Head of AI Adoption & Continuous Improvement

**Hybrid in Toronto, Canada**

The Role

We're hiring a Head of AI Adoption & Continuous Improvement to lead this Center of Excellence: a hands-on operator who can turn AI tooling and process discipline into measurable product, sales, and service outcomes across a multi-BU software portfolio. This is not an R&D or lab role; it is an adoption, governance, and results role. Success means each business unit ships more, sells more, and serves customers better because of the practices this role puts in place.

The mandate: help the portfolio achieve double-digit organic growth, every year, driven materially by AI-enabled product velocity, sales effectiveness, and operational efficiency.

What You'll Do

• Own the AI-SDLC standard across the portfolio. Drive consistent adoption of AI-assisted software development practices across every business unit's engineering team, moving teams from ad hoc tool usage to disciplined, measured practice.
• Build and run the Center of Excellence. Establish shared playbooks, training curricula, maturity assessments, and adoption scorecards that any BU can plug into, rather than reinventing AI practices independently.
• Translate adoption into shipped outcomes. Work with BU product and engineering leaders to ensure AI investment converts into shipped features, validated against real customer needs not just increased tool usage or hackathon output.
• Partner cross-functionally as an embedded operator, not a consultant. Work directly and regularly with:
  • The Finance Manager, to build the business case, track ROI, and tie AI initiatives to organic growth and margin targets
  • The IT Manager, on tooling procurement, security/governance guardrails, and platform rollout
  • The Marketing Manager, on AI-enabled demand generation, content and campaign production, and positioning of AI capabilities in market
  • Business Unit Managers, on BU-specific adoption plans, blockers, and go-to-market application of AI (e.g., sales enablement, customer support, implementation efficiency)
  • The Portfolio Manager, on cross-BU prioritization, reporting, and alignment with portfolio strategy
• Run measurement and governance. Define and track adoption maturity, usage, and most importantly, business outcome metrics (release velocity, win rates, support deflection, implementation time) tied back to the double-digit organic growth goal.
• Identify and scale AI use cases beyond the SDLC, including sales, customer success, implementation, and support functions where AI can measurably improve growth and efficiency.
• Manage vendor and platform decisions related to AI tooling, in partnership with IT and Finance, ensuring consistent standards across BUs rather than fragmented one-off purchases.
• Report progress to portfolio leadership on a regular cadence, with clear line-of-sight from initiative to growth metric.

What You Bring

• A track record of driving adoption of new tools or practices across multiple teams or business units, not just running a single successful pilot
• Direct experience with AI-assisted software development practices and a credible point of view on what separates real productivity gains from tool-usage theater
• Strong financial and business fluency: comfortable building a business case, tracking ROI, and defending initiatives to Finance and portfolio leadership
• Experience working across functional lines (engineering, sales, finance, IT, operations) without direct authority; this role earns influence through results and relationships, not org chart position
• Comfort operating across a portfolio of independently-run businesses with different products, cultures, and levels of AI maturity
• Prior experience in enterprise or vertical market software (ERP, MES, WMS, or similar) is a strong plus
• Familiarity with IBM i / RPG environments is a plus, given the technology stack of several portfolio companies

What Success Looks Like

• Every business unit has an active, measured AI-SDLC practice with adoption tracked against a defined maturity model
• AI-enabled improvements are visible in shipped product releases, sales cycle metrics, and support/implementation efficiency, not just training completion counts
• Finance, IT, Marketing, Portfolio, and BU Managers treat the CoE as the default resource for AI-related decisions, rather than working around it
• The portfolio demonstrates a credible, defensible link between AI adoption and double-digit organic growth