Dynamic Pricing Has Arrived in the Office Market
Landlords are increasingly using sophisticated, real-time data to determine how they price available office space. Historically, asking rents were established primarily through comparable lease transactions. The problem is that comparable lease data is inherently backward-looking. By the time a transaction becomes part of the market narrative, the economics were often negotiated months earlier. It was also difficult to precisely isolate the true competitive set for a particular space and understand the real-time dynamics within that subset of supply.
That is changing.
Today, institutional landlords can access highly detailed leasing intelligence through platforms like VTS, a software system widely used to track leasing activity across institutional office portfolios. Landlords require their leasing teams and brokers to report market activity into the platform, creating an expansive real-time dataset. Most major institutional owners now operate within this ecosystem.
More importantly, AI is beginning to transform that raw activity into strategic insight.
Landlords can now dissect the market at a micro level, segmenting supply by building quality, floor size, geography, tenant profile, availability timing, and competitive positioning. Instead of relying solely on completed lease transactions, they can analyze active negotiations and letter-of-intent pricing to understand where the market is moving in real time. In many cases, this provides a more accurate picture of current pricing pressure than signed leases.
The implications are significant.
We are beginning to see landlords make strategic pricing decisions based not simply on where the market was six months ago, but on where they believe it is heading. In some cases, owners may intentionally hold space off the market, allowing competing inventory to lease first so their remaining availability enters a tighter supply environment. Scarcity drives leverage, and leverage drives pricing.
This introduces a new level of complexity for occupiers.
Companies and their advisors must now understand the mechanics of dynamic pricing and the data influencing landlord behavior. Tenant advisors must possess the strategic capability to interpret the data and get ahead of how the landlord is using it to gain leverage in the negotiations.
Our long-held belief in “selling our client’s tenancy,” as opposed to simply helping them “lease space”, has never been more relevant. Data may support a landlord’s pricing thesis, but not all demand carries equal value. The tenant willing to pay the highest rent is not always the tenant a landlord most wants over the long-term.