will be used. Some may believe they can experiment while they determine the best use cases. Others may simply want to keep pace with competitors and develop a more defined strategy later. 

That uncertainty can create challenges on the talent side. Given the complexity and scope of AI initiatives, companies need clear leadership and accountability to build and scale AI initiatives across the organization. But the sequence matters, and before a search starts for a new AI leader, companies should work through a few fundamental decisions that will shape both the leadership model and the profile they ultimately need.

1. Start with the business outcome

Before any conversations around AI hiring begin, companies should first establish what their AI investment is intended to accomplish. That could mean improving internal processes, increasing productivity, building AI-enabled products, or enhancing how customers engage with the business. The objective should be specific enough to determine where AI can create measurable value and how success will be evaluated. 

That clarity also has direct implications for leadership. A company focused on enterprise transformation may need a very different executive than one building AI into its products or customer experience. Defining the business outcome first gives companies a clearer foundation for determining what kind of executive the company actually needs.

2. Establish ownership before going to market

Once a company has a clearly defined AI strategy, the next step is determining where ownership should sit. Many organizations may default to technology or data, but depending on the mandate, AI may be better aligned with strategy, product, or another part of the business. As with the strategy itself, the right answer depends on what the company expects AI to accomplish. 

From there, stakeholders can determine how much dedicated leadership the mandate requires. A standalone AI executive may not always be necessary; in some cases, an existing leader may already have the capabilities and authority to take ownership, potentially with additional support. Before going to market, companies should assess whether the need represents a true leadership gap or whether the right talent is already inside the organization.

3. If a hire is needed, match the profile to the mandate

After determining that an external AI executive is needed, companies must decide what type of leader best fits the mandate. There is no universal profile for AI leadership, so decision makers should consider which of three broad archetypes best aligns with the company’s strategy: 

• A technical/data-oriented leader 
• A transformation-focused leader 
• An AI product leader 

A successful hire depends on having a clear understanding of what the executive is expected to accomplish. Even a highly accomplished candidate can be the wrong fit if the mandate is poorly defined or stakeholders are not aligned on the outcomes they expect the leader to deliver.

4. Hire for where the role is going

Companies should account for the still-evolving nature of AI when making executive hiring decisions. As the technology becomes more embedded across the business, AI leaders will likely need capabilities that extend well beyond technical expertise. The evolution of the CISO role offers a useful comparison: as cybersecurity became a more significant enterprise issue, the role grew increasingly business-facing and influential. AI leadership may follow a similar path. 

That means companies should look for executives who can translate technical concepts for boards and other stakeholders, influence across functions, and connect AI initiatives to measurable business outcomes. Technical fluency will remain important, but it may increasingly become table stakes. Strong AI leaders will also need communication skills, business judgment, and the executive presence required to help shape strategy as the role continues to mature. 

The Order of Operations Matters 

With AI becoming such a critical business initiative, the urgency surrounding AI hiring is understandable. But hiring simply to keep pace can be counterproductive. Before launching a search, companies need to define their AI objectives, establish ownership, and determine whether existing talent can lead the effort. Only then should they determine whether an external AI leader is necessary. Making the most of AI requires the right oversight, and identifying that leadership starts well before the search itself.