Closing the AI Readiness Gap in CRE: Unlocking Data Foundations & Better Comps

Dealpath’s recent AI readiness survey revealed that while 96% of firms plan to increase AI investment in the next year, 93% face barriers to adoption like expertise, compliance, budget, and decentralized data. 

Join Vivek Thadani (MSCI) and Rob Cain (Dealpath) for a practical discussion on what AI readiness really means in today’s CRE environment, and how firms can unify proprietary, high-quality  data with trusted market intelligence to improve sourcing, screening, and investment decisions.

This session will unpack the gap between AI ambition and execution, and showcase how centralized, standardized data helps teams move beyond experimentation into systematic AI applications across investment workflows to evaluate more opportunities, faster.

What you’ll learn 

• Why AI adoption in CRE continues to lag investment

Key insights from institutional investors on the organizational and data challenges slowing AI adoption.

• What “AI-ready” data foundations actually look like

How centralized, standardized deal, comp, and pipeline data support trustworthy, explainable AI at institutional scale.

• How trusted market comparables strengthen AI outcomes

How MSCI Real Capital Analytics (RCA), supported by MSCI GRACS™, improves consistency and benchmarking.

• How AI can scale sourcing and screening workflows

How Dealpath AI Studio applies AI to data abstraction, comps sourcing, and deal screening to help teams move faster.

Designed for CRE investment, acquisitions, development, lending, research, and technology leaders focused on turning AI investment into real decision-making impact.