AI Strategist
United States · Hybrid
Axial Search builds long-term talent networks for AI, data, and transformation leaders across the United States, and applying for this role indicates your interest in positions like this one as your next move. This particular position isn't tied to a specific client today, but we actively place people with your background — apply and we'll be in touch when a matching role opens with one of our clients. In the meantime, please make use of our free tools to help with your job search, including our live job market dashboard with salary, skills, and hiring-trend data from thousands of AI transformation roles.
Job market data
AI strategy remains one of the clearest growth lanes in senior hiring — over 6,000 US roles tracked in the past year, split between in-house strategy functions at enterprises and embedded consultants at professional-services firms. Mid-senior compensation generally lands in a $140K–$250K band, with directors clearing $280K and executive-level strategy hires regularly breaking $300K. The strongest AI strategists we place combine technical fluency, commercial judgment, and the credibility to operate directly with the C-suite.
Key responsibilities
Partner with senior business leaders to identify, prioritize, and shape high-impact AI opportunities
Translate organizational strategy into concrete AI use cases, roadmaps, and investment plans
Lead AI maturity assessments, value-case development, and executive workshops
Work across functions — data, product, engineering, finance — to stress-test ideas before major commitment
Shape the long-term AI operating model, including governance, talent, and delivery structure
Bring external benchmarks, patterns, and honest perspective to internal decisions
Challenge bad ideas early — and build consensus around the right ones
Operate as a trusted advisor to the CEO, CIO, and business-line leadership
Candidate requirements
6+ years in strategy, management consulting, or in-house AI program leadership
Demonstrated ability to connect AI capability to business outcomes, not just pilots
Fluency in modern AI concepts — generative AI, agents, MLOps — without needing to be an engineer
Strong financial modeling, use-case prioritization, and executive storytelling skills
Track record of influencing C-level stakeholders on transformation decisions
MBA or equivalent experience preferred but not required
