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What the market looks like
We've tracked 4 executive-level AI strategy postings across Canada in the last six months, with strongest concentration in Ontario, Quebec, and British Columbia. Technology, financial services, and professional services firms are leading this hire; compensation for fractional chief AI officer engagements typically ranges from $250–$350 per hour, reflecting strategic advisory scope and flexible commitment. The strongest candidates bring proven experience scaling AI initiatives across enterprise organizations, board-level communication skills, and the ability to translate technical possibility into business strategy without needing operational day-to-day involvement.
Job responsibilities
Define and articulate AI strategy aligned with business objectives; assess organizational readiness and identify high-impact use cases across functions
Advise the executive team and board on AI investment priorities, risk management, and competitive positioning in a rapidly evolving landscape
Build and mentor internal AI leadership; establish governance frameworks, accountability structures, and decision-making processes for AI initiatives
Partner with technology and business leaders to evaluate AI tools, vendor relationships, and build/buy/partner decisions
Own communication of AI vision internally and externally; translate strategy into clear outcomes and measurable milestones
Guide organizational change management as AI reshapes roles, workflows, and skill requirements across the company
Monitor AI adoption, measure impact against strategic goals, and iterate strategy based on outcomes and market shifts
Candidate requirements
10+ years building and scaling technology or AI initiatives in enterprise settings; prior c-suite, board advisor, or chief technologist experience required
Demonstrated ability to translate AI/ML capabilities into business strategy and communicate effectively with non-technical executives and boards
Track record defining organizational strategy, building teams, and establishing governance in high-complexity environments
Deep familiarity with current AI/ML landscape (LLMs, generative AI, machine learning), vendor ecosystem, and practical application patterns across industries
Comfort with ambiguity and rapid change; ability to advise on emerging technology without requiring hands-on implementation