Manager AI Governance & Enablement

We are hiring a Manager AI Governance & Enablement on behalf of a well-established organization in Mississauga.

In your new role as a Manager, AI Governance & Enablement, you will be accountable for operating and advancing company’s enterprise AI practice. The role exists to help the organization adopt AI safely, practically, and at scale by combining governance discipline with education, advisory support, and pragmatic implementation guidance. It is not a research or data science role.

You will operate the governance processes that determine how AI is introduced into day-to-day work, help departments identify and prioritize valuable AI use cases, and ensure AI systems are deployed responsibly as they become more multimodal, more connected to enterprise data, and more capable of influencing decisions, workflows, and user behaviour. The role also serves as AI expertise-as-a-service function, working across corporate departments, FASTech, Service Management & Automation, Business Analysis & Quality Assurance, Data & Analytics, Privacy, Cybersecurity, and enterprise applications so that AI-enabled solutions are useful, explainable, governable, and aligned to operational realities.

The position has no direct reports. Authority is exercised through ownership of enterprise AI governance processes, leadership of the AI enablement program portfolio, management of third-party AI partner relationships, and cross-functional influence rather than direct supervision. The role owns the working relationship with external AI platform providers, training partners, and advisory firms - holding them to company’s governance, privacy, and security expectations, and leveraging them to extend internal AI education and enablement capacity. Governance framework design, risk-tier definitions, and final approval authority for higher-risk AI initiatives rest with the Director, Innovation & Technology Enablement; this role recommends, operates, and enforces.

Key Accountabilities

Enterprise AI Governance

• Recommend, maintain, and continuously improve AI governance framework, standards, guardrails, and acceptable-use practices in alignment with legal, privacy, security, and risk requirements, escalating framework changes to the Director for approval.
• Apply and document practical controls for responsible AI use, including human accountability, override mechanisms, confidence thresholds, auditability, data handling expectations, and documentation standards.
• Operate the AI intake and review process end to end - triage, assessment, and recommendation on appropriateness, value, risk, explainability, and organizational readiness.
• Apply established risk classification and approval paths, distinguishing between low-risk productivity uses, operational decision support, and higher-risk use cases, and route initiatives above the defined threshold to the Director for decision.
• Partner with Privacy, Cybersecurity, Legal, and enterprise technology leaders to ensure AI-enabled solutions meet policy, compliance, and audit expectations.
• Define and apply governance expectations for third-party AI providers and partners, including data handling, model transparency, sub-processor disclosure, and alignment to company’s privacy and security requirements, working with Privacy, Cybersecurity, Legal, and Procurement.

AI Education & Organizational Readiness

• Design and deliver role-based AI education, awareness, and training programs for leaders, practitioners, and end users.
• Create and maintain practical playbooks, templates, examples, and decision guides that help teams use AI effectively and responsibly.
• Promote AI literacy across the organization by translating technical concepts into plain-language guidance and actionable practices.
• Support leaders in understanding the opportunities and risks of multimodal AI, connected AI, agentic workflows, and AI-assisted decision support.
• Track adoption, usage patterns, and learning outcomes to refine enablement programs and improve organizational readiness.
• Manage third-party training and enablement partners, including scope, delivery quality, and alignment of externally sourced content to Chartwell’s AI standards and governance expectations.

AI Expertise-as-a-Service (Advisory)

• Provide advisory support to corporate departments on AI opportunities, use-case framing, vendor and tool evaluation, and solution options.
• Help teams convert ambiguous problems into clear AI and automation use cases with defined objectives, constraints, risks, and success measures.
• Support business and technology teams during design and implementation with practical guidance on model and tool selection, workflow design, prompting patterns, and integration considerations.
• Act as a trusted internal partner who helps departments move from experimentation to controlled, business-aligned AI adoption.
• Contribute expert guidance to FASTech and other delivery teams so that AI-enabled solutions remain practical, supportable, and aligned with enterprise standards.

Safeguarding the Organization as AI Evolves

• Develop guidance and control patterns for AI systems that use text, images, documents, screenshots, voice, and other multimodal inputs or outputs.
• Apply governance to AI systems connected to enterprise data sources, documents, communications, applications, and external research tools.
• Assess and mitigate risks related to hallucinations, model drift, privacy invasion, data leakage, bias, impersonation, surveillance, over-reliance, and unsafe automation.
• Recommend boundaries for where AI may assist versus where decisions must remain deterministic or human-owned, especially for safety, compliance, financial approvals, and resident-impacting decisions.
• Provide guidance on the safe use of AI as an assistant, coach, or decision-support tool, including controls to prevent manipulation, inappropriate inference, or hidden monitoring behaviours.

Program Leadership & Cross-Functional Collaboration

• Lead the AI enablement program portfolio, including planning, sequencing, stakeholder coordination, and delivery tracking against committed outcomes.
• Work closely with FASTech, Service Management & Automation, Business Analysis & Quality Assurance, Data & Analytics, Cybersecurity, enterprise applications, and business leaders to align AI adoption with business priorities.
• Own the ongoing working relationship with third-party AI platform providers, advisory firms, and education partners, including roadmap awareness, escalation paths, and periodic performance and risk review.
• Maintain the enterprise register of approved AI use cases, tools, integrations, risks, and realized outcomes.
• Prepare executive reporting on AI pipeline, enablement activities, governance findings, adoption levels, and realized value for presentation by the Director.
• Identify recurring themes, risks, and opportunities across departments and recommend pragmatic improvements to AI operating model.

Qualifications

Education

• Post-secondary education in Computer Science, Data, Information Systems, Business, Risk, Privacy, or a related discipline is preferred.
• Demonstrated and credible expertise in AI governance, responsible AI, and enterprise AI enablement will be strongly considered in lieu of a formal degree.
• Coursework, certifications, or professional development in AI governance, privacy, risk, responsible AI, or change management are assets.

Experience

• 8+ years of progressive professional experience in technology, digital transformation, technology advisory, or a closely related field.
• 5+ years of combined, demonstrable experience across AI governance, AI adoption and enablement, people enablement and training, and hands-on AI solution development.
• Demonstrated experience establishing or operating governance, standards, or policy controls for enterprise technology or AI adoption.
• Experience designing and delivering training, communications, and change readiness programs for technology adoption.
• Practical working experience with large language models, copilots, AI agents, multimodal AI, and AI systems connected to enterprise data and workflows, including hands-on prototyping or solution build.
• Experience leading programs or workstreams to delivery without direct authority over contributors.
• Experience operating in a mid-sized, decentralized, multi-site environment is an asset; exposure to seniors housing, real estate, healthcare delivery, retail, or hospitality operations is an asset.

Skills & Abilities

• Communication: Strong written and verbal communication skills; able to translate technical concepts into clear guidance for business leaders and end users.
• Influence & Facilitation: Strong facilitation, stakeholder management, and influence skills across functions and levels, including the ability to hold a governance position under pressure while maintaining constructive working relationships.
• Risk Judgement: Pragmatic risk management mindset with the ability to balance innovation with restraint.
• Technology Assessment: Ability to assess emerging AI capabilities and convert them into practical organizational guidance and standards.
• Program Discipline: Structured approach to planning, documentation, and delivery tracking so that enablement commitments are measurable and auditable.