Senior Director - AI Enablement

About this role

ABOUT GREYSTAR

Greystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $350 billion of real estate in more than 260 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over one million units/beds globally. Across its platforms, Greystar has nearly $79 billion of assets under management, including over $34 billion of development assets and over $36.5 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit .
JOB DESCRIPTION SUMMARY
The Senior Director, AI Enablement owns the production of role-specific AI capability: the Skills, projects, agents, product education and workflows that make GPS, Prism and our data platform usable inside the job, for the roles that matter most. Training is a delivery mechanism for this work, not the product. The product is a working set of content and tools a Greystar team member can pick up and use, on real Greystar data, and a measurable change in how they operate.

This is the technical counterpart to the Director, Talent Development in People & Culture. That role owns the enterprise learning framework, leadership development and the learning technology stack, and is the distribution channel to the workforce. This role owns what gets distributed — the artifacts, the technical standards behind them, and the adoption they drive.

This is a builder’s seat with a leader’s remit. The right person is fluent enough in Claude, ChatGPT, AI tools, MCP and data platforms to author skills personally and set the bar for a team that does, and commercial enough to argue, in NOI terms, why a given workflow should be rebuilt at all.JOB DESCRIPTION
Key Responsibilities
Role-Based Capability Production

• Define, for each priority role, what “AI-enabled” concretely means in the workflow — which decisions, which reports, which repetitive steps — and build the artifacts, or work with the teams to build the artifacts and education that deliver it.

• Author and ship Skills, projects and agent workflows grounded in Greystar’s metric definitions (Atlas), data platform (DMP) and intelligence products (GPS, Prism, LEAP); personally build the first versions, then scale the team’s output working closely with your HR counterpart to expand delivery.

• Maintain a governed skill & tool library with ownership, versioning, test cases and deprecation — treated as a product, not a training catalogue.

• Sequence work by leverage: key roles first, in lockstep with leadership, the GPS roadmap and the FDI Pod deployments.

Adoption and Measurement

• Own the adoption metric for AI capability across eligible roles: active users, repeat usage, workflow coverage, time-to-first-value.

• Instrument enablement artifacts so usage is visible without self-report; partner with Data Engineering on the consumption and usage feeds.

• Run the feedback loop from the field into the artifacts — what breaks, what is ignored, what gets copied — and iterate weekly.

• Report adoption alongside FDI Pod impact so cost and value are always shown together.

Partnership with People & Culture

• Serve as the primary technical partner to the Director, Talent Development, and to People Strategy & Programs on AI readiness; P&C owns the pathway, readiness approach and competency framework, and this role owns the technical content and the tools.

• Feed enablement artifacts and technical curriculum into Workday Learning and P&C programs as the distribution channel; do not build a parallel LMS.

• Share role-level adoption data (active users, workflow coverage, time-to-first-value) with People Strategy & Programs so manager enablement and communications can target where readiness lags.

• Jointly define what an “AI-ready” role profile looks like for hiring and internal mobility, with P&C owning the competency framework.

Standards, Safety and Governance

• Set the technical standards for enablement artifacts: data access aligned to the External Data Sharing Framework and Unity Catalog permissions; no ungoverned data paths.

• Ensure every skill is grounded in the definition of record (Atlas/GPS); when a skill and a legacy report disagree, the platform number travels.

• Partner with InfoSec on prompt, data and model-flexibility standards as the model landscape changes.

Team Leadership

• Lead and retool the AI Enablement team from a training orientation to a build orientation; hire for skill authorship and applied AI over instructional design where the two conflict.

• Build a champion network inside the business units that extends the team without adding headcount, with clear standards for what champions may and may not ship.

• Model the operating principle of the function: narrow aperture, ship, measure, iterate; say no to requests without a role, a workflow and a metric attached.
What We’re Looking For
Experience

• Led an AI or technology enablement function in a large, complex organization through an actual adoption curve — not a pilot program.

• Demonstrated hands-on record building with LLM tooling in production: skills, prompt systems, agent workflows or equivalent that other people used at scale.

• Partnered closely with data or engineering teams to ground enablement in real systems and real data, and with HR or L&D as the distribution partner.

• Measured adoption and outcomes rigorously and can distinguish reach, adoption and impact without prompting.

• Experience in operations-heavy, distributed businesses (real estate, financial services, healthcare, logistics) is an advantage; multifamily is not…