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 www.greystar.com .
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,…