The Digital Economy Has a Physical Footprint 

Much of the conversation about technology centers on what happens on a screen. In commercial real estate, we also need to consider what happens behind it. 

From camera networks and connected devices to cloud applications and AI platforms, digital activity depends on physical infrastructure. Data centers house the servers, storage systems, and networking equipment that make these services possible, along with cooling and backup power systems.

That connection makes the expansion of the digital economy relevant to property owners, developers, investors, and the communities where these facilities are proposed. 

It also raises a question worth asking: how much of today’s development demand reflects durable business needs, and how much depends on expectations that have yet to be proven? 

Surveillance, Privacy, and Data Demand 

The expansion of systems such as Flock cameras brings privacy and accountability into the discussion. My concern is not simply that more information can be collected. It is who controls that information, how long it is retained, and how its use may change over time. 

International examples reinforce the need for precision in this debate. Stanford research describes China’s social credit arrangements as multiple systems and local experiments, rather than a single nationwide scoring system. Its examination of one local program nevertheless raises concerns about discretionary authority, unequal treatment, and oversight. 

For commercial real estate, my view is that expanding data collection is one element of a broader infrastructure story. It should not, without supporting evidence, be presented as the principal driver of data center development. 

AI is an important part of that story, but the International Energy Agency’s outlook also anticipates growth in conventional computing infrastructure. The distinction matters when evaluating what a particular facility will serve and how durable its demand may be. 

AI: A Case for Measured Expectations 

I remain skeptical of the assumption that every business must embrace AI immediately or risk becoming irrelevant. 

In my own commercial real estate work, its benefits have been incremental. It can assist with tasks I would otherwise complete manually, but I have yet to see it replace the judgment, relationships, and local knowledge that underpin this profession. 

That is a personal observation, not a conclusion about every industry. Stanford’s review of the evidence identifies productivity benefits in several settings while emphasizing that results vary by task, worker experience, and implementation.

For our industry, the useful question is whether a tool improves a specific outcome. Does it save meaningful time after review? Improve accuracy? Strengthen client service? Those are better measures than adoption for its own sake. 

I am also concerned about overreliance. A tool that helps us work more efficiently should still leave us able to assess its output and explain our decisions. 

Investment Structure and Tenant Strength 

An infrastructure project’s credibility depends on more than the size of an announced investment. 

Consider a supplier that invests in a customer, which then purchases the supplier’s products. That arrangement can support legitimate growth; it does not automatically erase the economic value of the sale. It does, however, warrant questions about how much purchasing depends on continued financing and whether end customers will ultimately support the spending. 

For property owners, this is a tenant-strength question. Who is responsible for the lease? What supports that obligation? How concentrated is the tenant’s revenue? What happens if expansion slows? 

A compelling technology story should withstand the same scrutiny we apply to other commercial tenants. 

Buildings and Equipment Operate on Different Timelines 

A data center’s real estate and its computing equipment should be evaluated separately. 

Accounting depreciation, physical durability, and economic usefulness are different concepts. New hardware does not automatically make older equipment unusable, but changes in performance, operating costs, and customer requirements can affect its competitiveness. 

The real estate questions follow naturally: who funds equipment replacements, can the facility accommodate upgrades, and what additional power or cooling will be required? 

The IEA also identifies a timing challenge: data center development can move faster than the energy infrastructure needed to support it. Power availability and delivery schedules therefore deserve close attention alongside the building itself. 

Human Judgment Still Matters 

The employment implications of AI remain unsettled. Stanford’s review finds limited evidence of broad AI-driven job losses to date, while recognizing uncertainty and differences across occupations.

That supports a measured approach. Automating a task is not the same as replacing an entire role, particularly when the work involves interpretation, negotiation, accountability, and trust. 

In commercial real estate, those responsibilities remain central to the service we provide. 

The Commercial Real Estate Perspective 

I see opportunity in digital infrastructure, but opportunity does not remove the need for discipline. 

Growing data demand and expanding AI use deserve attention. So do financing dependencies, equipment replacement requirements, power constraints, and community concerns. 

Our role is to ask informed questions, distinguish demonstrated demand from projected demand, and evaluate each project on its merits. Technology may evolve quickly. Sound commercial real estate decisions still require careful analysis and a clear understanding of the risks.