AI Enablement Leader

Johnson Controls•Glendale, AZ

6d•$130,000 - $175,000•Remote

About The Position

The AI Enablement Leader is responsible for making the JCI enterprise measurably better at using AI. This is a capability-building and standards role rather than a delivery role. The person in this seat owns how our enterprise learns, adopts, and standardizes AI tooling, and sets the enterprise standards for AI licensing and tooling personas to execute against. The role also carries the coordination layer across our shared agentic and analytics foundation work: the centralized knowledge base, agent repository, agent design standards, semantic layer, and related workstreams. Individual workstreams stay with their technical owners. This role supplies the coordination, standards alignment, and forward pressure that keeps the portfolio moving as one strategy instead of disconnected efforts. The role is our consultative front door to the rest of Johnson Controls. That means partnering with HR and Learning & Development on enterprise AI fluency, advising functional and technology leaders on where AI fits into their workflows, working alongside information security, legal, and compliance so adoption is safe by design rather than corrected after the fact, and serving as the point person for AI Week. What this role builds for one function should work for the next ten, so reusable frameworks matter more than one-off answers. Success in this role looks like influence, not throughput. The person who thrives here moves work forward through other people's teams, is comfortable holding a standard without owning the pipeline, navigates a large matrixed organization without needing formal authority, and can tell the difference between activity and adoption.

Requirements

Bachelor’s degree in business, technology, data, organizational development, or a related field. Advanced degree welcome but not required.
7+ years of professional experience, with at least 2 years leading enablement, training, standards, or program functions in a technology or data organization.
Demonstrated experience driving adoption of new technology across an organization, including measuring that adoption quantitatively.
Experience operating in a matrixed environment where delivery depends on teams the role does not own.
People management experience, or clear readiness for it.
Working fluency with the current enterprise AI tooling landscape, including Microsoft 365 Copilot, Copilot Studio, and agent platforms. Able to hold a credible conversation with AI engineers without being one.
Understanding of agentic architecture concepts sufficient to coordinate standards work: agent design patterns, reuse and repository models, knowledge grounding, and semantic layers.
Comfort with usage and adoption analytics, including defining metrics, working with platform telemetry, and building reporting for executive audiences.
Strong program management capability, including dependency and risk management across multiple owners.
Influence without authority. Most of this role’s outcomes are delivered by other people’s teams.
Willingness to hold a standard, including saying no to exceptions that would erode it.
Consultative posture with senior stakeholders, able to advise on measurement and approach rather than take orders.
Judgment about scope. This role will be pulled toward execution constantly and needs to resist it.
Clear written and verbal communication for audiences ranging from engineers to the executive committee.

Nice To Haves

Advanced degree welcome but not required.
Clear readiness for people management.

Responsibilities

Enterprise AI enablement and adoption measurement. Own the strategy, curriculum, and cadence for how the organization builds AI fluency and applies AI to its own workflows. Organize and run training, define what each role should be able to do with AI, identify capability gaps, and drive from tool availability to habitual use. Instrument and report that progress, bringing a clear quantitative view of AI usage and capability to organizational reviews.
AI standards: licensing and tooling personas. Define and maintain the enterprise standards governing AI tool licensing, excluding software engineering tools: which tools are approved, what qualifies a user for a license, and how licenses are allocated, reclaimed, and reviewed. Own the companion persona framework that maps roles to the tools, licenses, and training paths appropriate to them, and keep it current as the tool landscape shifts. Standards are set here; execution and provisioning sit with the platform, engineering, and delivery teams.
AI Foundations Portfolio coordination. Provide coordination across the shared agentic and AI-related analytics foundation workstreams, including the centralized knowledge base, centralized agent repository, agent design standards, semantic layer, Power BI embed pattern, and centralized agent backlog. Work directly with the AI leaders inside DA&AI to translate technical direction into enablement and standards, maintain the integrated view, surface risk and dependency early, keep standards consistent across workstreams, and hold owners to committed dates without taking over their delivery.
AI Week point person. Partner with leadership on AI Week, including planning, track and content coordination, seat allocation, speaker and sponsor logistics, and post-event reporting.
Enterprise AI fluency partnership. Partner with HR and Learning & Development on the enterprise AI fluency program, advising on curriculum design, audience segmentation, KPI selection, and what counts as credible evidence of fluency. Support recurring enterprise-facing programs such as Agent in a Day cohorts, AI Coffee Chats, and the Start Here training discovery hub. Consultative, not owning.
Functional AI advisory. Work with non-AI functional and technology leaders across Johnson Controls to identify where AI applies to their workflows, connect them to the right tools, personas, and training, and route substantive build requests to the appropriate delivery team.