Artificial intelligence is reshaping how deals are sourced, analyzed, negotiated and managed across the industrial sector. At NAIOP’s I.CON West this week in Los Angeles, a panel of experts with diverse roles and perspectives discussed efficiency gains, risk considerations and the competitive implications for firms that adopt (or hesitate).
Denice Tokunaga, partner, Seyfarth Shaw LLP, moderated the discussion, which included Jay Carle, partner, Seyfarth Shaw LLP; Chris Karacic, due diligence director, LBA Realty; Will Pearce, CEO and co-founder, Orbital; and Maria Poyer; head of acquisitions, Verrus.
Poyer shared how AI-driven platforms have transformed early site selection. What previously required weeks of analyst time now can be completed in a single day, often by just one person. “So really what that means is the speed of knowing site constraints is much faster. And in the development cycle, that’s everything,” she said. That acceleration has real implications for how many opportunities a team can evaluate, and how quickly they can pursue the most viable ones.
Tasks that once consumed hours or days – pulling jurisdictional data, comparing rent rolls, summarizing long leases – can now be accomplished in a fraction of the time. Poyer acknowledged that there’s a lot of discussion in the market about AI eliminating certain jobs, “but really it’s just transferring the type of analysis that needs to be done by junior folks and senior folks, rather than focusing their time on some of the minutia.”
Karacic shared another use case: “If you run into an issue with a seller that you need to creatively think around, you can prompt AI to give you some methods to solve the issue.”
As the CEO of an AI-enabled real estate technology company, Pearce presented an optimistic view: that AI represents the most significant technical paradigm shift in our lifetimes. In his view, nearly every step of a transaction that involves reasoning, pattern recognition or analysis will be accelerated and eventually executed by AI.
He highlighted the rapid pace of improvement: The latest AI models are doubling in capability once every seven months, so the professionals using them need to continuously recalibrate their expectations.
Optimism will get you far, but pragmatism has its value, too. Carle emphasized that while technology evolves quickly, law and regulation do not – and corporate governance must bridge that gap. Firms must know exactly what data they’re inputting into AI systems, where it’s going, and how it will be handled. Confidential lease terms and investor data, for instance, should never be uploaded into publicly available AI tools.
Companies need clear policies, audit trails and human oversight. It’s critical to have a reasonable validation process for AI outputs and build it into your governance, and clearly define what requires human review. Financial models and major underwriting decisions still need “a human in the loop,” as Carle put it.
With this tech acceleration in hyperdrive, what’s next?
“I would say robotics, and the interaction of AI and robotics, to support real estate construction,” said Pearce, and other panelists nodded in agreement.
Karacic shared a more near-term prediction. “Right now, a lot of the way that we use AI is through prompting… we ask the AI to abstract a lease. Then we ask the AI to look at a credit profile for a tenant. Then we ask it to run an environmental history.” Users have to prompt the AI several times at various steps. Karacic expects that as agentic AI tools – which act mostly autonomously with limited human supervision to accomplish pre-determined goals – continue to be more integrated into the due diligence process, the AI will do a lot of that by itself.
“And it should be able to compare different deliverables against each other,” he added. “So, for example, it’ll be able to look at an environmental history report, assess the risk, and then go look at the financial underwriting and say, ‘Well, do we need to tweak the underwriting based on the environmental risks that I just learned about?’”
Pearce brought up the flywheel effect: As AI capabilities grow, the speed of building AI products increases, which further strengthens AI itself – a cycle that drives the exponential growth AI researchers often discuss.
“I think things are going to get pretty scary pretty quickly,” said Pearce, clarifying: “Scary like good scary, like there’s going to be a world of opportunity with AI to disrupt real human work.”
This post is brought to you by JLL, the social media and conference blog sponsor of NAIOP’s I.CON West 2026. Learn more about JLL at www.us.jll.com or www.jll.ca.
