Fractional Head of AI

Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we'll add you to our candidate network and may reach out when relevant roles come up.

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What the market looks like

We've tracked 1,500+ senior-level AI strategy postings in the US over the last six months, with particular concentration in California, New York, and Texas across Professional Services, Technology, Financial Services, and Life Sciences. Organizations are moving past proof-of-concept and building permanent AI strategy functions — fractional heads of AI remain popular because they allow companies to tap experienced leadership without committing to a full-time hire. The strongest candidates bring 10+ years of business or technical leadership, deep fluency in how AI affects organizational capability and competitive positioning, and a track record of translating strategy into executable roadmaps.

Job responsibilities

• Develop and own the organization's AI strategy, including technology selection, capability-building priorities, and integration with business objectives

• Partner with C-suite and business leaders to identify high-impact AI use cases and define success metrics

• Build or scale the internal AI team, recruit specialized talent, and establish governance structures and best practices

• Lead AI transformation initiatives across functions—product, operations, customer experience—and manage dependencies across teams

• Stay current with AI landscape shifts, evaluate emerging tools and models, and advise on technical architecture and vendor relationships

• Drive ethical AI and risk management conversations; establish policies on data use, model transparency, and regulatory compliance

• Report to the CEO or board on AI progress, ROI, and strategic implications for competitive positioning

Candidate requirements

• 10+ years of leadership experience building or scaling AI, data science, or technology strategy functions within large or fast-growing organizations

• Deep understanding of machine learning, generative AI, and data infrastructure—enough to credibly partner with technical teams and make architectural trade-offs

• Proven ability to translate AI strategy into measurable business outcomes and communicate value to non-technical stakeholders

• Experience building and recruiting high-performing teams, setting organizational norms, and establishing governance in emerging function areas

• Comfort operating in ambiguity and moving at pace in a fractional capacity; strong executive presence and stakeholder management