Fractional Chief AI Officer

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What the market looks like

We've tracked 100+ executive-level postings in AI strategy across the US in the last six months, with concentrated hiring in California, New York, and Texas. Organizations are building out fractional Chief AI Officer roles to scale strategic guidance without adding permanent headcount—especially in technology, professional services, financial services, and life sciences. The strongest candidates in this space combine deep experience scaling AI across organizations with the flexibility to operate as trusted advisors; they typically charge $250–$400 per hour and split their time across 2–4 client engagements. Boards and C-suites value people who can translate AI capability into business outcomes and help navigate governance, vendor selection, and team buildout without owning day-to-day operations.

Job responsibilities

• Own the AI strategy roadmap: assess current AI maturity, identify high-impact use cases, and prioritize investments across product, operations, and customer experience.

• Partner with executive leadership on AI governance, risk, and compliance frameworks—including data privacy, model validation, and responsible AI principles.

• Build and mentor the internal AI leadership team: advise on hiring, org structure, and skill gaps; serve as coach to the Chief Data Officer, VP of Engineering, or other relevant leaders.

• Evaluate and integrate AI vendors and tools: assess third-party solutions, pilot programs, and make/buy decisions aligned with business strategy and technical constraints.

• Drive board and investor communication: translate AI strategy and progress into narratives for stakeholders; quantify business impact and competitive positioning.

• Establish metrics and accountability: define KPIs for AI initiatives, track adoption and ROI, and course-correct based on market and organizational feedback.

• Advise on talent strategy and external partnerships: recommend external resources (agencies, consultants, research partners) when internal capacity is constrained.

Candidate requirements

• 15+ years building and scaling technology or AI-driven initiatives, with 5+ years in executive or senior advisory roles focused on AI strategy, transformation, or product.

• Proven track record translating AI from research/engineering into measurable business value—revenue growth, cost reduction, customer experience improvement, or operational efficiency.

• Deep fluency in current AI/ML landscapes: foundation models, RAG, prompt engineering, vector databases, and emerging tools; ability to assess technical feasibility and competitive positioning.

• Experience operating as a fractional executive, advisor, or board member—comfortable working part-time across multiple stakeholders with minimal hand-holding.

• Excellent communication across technical and non-technical audiences: can present strategy to boards, mentor engineering teams, and shape buy-in with business leaders.

• Track record in governance, risk, and compliance work—ideally around data privacy, model governance, or responsible AI frameworks in regulated industries.