The importance of judgement in business, especially in the field of commercial real estate, is gaining increasing relevance. The value of information is falling, while the value of judgement is rising. This is based on the simple premise that information used to be a major competitive advantage because it was difficult to obtain. Knowledge of ownership, sale prices, development plans, comparable transactions, active buyers, financing options and developments in a specific sub-market offered a significant advantage.
Today, much of this information is immediately available, and artificial intelligence (AI) is accelerating this trend to an extraordinary degree. After the publication of a previous column, a user asked whether practical examples could be given of situations where judgement went beyond the limits of AI. Such examples are found almost daily in investment sales brokerage, as AI can increasingly replicate the information level of the work. The level of judgement, however, is something entirely different.
Let us consider the fundamental task of valuing a building. AI can process comparable sales, rents, operating costs, capitalisation rates, interest rates, zoning plans, property taxes and dozens of other variables, and would probably generate a very credible valuation range. Assume the result is $40 million. The more important question might be: Should this particular owner sell the building today for $40 million? This requires an understanding of the owner's basis, their debt, taxes, partnership structure, family situation, alternative uses for the proceeds, risk appetite and market view. In many cases, the ultimate advice was not to sell the property. AI can determine the value, but judgement determines what to do with that information.
Another common scenario is the marketing of a property, where 10 offers ranging from $47 million to $52 million are received. Technology can organise these bids clearly, and AI can assess them instantly. But is the $52 million offer actually the best? Possibly yes, possibly not. It is necessary to check who has equity, who needs financing, who has investment committee approval, who has renegotiated with buyers in previous transactions, who understands the building's problems, or who has a history of successfully closing difficult transactions. It might be that a seller is better off accepting $50 million from buyer B rather than $52 million from buyer A. While a spreadsheet would show a lost profit of $2 million here, judgement significantly increases the likelihood of successfully closing the transaction. The highest offer and the best offer are not always identical.
Comparable sales provide another example. AI can identify 20 properties that statistically appear comparable to a building being valued. After 42 years of specialisation in this market, 15 of these 20 transactions could immediately be ruled out. For example, because a buyer urgently needed the adjacent plot, another seller was under unusual financial pressure, a transaction included favourable financing, another had unrecognised development potential, or a buyer had strategic motives that led them to pay above the price of an ordinary investor. The computer sees 20 data points; experience tells us that only five of these are truly relevant. Information identifies the comparisons, judgement determines which comparisons carry weight.
This becomes particularly relevant with vacant buildings. AI can calculate what a traditional investor should pay based on the potential income of a property. But what if the best buyer is not an investor, but a school, a hospital, a university, a non-profit organisation, a company, a religious institution, or a wealthy private individual who needs the property for their own use? Such buyers can assess value entirely differently. An analysis of over a thousand user transactions shows that users often pay significant premiums over investor prices. While investors ask what return the building can generate, users ask how owning this property affects their business and its perception. AI can accurately value the property as an investment, but judgement helps to identify the buyer for whom the property has strategic value.
- —What if we combine this building with the adjacent building?
- —What if we acquire air rights from another property?
- —What if a retail tenant can be bought out?
- —What if an easement resolves an issue with light and air?
Development sites are another excellent example. AI can show the density, permitted floor area, allowable uses, available air rights, and theoretical development potential of a single plot. However, the most successful development transactions often began with questions not contained in the data. AI excels at analysing existing components. Judgement sometimes means imagining a table that does not yet exist. Finding potential clients perhaps illustrates the changing value of information better than anything else.
