Why CRE Needs Agentic AI, Not More Chatbots
In a Q&A with citybiz, Feasibly founder and CEO Brian Connolly explains why commercial real estate has struggled to extract value from generative AI and how purpose-built agentic systems change the picture. Connolly argues that most firms started with the wrong tool, investing heavily in generic chatbots and copilots that were never designed for the complexity of CRE workflows. He cites a 2025 MIT study finding that 95 percent of organizations reported no measurable P&L impact from generative AI despite enterprise spending of $30 to $40 billion, and a JLL survey in which 60 percent of decision-makers said they felt unprepared to implement AI into business workflows.
Connolly draws a clear line between chatbots and agentic AI. Where chatbots answer questions and generate responses dynamically, agentic systems are structured, goal-oriented, and built to execute multi-step workflows with consistency and minimal oversight. He compares the difference to an intern searching through files versus a trained specialist who already knows where to look and how to act. In an industry where consistency and accuracy drive underwriting and capital decisions, he says, removing variability matters.
The Q&A turns to where Connolly sees the most immediate impact: market studies and financial feasibility analysis. Traditional feasibility studies can cost $50,000 or more and take months of analyst time, and he explains that agentic AI can reduce that time and cost by up to 90 percent. In Feasibly's system, specialized agents handle discrete tasks such as data retrieval, market validation, benchmarking, forecasting, and narrative synthesis, with a human expert kept in the loop to validate outputs and ensure compliance. Connolly frames this as elevating the analyst role rather than replacing it.
Connolly closes by connecting the approach to broader industry challenges, noting that faster, more accessible feasibility analysis could help first-time developers test ideas, secure early funding, and move stalled projects forward, with implications for the nation's apartment shortage. His advice to CRE leaders is to shift from asking how to use AI toward identifying the specific problems they want AI to solve, then adopting purpose-built systems designed to solve them.
