Educational Workshop: AI in Underwriting

About the Workshop

A two-session interactive workshop for investors, developers, lenders, and operators exploring how AI is being applied to real estate underwriting—from deal screening to IC memos.

Underwriting has always been about speed, judgment, and pattern recognition. AI is now changing all three—but most teams aren’t sure what’s actually possible, what’s reliable, and what introduces new risk.
 

Over two 90-minute live sessions, this workshop delivers a clear, no-jargon explanation of how modern AI works, followed by a deep dive into real-world underwriting use cases across acquisitions, development, and credit.
 

We’ll explore how AI is being used to accelerate deal screening, automate assumptions, abstract documents, stress test scenarios, and support investment decision-making—then focus on implementation: where AI adds leverage, where human judgment still matters, and how to deploy AI without breaking trust, governance, or IC discipline.
 

You’ll leave with a practical framework for applying AI in underwriting—plus tools to avoid hype and focus on accuracy, speed, and decision quality.
 

Participants will receive pre-read materials, including framing decks and underwriting-specific examples, and gain post-workshop access to Circle, where we’ll share recordings, tools, vendor lists, and implementation guides.

You’ll Learn How To

Understand how AI actually works

Break down what modern AI is (and isn’t), including models vs. applications, agentic AI, and frameworks like HITL, HOTL, and HOOTL—explained for investment teams.
 

Explore underwriting-specific use cases

See how AI is being applied to deal intake, rent comps, expense normalization, sensitivity analysis, and memo generation.
 

Learn from real underwriting workflows

Walk through examples of AI-assisted screening, model support, and risk analysis used by active investors and lenders.
 

Evaluate where AI fits in your process

Identify which parts of underwriting benefit from automation vs. judgment, and where AI improves speed without sacrificing rigor.
 

Prep your data, models, and team

Understand what makes underwriting data “AI-ready,” how to structure assumptions, and how to integrate AI into Excel-first workflows.
 

Stay ahead of what’s coming

Explore what’s next in automated modeling, document intelligence, and AI-supported IC processes.

Questions about the workshop?
View FAQs on format, access, recordings and more: FAQs

The Workshop Will Cover

What Is AI and How Does It Work?

• Evolution of AI and key model types
• Models vs. tools vs. automation
• Agentic AI and human-in-the-loop frameworks
  Capabilities—and limitations in financial analysis
   

AI in Deal Screening & Intake

• Automated deal summaries and data ingestion
• OM, rent roll, and T12 abstraction
• Rapid downside and upside flagging
• Prioritizing deals at scale
   

AI in Financial Modeling & Analysis

• Assumption generation and normalization
• Sensitivity and scenario analysis
• Market and comp set analysis
• Supporting—not replacing—Excel models
   

AI in Risk, Credit, and IC Support

• Identifying underwriting blind spots
• Stress testing assumptions
• IC memo drafting and consistency
• Auditability, explainability, and trust
   

How to Implement AI in Underwriting

• Mapping AI to each step of the underwriting process
• Assessing data quality and reliability
• Platform vs. point solutions
• Build vs. buy decisions
• Governance, controls, and error management
   

What’s Next for AI in Underwriting

• Automated model generation
• Continuous market feedback loops
• AI-supported portfolio monitoring
• How underwriting roles evolve—not disappear