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Bank of Montreal

Runs Canadian and US banks for people and firms

AI Enablement Manager

Product ManagementConfirmed live in the last 24 hours
Full-timeToronto, ON, CanadaIn-person

About the Job

Requirements

  • Typically, five or more years of relevant experience and a post-secondary degree in a related field of study, or an equivalent combination of education and experience.
  • Experience in product discovery or business analysis, with additional experience in one or more of the following areas: innovation, strategic initiatives, capability enablement, consulting, or technology delivery.
  • Experience partnering with business stakeholders to identify needs, qualify opportunities, define expected value, and develop business or capability requirements.
  • Knowledge of product discovery, portfolio management, and solution delivery practices and lifecycles.
  • Working knowledge of artificial intelligence concepts and enterprise AI capabilities, with the ability to assess their practical application to business needs.
  • Experience coordinating complex initiatives across business, technology, risk, governance, and other enabling functions, including reconciling competing requirements and advancing decisions without direct authority.
  • Experience developing or delivering demonstrations, learning materials, workshops, or capability education that support practical understanding and adoption.
  • Strong analytical and problem-solving skills.
  • Strong verbal and written communication skills.
  • Ability to translate business needs into clearly defined opportunities, requirements, and recommendations.
  • Ability to communicate AI and technology concepts in clear, accessible, and practical language.
  • Strong facilitation, presentation, and stakeholder management skills, demonstrated through the ability to surface differing perspectives, constructively challenge assumptions, and build alignment on decisions and next steps.
  • Ability to build effective relationships and work across business and technical teams.
  • Ability to independently manage a portfolio of opportunities with competing priorities, dependencies, and varying levels of readiness, making trade-offs and adjusting focus as business needs evolve.
  • Sound judgment to assess readiness, recommend next steps, and identify when issues require escalation.
  • Ability to work independently and exercise sound judgment in an evolving environment with changing priorities and ambiguity.
  • Strong curiosity and learning agility related to emerging AI capabilities and their practical business application.

Responsibilities

  • Partner with business teams to identify and frame business problems and needs that may be addressed through AI.
  • Facilitate discovery discussions to clarify the business problem, target users, intended outcomes, potential value, and factors affecting opportunity readiness.
  • Advise business partners on the suitability of approved enterprise capabilities, third-party capabilities, or new AI use cases for identified needs.
  • Establish and manage the MCSI AI opportunity funnel, progressing business-owned opportunities through intake, discovery, qualification, and definition.
  • Partner with business teams to develop opportunity assessments defining the business problem, target users, expected value, requirements, dependencies, and success measures.
  • Review supporting information to identify gaps and areas requiring further definition or analysis.
  • Assess opportunity readiness and recommend whether opportunities should advance, require further development, be redirected, or be closed.
  • Maintain visibility into opportunity status, dependencies, decisions, and required actions.
  • Prepare qualified opportunities for portfolio and decision forums and recommend readiness, expected value, requirements, dependencies, and next steps.
  • Guide qualified AI opportunities through lifecycle stages, ensuring business ownership, required evidence, and readiness conditions are established before formal use case approval, funding, and resourcing decisions.
  • Translate qualified business needs into decision-ready opportunity statements, user needs, and capability requirements supporting formal lifecycle reviews.
  • Coordinate activities across business, technology, governance, risk, and other enabling partners, including required documentation, reviews, and readiness activities, to address requirements and dependencies and support opportunity progression and formal use case decisions.
  • Track actions, milestones, dependencies, decisions, and readiness conditions for assigned opportunities and use cases.
  • Identify issues affecting opportunity progression and coordinate with stakeholders to resolve them or determine appropriate next steps.
  • Support business owners with planning and readiness for approved pilots, capability releases, and broader adoption.
  • Maintain continuity across opportunity development, formal use case approval, delivery, deployment, and transition to ongoing business ownership, coordinating handoffs while remaining engaged to clarify requirements, address dependencies, and support lifecycle decisions.
  • Steward use case readiness, requirements, dependencies, and stakeholder alignment throughout the lifecycle without owning technical design, development execution, sprint management, delivery-team backlogs, or ultimate accountability for business outcome realization.
  • Support business owners after release by coordinating feedback gathering and monitoring early adoption, identifying improvement opportunities, and sharing findings with capability and delivery partners.
  • Assess the materiality of risks, unresolved dependencies, and decisions, and escalate matters requiring additional authority or specialized expertise.
  • Maintain current knowledge of approved enterprise and third-party AI capabilities relevant to MCSI business needs.
  • Work with capability owners and subject-matter experts to understand available functionality, intended uses, limitations, and implementation considerations.
  • Partner with business teams to identify processes and workflows that may benefit from approved AI capabilities.
  • Support assessment and introduction of third-party AI capabilities by coordinating business needs, requirements, and input from relevant partners.
  • Advise business teams on differences, intended uses, and limitations of available capabilities to inform fit-for-purpose decisions.
  • Develop practical examples and demonstrations showing how approved AI capabilities can be applied to MCSI business needs.
  • Consolidate business feedback and communicate recurring needs, capability gaps, and improvement opportunities to relevant capability owners and partners.
  • Monitor emerging AI capabilities and trends and assess their potential relevance to MCSI priorities and business needs.
  • Support the MCSI AI enablement, adoption, and literacy program through practical education, guidance, and targeted adoption activities.
  • Develop and deliver practical demonstrations, capability education, and targeted learning sessions.
  • Create clear guidance, examples, and reusable materials that help employees understand and apply approved AI capabilities.
  • Contribute content and expertise to AI learning activities, champion forums, communications, and other enablement channels.
  • Work with business teams to identify capability knowledge gaps and appropriate enablement approaches.
  • Provide practical guidance on the responsible use of approved AI capabilities.
  • Gather feedback from employees and stakeholders to inform improvements to learning materials, demonstrations, and enablement activities.
  • Share practical examples, lessons learned, and reusable approaches that can be applied across teams.
  • Build effective relationships with business teams and internal and external stakeholders to surface opportunities, resolve dependencies, and support timely decisions.
  • Collaborate with technology, governance, risk, change, learning, and capability partners to advance AI opportunities.
  • Serve as a knowledgeable point of contact for assigned opportunities, use cases, and capabilities.
  • Facilitate discussions involving different business perspectives, technical requirements, and levels of AI understanding.
  • Communicate AI, technology, and process concepts in clear and practical business language.
  • Provide clear, timely updates on opportunity status, readiness, dependencies, risks, decisions, and required actions.
  • Connect stakeholders with appropriate subject-matter experts and decision makers when specialized input is required.
  • Facilitate collaboration between business owners and enabling partners throughout the AI opportunity lifecycle.
  • Maintain stakeholder alignment by confirming requirements, documenting decisions, and clarifying ownership of next steps.
  • Analyze information from the opportunity funnel, active use cases, and enablement activities to identify trends, barriers, and improvement opportunities.
  • Define reporting requirements and measures to monitor opportunity funnel health, progression, readiness, aging, and key dependencies.
  • Recommend and support improvements to the MCSI AI opportunity lifecycle, operating model, tools, templates, guidance, and ways of working.
  • Capture and share lessons learned from AI use cases and capability introductions to inform future opportunities and lifecycle improvements.
  • Research relevant AI developments, industry practices, and emerging capabilities to inform recommendations.
  • Break down complex or non-routine business problems, evaluate incomplete or competing information, and recommend practical next steps when established approaches may not apply.

Desired Qualifications

  • Familiarity with responsible AI, technology risk, data, privacy, and governance practices in a regulated environment.
  • Experience supporting marketing, communications, or related corporate functions.
  • Demonstrated commitment to collaboration and responsible innovation.

About the Company

Bank of Montreal

Runs Canadian and US banks for people and firms

Bank of Montreal, known as BMO, runs a Canadian bank and a large American bank, serving households and businesses on both sides of the border. Until the Bank of Canada opened in 1935, it acted as the Canadian government's banker. People use its branches and apps for accounts, mortgages, credit cards, and investments, while companies borrow from it and turn to its BMO Capital Markets arm to raise money and trade securities. BMO makes money on the gap between the interest it charges on loans and pays on deposits, plus fees from managing wealth and advising on deals. Bank of Montreal was founded in 1817 as Canada's first bank, and it keeps its legal head office in Montreal and its executive offices in Toronto, Canada.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1817

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