Harvard executive training teaches real estate investors to cut through data noise with AI tools and a proven framework

Harvard University's Graduate School of Design will run a three-part executive training course this December on real estate investment strategy, AI models, and data analytics. The online program, scheduled for December 2, 4, and 7, 2026, from 11:00 a.m. to 1:00 p.m. Eastern, is taught by Jeff Adler, vice president of Yardi Matrix and a real estate economist who leads the firm's data analytics division.

The course targets commercial real estate professionals who face a flood of conflicting market signals. "We're often inundated with meaningless and contradictory information that masquerades as 'data,'" Adler said. The program aims to replace that noise with an integrated investment perspective that leads to action and better results.

Participants will work through real deals closed in the current difficult financing environment. The curriculum connects macroeconomic forces, federal policy shifts, and local housing regulation directly to property income and valuation.

Inflation and interest rate mechanics

The first topic cluster examines the sources of inflation-money supply growth, U.S. federal government deficits, and disruptions across transportation, goods, labor, food, and energy markets. The course will trace the Federal Reserve's interest rate response and explain how short- and long-term rates interact to eventually control price pressures. These dynamics are then tied directly to real estate income streams and asset valuations.

Federal policy and the re-industrialization of markets

Adler will analyze how recent federal legislation is reshaping investment geography. Policies discussed include the CHIPS Act, the Inflation Reduction Act, and the Big Beautiful Bill. The focus is on how these measures foster re-industrialization in markets that institutional capital previously overlooked, including the AI data center buildout now underway across the country.

Housing affordability and public policy responses

The program surveys the range of government reactions to housing affordability pressures. It contrasts market-driven development approaches with interventions that enable rent control, and examines the on-the-ground impact each has on local markets. For investors allocating capital across jurisdictions, understanding this regulatory divergence is a core risk-management skill.

New and experienced investors will learn to use AI tools and a proven analytical framework to develop a cohesive strategy. The course is offered in partnership with Yardi Matrix, and continuing education units are pending. For professionals focused on leadership applications of these technologies, AI for Executives & Strategy resources address the same intersection of business intelligence and decision-making. Those working specifically in property markets can find related training under AI for Real Estate & Construction.

Why this matters for executives and strategy leaders

Investment committees and senior decision-makers cannot afford to treat data quality as a back-office concern. When a portfolio's performance hinges on correctly reading inflation trajectories, legislative timelines, and local rent-control risks, the analytical framework becomes a fiduciary obligation. This course delivers a structured, repeatable process for separating signal from noise-one that applies AI models not as a gimmick, but as a tool for testing assumptions against closed deals and real-world policy outcomes.