JLL CTO Yao Morin On The Future Of AI In Commercial Real Estate

Posted by Peter High, Contributor | 7 hours ago | /ai, /cio-network, /innovation, /leadership, AI, CIO Network, enterprise&cloud, Innovation, Leadership, standard | Views: 9


In an industry as rooted in physical space as commercial real estate, the digital revolution might appear peripheral. But for Yao Morin, Chief Technology Officer at JLL, the $24 billion global real estate services firm, its at the core of the company’s future. Since stepping into the CTO role two and a half years ago, Morin has been driving a comprehensive technology strategy that hinges on data, artificial intelligence and cultural transformation. Under Morin’s leadership, JLL is infusing intelligence into every square foot of the built environment.

From Overhead to Strategy: Redefining the CTO Role
Morin self-effacingly jokes that her job is “all overhead,” but in reality, she spends her days shaping the future of how technology functions across JLL. Her remit is vast: overseeing a team of 600–700 software engineers and hundreds more data engineers, scientists and AI professionals. This group builds not just internal systems, but external software products that JLL clients use to manage buildings, optimize facilities and, increasingly, embed AI into their daily workflows. “Our team builds everything from scratch,” Morin explained. “We’re the builders behind both the platforms that run our internal operations and the SaaS products our clients rely on.”

AI Products That Talk to Buildings
One of JLL’s flagship innovations is JLL Property Assistant, an AI agent that supports property managers in overseeing everything from maintenance and equipment health to tenant satisfaction. Other solutions like Corrigo and Building Engines facilitate day-to-day operations across massive commercial properties, enabling efficiency through automation. “With AI, buildings are beginning to feel more alive,” said Morin. “The property assistant helps users not just react to issues but anticipate and plan based on data-driven insights.” These products are not theoretical. They are built, tested and deployed first inside JLL itself. “We are client zero,” she underscored. “Before we ship AI tools externally, we use them ourselves to ensure the data is safe, the models are accurate and the experience is seamless.”

Engineering in the Age of AI: Smaller Teams, Bigger Impact
As AI reshapes how software is built, Morin is focused on transforming JLL’s engineering culture to match. She described three key trends:

  1. Coding Less, Reviewing More – With AI-generated code becoming more common, engineers must shift toward code review, architecture and oversight
  2. Shrinking Scrum Teams – Traditional six-to-eight person teams are evolving into three-to-four person squads, each empowered by AI tools to deliver more independently
  3. End-to-End Ownership – The DevOps mantra of “shift left” continues, with engineers responsible not just for development, but also for testing, monitoring and operations.





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