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What the market looks like
We've tracked 6 executive-level AI strategy postings in Canada over the last six months, concentrated in Toronto, Montreal, and Vancouver across technology, financial services, and professional services sectors. Organizations are moving beyond pilot programs and building permanent AI leadership functions—they need executives who can translate business strategy into AI capability and governance. Compensation for this cohort ranges from $180,000 to $350,000 annually. The strongest candidates combine deep AI/ML literacy with boardroom-ready communication skills, a track record of building scaled technical teams, and experience navigating organizational change at the executive level.
Job responsibilities
Develop and articulate the organization's AI strategy, including use-case prioritization, build-versus-buy decisions, and alignment with business objectives
Own enterprise AI governance, risk management, and compliance frameworks—including data privacy, model governance, and responsible AI principles
Build and scale the internal AI/ML team or partner ecosystem, including hiring leadership, defining talent development, and fostering technical culture
Lead cross-functional collaboration with business units, technology, and legal teams to identify and operationalize high-impact AI initiatives
Communicate AI roadmap, progress, and business impact to the board, C-suite, and stakeholders; translate technical concepts for non-technical audiences
Stay current with AI capabilities, emerging tools, and market trends; benchmark competitive landscape and advise on build-or-partner strategies
Define success metrics and measurement frameworks for AI investments; track ROI and organizational capability maturity
Candidate requirements
10+ years of experience leading AI, machine learning, data science, or related technical functions at the executive or senior director level
Demonstrated success building and scaling technical teams of 20+ people, including hiring, retention, and leadership development
Deep fluency in AI/ML fundamentals, current tools and frameworks, and real-world constraints of productionizing AI systems—not just theoretical knowledge
Proven ability to translate between technical depth and business strategy; comfort presenting to boards and C-level executives
Track record navigating organizational change, embedding new capabilities, and driving adoption of emerging technologies
Experience with AI governance, responsible AI practices, data privacy regulation, or related risk/compliance frameworks