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This role supports the advancement of Artificial Intelligence (AI) at BMO InvestorLine by empowering teams to understand, adopt, and leverage AI across workflows, while ensuring that AI investments scale across the enterprise.

This role reports into the Head of AI, Digital Investing, and owns two core mandates:

• AI business enablement– driving adoption, capability-building, and measurable value from internal AI tools, while designing the future state AI operating model

• Scalability of AI investments– partnering across BMO lines of business to extend, co-develop, and economically scale AI investments

In addition to the two core mandates, this role will provide flexible, ad hoc support across AI strategy and delivery based on evolving business priorities.

AI Business Enablement

• Own business enablement strategy and execution for AI across InvestorLine, driving measurable, value accretive adoption of internal AI tools (e.g., Copilot Studio, Claude Cowork, and other no-/low-code tools)

• Lead change management efforts to embed AI into workflows, including communications, activation plans, and champion networks

• Define and execute the AI Learning & Development strategy, including role-based learning paths, workshops, speaker series, and ongoing capability-building programs

• Build and maintain a centralized AI knowledge ecosystem (e.g., use-case libraries, prompt/skill/agent libraries, playbooks, best practices)

• Partner cross-functionally across a highly matrixed business to identify practical, role-relevant AI use cases that improve productivity, decision-making, and quality of work

• Partner with technology, data science, AI, and risk teams to activate value accretive internal use cases with pace

• Establish and track adoption and impact metrics (e.g., workflow integration, efficiency gains), translating insights into clear, actionable direction for leadership

• Reinforce responsible AI usage aligned to enterprise governance, risk, and data privacy requirements

• Design the future state agentic operating model for InvestorLine, including a pragmatic, multi-stage operationalization approach

• Continuously evolve enablement approaches based on feedback, usage patterns, and emerging AI capabilities

AI Scalability & Enterprise Alignment

• Partner across Wealth and BMO business & technology teams to identify shared AI opportunities and overlapping demand, helping inform where InvestorLine directs its AI investments

• Lead across multiple lines of business to shape initiatives with scalability in mind, balancing shared build opportunities with InvestorLine specific needs

• Support collaboration on AI initiatives by bringing clarity to scope, ownership, and delivery approach across partners

• Lead the development of cost-sharing and value attribution approaches for jointly developed capabilities

• Define what elements of a solution are scalable (e.g., platforms, core capabilities, workflows) versus what requires tailored builds

• Establish repeatable approaches for extending AI initiatives beyond InvestorLine, reducing friction in scaling and reuse

• Work within and adapt to the evolving Wealth and BMO AI landscape, aligning with broader practices, governance expectations, and ways of working

• Maintain awareness of external trends and approaches to scalable AI deployment to inform internal decisions

Qualifications

• Minimum of six years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience

• Minimum of two years of management consulting experience, with an emphasis on AI; MBB experience is an asset

• Bachelor’s degree in relevant field; Master’s or PhD is an asset

• Deep understanding of AI technology and delivery, including SDLC, agentic solution architecture, AI harness development, and the scalability of technology elements across use cases

• Expert level understanding of modern applied AI capabilities and their application in business contexts

• Demonstrated experience driving adoption of AI tools, capabilities, and ways of working at scale

• Proven ability to operate cross-functionally and influence senior stakeholders without direct authority

• Experience translating business needs into practical, scalable solutions

• Working knowledge of responsible AI, governance considerations, and data/privacy requirements within a highly regulated industry

• Verbal & written communication skills – Expert

• Collaboration & team skills – Expert

• Analytical and problem solving skills – Expert

• Influence skills – Expert

• Managing ambiguity – Expert

• Data-driven decision making – Expert

Culture & Ways of Working

• Acts with a strong sense of ownership and accountability for outcomes

• Highly collaborative, with the ability to build trust and influence across business, technology, and risk partners

• Comfortable operating in ambiguity and shaping structure where it does not yet exist

• Balances strategic thinking with hands-on execution

• Maintains a client- and employee-first mindset when designing and scaling AI-enabled ways of working

• Continuously learns and adapts as AI capabilities and industry practices evolve