The company says it needs AI talent — but may not yet know which AI role it needs

A request for 'AI talent' can refer to a Chief AI Officer, Head of AI, product leader, applied engineer, data leader, MLOps leader or Forward Deployed Engineer.

Solomon Page launched a retained executive search practice dedicated to AI leadership in September 2026 and described many clients as hiring one first AI leader rather than building a twenty-person team all at once.

That matters because the role may have no predecessor, proven mandate or settled job specification inside the company.

Solomon Page puts role definition before sourcing

Managing Director Ryan Kellner says the hard part of an AI search is rarely just sourcing qualified candidates. It is defining what the organization needs the role to accomplish before the search begins.

The firm's practice covers Chief AI Officers, Heads and Directors of AI, Heads of Data Science, Applied LLM and Agentic AI engineers, Forward Deployed Engineers, RAG and retrieval-quality roles, AI Solution Architects, MLOps, AI product, research and security roles.

The list illustrates how quickly one broad label — AI talent — splits into different business problems and capability markets.

‘Find us a Chief AI Officer’ may not yet be a search specification

If the bottleneck is research, the company may need research or ML leadership. If prototypes do not reach production, the need may be applied AI, platform or transformation leadership. If deployment fails at customer sites, FDE or solution-architecture capability may matter more.

The same title can therefore point to very different people, and different titles can hide similar capability.

The search market becomes clearer only after the company identifies which execution problem the role must solve.

AI hiring priorities are not concentrated in the C-suite

Riviera Partners surveyed 958 senior technology executives across North America and Europe in its 2026 Future of Tech Leadership research.

Fifty-four percent rated individual contributors as a high hiring priority, 48% prioritized AI-relevant technical roles below VP, 35% prioritized manager or senior-manager technical leadership, and 29% prioritized C-suite leadership.

Some organizations need the first AI leader. Others already have leadership and need builders who can implement, integrate, govern and scale the systems.

Only 19% reached Advanced AI execution maturity

Riviera's AI Execution Maturity Model places 19% of organizations at Advanced, 57% at Developing and 25% at Emerging.

This is a separate study context from Solomon Page's client experience, but it adds an important caution: AI execution depends on structure, leadership engagement, governance and builder capability, not simply on filling one executive seat.

The better hiring question may therefore be 'where is our AI execution blocked?' rather than simply 'do we need an AI executive?'

In a new role market, search can begin before the JD

A conventional process often looks like JD → Search → Candidate. For a role the company has never had, however, the JD itself is still a hypothesis.

The sequence can become Business Problem → Role Definition → Capability Definition → Talent Market → Candidate → Search.

Instead of searching titles first, the firm translates the business problem into capability, locates where that capability exists in the market, and only then identifies people.

BANSEOG VIEW | The expensive failure may be searching hard for the wrong role

Riviera's research shows real candidate-market problems: 47% cite insufficient qualified pipeline, 43% slow hiring, 42% inconsistent candidate quality and 40% compensation or equity expectations.

But a search can fail even earlier. A company that needs AI product and transformation leadership can search excellent research candidates and still solve the wrong problem.

In emerging roles, the value of executive search is therefore not only finding more names. It is helping make sure the organization is searching the right market for the right capability.

BANSEOG VIEW

Banseog View — Problem → Role → Capability → Market → Search

First-time AI leadership search can begin with role definition rather than candidate sourcing.

AI talent is already split across multiple capability markets and organizational layers.

The costliest search failure can be executing efficiently against the wrong role definition.

SOURCES

Primary sources and references

Solomon Page's statements reflect its own client experience and newly launched practice and should not be generalized to every company. Riviera Partners is a separate survey of 958 senior technology executives in North America and Europe. The Problem → Role → Capability → Talent Market → Candidate → Search sequence is Banseog's analytical framework, not a quoted methodology from either firm.