Construction and real estate / Commercial real estate services
JLL: Knowledge work for real estate staff
- Company
- JLL
- Country
- United States
- Adoption stage
- In operation
- Source published
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
A single building produces too many kinds of data. Neil Murray of JLL gave portfolio data, usage data, energy data, operations and work order management data, and capital expenditure data as examples. The starting point is that it is hard for people to gather, read and judge on this data.
Technology and data
JLL set a generative AI strategy tailored to real estate problems on top of the JLL Falcon platform. On that it built its own model, JLL GPT. The company presents JLL GPT as the first generative AI built for the commercial real estate industry. This article does not disclose the data used for training, the underlying model or the number of users.
Results
JLL said that in a recent Future of Work survey more than 50 percent of corporate leaders named data quality as a major barrier to spreading AI in commercial real estate. Carlin Power, who leads AI products, described a picture in which brokers, asset managers and client teams spend more time on client relationships and strategic planning while AI takes on data analysis, market research, report writing and basic facility work. That description is a picture of what is to come, not a current performance figure.
Limits and open questions
Adoption figures such as the number of users, throughput or change in working hours are not in this article.
Sources
Compiled from public sources. These are not results from ATF Works customers.