The Next Phase of Proptech: Agentic AI Takes Hold in 2026

The Short Version

• Agentic AI is emerging as the next major phase of proptech, moving beyond content generation to autonomous decision-making and execution.
• Retailers and real estate operators are already using AI agents for procurement, pricing, inventory management and event programming.
• Early adopters may gain significant operational and cost advantages as agentic AI matures in 2026.

A New AI Class With Real-World Operational Impact

Agentic AI may dwarf generative AI and other predecessors’ cost-savings prowess through condensed payrolls, operational efficiencies and other functions. “There is no end to the realm that agentic AI technologies can work in,” said Retail Prophet CEO Doug Stephens, an author and retail futurist. Agentic AI isn’t just the future of retail management, he said. “It’s the present. Agentic AI will redefine how organizations operate and compete.” 

Unlike generative AI, agentic AI can process and optimize information to orchestrate complex workflows with little or no human intervention, Stephens explained. “Agents” can make decisions based on programmed objectives but also can adjust their actions on the fly based on real-time information and tools like images, videos, documents and other digital assets.

From Insight to Action: What AI Agents Can Do

A November KPMG Real Estate Accounting and Reporting 2025 client report said potential agentic AI applications are “mind-boggling” and the resulting end-to-end automation “could disrupt entire organizational value chains.” Agents can ingest both structured and unstructured data to make real-time decisions, adapt to new situations and learn from company interactions and feedback, said the KPMG report.

Agentic AI will help stores with more complex tasks than generative AI can perform, Stephens said at ICSC@WESTERN in September, such as programming robots to monitor and replace stock, monitoring security cameras and sensors, observing shopping behavior to identify product trends, choosing the most-effective ads based on a store’s location and adjusting prices based on demand and competitor pricing. An agent also could determine how a change in company strategy or even another pandemic would impact sales and profit, Stephens noted.

What Agentic AI Looks Like in Retail Operations

Agentic AI already is demonstrating its worth for retail functions like procurement, sales support and customer care, he said. Walmart, for example, uses agentic AI to negotiate with suppliers. “Their goal when they started this was to try to negotiate 20% of vendor agreements using agentic AI,” he said in the fall. “They’ve actually negotiated 64% of those agreements thus far to achieve a 1.5% saving on the process. Plus, it turns out that 83% of vendors liked dealing with AI better than with buyers.” Similar efficiencies will become routine as agentic technology rolls out, he posited. “You may soon be using agentic AI workflows to negotiate leases with tenants, and the tenants in turn may be using AI to negotiate with you.”

AI agents also can set up merchandising and marketing campaigns, track sales velocity and seasonality, and monitor inventory, both in-transit and on hand, Stephens said. Auditing agents, for example, can monitor store-operations data and customer feedback, identify performance anomalies across all locations, flag compliance issues and generate corrective action for regional managers, according to KPMG. Stephens offered another example: A retailer contemplating how many pairs of shoes to order from a particular brand could assign an AI agent to discover the trendiest, hottest-selling shoes and most frequently discussed shoes based on social media and other trade information.

From Events to Operations: Real Estate Use Cases

Agentic AI offers potential for real estate operators, as well. A mall, for example, could give an AI agent access to social media and its event history, prompt the agent to research regional tastes and tell it to use the information it finds to create a calendar of events that would drive traffic, Stephens offered. And commercial real estate investor and AI proponent Austin Rogers said in his High Yield Landlord investment report in June that management-intensive retail and multifamily REITs stand to benefit greatly from agentic AI. “REITs have huge amounts of proprietary data that AI can use to improve operations,” he noted.

Stephens asserted that AI agents will save companies millions in administrative and overhead costs. Agents can, for example, cross-reference invoices against contracts, purchase orders and receipts and flag any discrepancies, Stephens said. When customer and supplier lists are updated and a company’s structure or policies change, agentic systems adjust to the new information automatically, he said.

The Competitive Edge of Moving Early

Early adopters will enjoy competitive advantages in growth, scale and value in their commercial real estate operations, Forrester predicted. “Fortune will favor the bold in agentic AI,” it said in a March 2025 report called Agentic AI Is Rising and Will Reforge Businesses That Embrace It. But the technology is still young and can go off course. Thus, companies will need to learn how to use and thoroughly test AI agents, Forrester principal analyst Rowan Curran noted in the report.

PwC forecast in 2023 that AI would contribute as much as $15.7 trillion, more than the combined output of China and India, to the global economy by 2030. Most CEOs said at the time that their companies had yet to see financial returns on investment. However, PwC’s 29th Global CEO Survey, released this month, found that 30% reported revenue increases attributable to AI in the past 12 months. Just over a quarter saw lower costs. Still, more than half have yet to realize either revenue or cost benefits.

Why 2026 May Be the Inflection Point

Further, a KPMG survey of more than 750 Canadian business leaders found that 93% of their firms are using AI, up from 61% in 2024. Still, when the survey was conducted between Aug. 15 and Sept. 3, only 2% had seen ROI. KPMG attributed that to the learning curve of demonstrating and integrating AI. Stephens, though, made the case that the recent rapid adoption of generative AI like ChatGPT has opened a large customer base that will carry forth to agentic AI in 2026 and beyond.