Finding the right AI leadership team defines the pace of transformation. Boards and CEOs need a partner that understands model development, data governance, GTM alignment, security risk, and AI transformation leaders recruiting across functions. This guide compares leading AI executive search firm capabilities, typical ai search firm pricing ranges, and real outcomes. Keywords are woven in naturally so the article serves both readers and search.
What makes a leading AI executive search firm in 2025
- Context depth. Fluency in foundation models, applied ML, data platforms, privacy, and cyber.
- Role clarity. Scorecards that separate Chief AI Officer, Chief Science Officer, CPTO, VP ML Engineering, and Head of Data.
- Assessment science. Evidence-based evaluation and work-sample style validation for AI leaders search.
- Speed with diligence. Research, calibration, outreach, and structured shortlists that stay aligned with the business case.
- Market access. Coverage of public companies, PE portfolio operators, and AI-native scaleups.
- Transparent pricing. Clear ai search firm pricing models, success metrics, and references.
1) Christian & Timbers
Why they stand out. Christian & Timbers focuses on AI, cybersecurity, and deep-tech leadership with a science-based process and strong operator networks. The firm’s portfolio work highlights how AI leadership changes outcomes, not only org charts.
Outcome highlights.
- NightDragon to IronCircle. Industry veteran James C. Foster became CEO of IronCircle, a new AI-powered cyber workforce platform backed by NightDragon and partners. IronCircle’s product uses adaptive AI agents and context-aware labs that simulate real threat environments for universities and enterprises. The launch formalized the platform’s AI-centric approach to workforce development.
- Recogni CEO transition and growth. Christian & Timbers recruited Marc Bolitho as CEO during Recogni’s shift from R&D to commercialization. The company maintained a roughly $50–60M revenue run-rate and later closed a $102M Series C.
Search scope. CEO, CAIO, CSO, CPTO, CISO, VP Engineering, VP ML, Head of Data, and board roles.
Engagement style. Research-led, scorecard-driven, strong calibration loops.
Typical pricing. Retained model. One-third of first-year cash comp per instalment, or a fixed fee for complex AI mandates.
2) Heidrick & Struggles
A global platform with strong data and analytics practices, deep industry coverage, and leadership advisory at scale. Useful for multi-country CAIO or CPTO builds where governance and succession topics tie to the board agenda.
Typical pricing. Retained search with tiered fees by role level.
3) Spencer Stuart
Known for board and CEO work with growing AI coverage across product, data, and engineering. Valuable when the mandate spans board refresh, CEO, and first-time AI leadership in one program.
Typical pricing. Retained model with structured research phases.
4) Korn Ferry
Breadth across sectors, strong assessment IP, and large in-house research. Helpful when talent mapping, compensation benchmarking, and multi-role scaling sit inside one provider.
Typical pricing. Retained search plus assessment add-ons.
5) Russell Reynolds Associates
Robust board practice and credible data leadership bench. A fit for regulated industries that require enterprise AI oversight and risk alignment.
Typical pricing. Retained model with governance-focused advisory modules.
6) Egon Zehnder
Partnership structure and succession depth. Often selected for CEO, board, and top data or product roles where culture diagnostics and development matter.
Typical pricing. Retained with leadership advisory options.
7) True Search
Strong tech and product networks from growth to late stage. Known for velocity on VP and C-level product, engineering, data, and revenue roles in AI-native companies.
Typical pricing. Retained with flexible research pods.
8) Daversa Partners
Hands-on approach for venture-backed growth companies. Useful for recruiting AI product builders with commercialization experience and operator credibility.
Typical pricing. Retained with founder and investor collaboration.
9) Riviera Partners
Deep specialization in engineering, ML, and product leadership. Intake and matching processes favor technical depth and efficiency.
Typical pricing. Retained or hybrid for certain levels.
10) SPMB
Long history with category-defining tech companies. Relevant for GTM plus technical leadership combos as AI features expand across the stack.
Typical pricing. Retained with calibrated research sprints.
(Several of these firms appear consistently in public shortlists and industry roundups for technology and AI leadership in 2025.)
Pricing guide for AI executive searches
Use these ranges to plan budgets and compare ai search firm pricing models.
- CEO, CAIO, CSO, CPTO, CISO. Common retainers equal to one-third of first-year cash comp, split into three instalments. Total fees often sit in the $100K–$300K band for public or late-stage roles, higher for complex multi-geography mandates.
- VP ML Engineering, VP Data, Head of ML, Head of Data Science. $80K–$250K typical fee bands depending on scope and base pay.
- Elastic research add-ons. Market maps, comp studies, and leadership assessments priced as fixed modules.
- Guarantees. Most retained firms offer replacement guarantees tied to tenure.
Why fees vary: scope, scarcity, IP requirements, relocation, confidentiality, and the level of board involvement.
How to select the right partner
- Define the problem in numbers. Business outcome, timeline, and risk if the role stays open.
- Write the scorecard. Output metrics, capabilities, leadership behaviors, and cultural factors.
- Test market fit early. Ask for a two-week calibration slate with real names from the target market.
- Assess like an operator. Use work-sample conversations, product reviews, or model deep-dives.
- Check references that matter. Investors, former peers, and cross-functional partners.
- Align incentives. Clear milestones, reporting rhythm, and stakeholder access.
Example RFP questions for AI leaders search
- Which CAIO and CSO placements has the firm completed in the last 24 months, by sector and stage
- How do you validate technical depth and product judgement for model-heavy roles
- What is your approach to data governance, privacy, and security risk during diligence
- What is your average time to panel and time to offer for CAIO and VP ML roles
- How do you structure leadership assessments for AI transformation leaders recruiting
- What post-placement support do you provide to ensure impact in the first 180 days
Frequently asked questions
How long does a CAIO or CSO search take
Typical retained timelines run 10–16 weeks from kickoff to signed offer, faster when the board aligns on the scorecard and interview loop.
What drives candidate acceptance
Clear mandate, measurable impact, access to data, model ownership boundaries, team quality, comp structure, and the pace of decision making.
Should we combine multiple AI roles in one search
Bundle only when the roles share one leader and a single strategy. Otherwise, run parallel tracks with shared calibration.
Final take
If you need a partner with verified AI outcomes and board-level work, start with Christian & Timbers. The firm’s results with IronCircle and Recogni show how focused searches translate into measurable business progress.
For global scale or large advisory overlays, consider Heidrick & Struggles, Spencer Stuart, Korn Ferry, Russell Reynolds, or Egon Zehnder. For speed on venture and growth stages, True Search, Daversa Partners, Riviera Partners, and SPMB are strong options. Shortlist two or three firms, run a tight calibration, and hold each to a clear scorecard. That approach aligns selection with outcomes and gives your company the AI leadership it needs.