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Director, AI Adoption & Operations Integration

Job in Augusta, Richmond County, Georgia, 30910, USA
Listing for: Greystar
Full Time position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    AI Engineer, Data Analyst, Data Science Manager, Business Systems/ Tech Analyst
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

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 $300 billion of real estate in more than 265 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 $35 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

This position is responsible for leading the adoption, integration, and scaling of AI across property management operations  Director serves as the central connector between technology, operations, and business stakeholders to ensure AI initiatives are coordinated, measured, and delivering real value to onsite teams, corporate functions, and clients. The role spans corporate and operational AI use cases, with a strong emphasis on change management, enablement, cross-functional program leadership, and translating emerging AI capabilities into practical, role-specific solutions for field and corporate teams.

The role also requires strong project and program management capabilities to structure, execute, and scale complex, cross-functional AI initiatives across multiple regions, stakeholders, and business units.

Key Responsibilities
  • Use Case Identification & Prioritization — Find, vet, and sequence AI opportunities across onsite and corporate functions.
  • Partner with field and corporate teams (including RPMs, Directors, and AI SWAT team resources) to identify operational pain points and prioritize high-impact AI use cases.
  • Support the Corporate AI SWAT team in identifying and prioritizing AI use cases across accounting, marketing, and property performance functions.
  • Evaluate new and emerging AI vendors and technologies, maintaining a market map and making adoption recommendations.
  • Adoption & Change Management — Own the change management and adoption strategy for AI rollouts, driving sustained behavior change through leadership engagement, performance alignment, and role modeling.
  • Build and nurture an internal AI community of practice, identifying and supporting super users across regions who can serve as peer advocates.
  • Enablement, Training & Communications — Build the content and forums that make adoption stick.
  • Partner with Operations Enablement and vendor teams to develop and deliver training, SOPs, and communications tailored to onsite teams, RPMs, Directors, and clients.
  • Curate and scale recurring forums and best practices from early adopters and super users, creating a reusable case library for broader distribution (e.g., AI Show & Tell, AI Breakfast Series).
  • Program Management, Analytics & Reporting — Prove value and keep stakeholders informed; lead program management of AI initiatives end-to-end, including planning, sequencing, risk management, and execution tracking across pilots and scaled deployments.
  • Define and track success metrics for AI initiatives, including ROI, time savings, operational performance, and user satisfaction.
  • Coordinate with analytics teams to ensure consistent measurement and deliver executive-ready reporting on AI performance and impact.
  • Vendor & Partner Management — Manage AI vendor relationships end-to-end, including pilot scoping, coordination with engineering teams, roadmap alignment, and tracking of status, risks, and performance.
  • Own the execution and scaling of AI pilots, applying structured program management disciplines to ensure successful transition from pilot to scaled deployment.
  • Governance, Compliance & Cross-BU Coordination — Keep the AI program responsible, legal, and non-duplicative; support AI governance and compliance…
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