Why I believe AI automation is the smallest of the changes coming

How to Think About AI — Edition 4

The conversation about AI in surveying has so far been mostly about one thing. Doing current work faster. Drafting reports more quickly. Reviewing documents in less time. Processing instructions with fewer hands. This is real work and it matters. Firms that get good at it will have meaningful advantages over firms that do not.

But it is the surface of what AI is doing to professional services, not the depth of it. There are three distinct things AI can do to a profession, and the difference between them turns out to matter a great deal.

It can automate the work the profession already does. It can produce entirely new ways of delivering the outcomes the profession exists to deliver. And it can remove the need for the outcomes altogether. Each of these is a different kind of change, and each rewards a different kind of strategic response.

Most of the strategic energy in surveying right now is going into the first one. It is worth taking a clear look at the other two, because that is where the bigger transformation is happening.

Automation: doing today’s work faster

Automation is the most visible. It takes the work a firm already does and uses AI to do it more efficiently. The work is the same. The output is the same. The process gets faster, cheaper, or both.

A firm that uses AI to halve the time it takes to draft a report has a meaningful cost advantage. A firm that automates routine document review can take on more instructions with the same headcount. These are useful gains and worth pursuing.

They are also gains within an unchanged paradigm. The firm is still selling the same product, to the same clients, through the same channels, in the same form. Automation makes the existing model more efficient. It does not change what the model is. Which means automation answers an operational question. It does not answer a strategic one. A firm that becomes brilliantly efficient at producing a product the market is moving away from is still a firm that has not addressed the strategic question.

Innovation: new ways of reaching the same outcome

Innovation is a different category. It does not speed up existing work. It produces a new way of delivering what clients actually need, often through processes the original profession would not recognise as their work at all.

Think about how money moved before ATMs. If you needed cash in the evening, you waited until the bank opened in the morning. Bank tellers handled every withdrawal in person. The ATM did not automate the teller. It did not give the teller a faster machine. It enabled an entirely new way of getting cash to people, one that did not need a teller at all. The outcome of access to your money was preserved. The process was reinvented from scratch.

Innovation is what happens when someone asks not “how can we do this faster” but “is this still the right way to do this at all.” It tends to produce solutions that the established profession does not initially recognise as competition, because the solutions do not look like the profession’s own work.

For surveying, innovation looks like continuous structural monitoring instead of periodic inspection. AI-assisted property risk assessment instead of full site surveys for low-complexity transactions. Real-time condition data feeds instead of point-in-time reports. None of these is automation. They are different ways of meeting the same underlying client needs, delivered through processes that do not involve a surveyor producing a document.

Elimination: removing the need altogether

The third category gets the least attention and may turn out to be the most significant. Elimination happens when the problem the profession exists to solve simply stops being a problem.

The classic example is the great horse manure crisis of the 1890s. Cities were drowning in horse droppings. New York alone had to deal with around 2.5 million pounds of manure a day. Policymakers in London and New York convened conferences to find ways of dealing with it. None of them anticipated what actually happened. The internal combustion engine arrived, horses left the streets, and the problem disappeared.

Nobody automated manure clearance. Nobody innovated a better way of disposing of horse waste. The technology that solved the problem made the problem itself irrelevant.

The pattern shows up everywhere once you start looking for it. Non-iron fabrics are eliminating the need for ironing rather than improving the iron. Preventative medicine is eliminating the need for some kinds of treatment rather than improving the treatment. Self-cleaning surfaces are eliminating the need for cleaning rather than producing better cleaning products.

For surveying, elimination is the hardest category to see clearly because it requires imagining a world in which certain surveying needs no longer exist in their current form. The early signs are visible. If buildings are continuously monitored, the moment-in-time condition survey becomes less necessary. If property data is aggregated, verified, and continuously updated, the standalone pre-purchase survey becomes one input among many rather than the primary source of confidence. If insurers can price risk directly from sensor data and predictive models, the survey-driven insurance decision becomes one mechanism among several. The work itself does not disappear overnight. But the need is being met from multiple directions, and in some categories of work, the question becomes whether a surveyor needs to be involved at a

The three categories reward very different strategic responses.

Automation is an operational discipline. Get good at it, keep getting better at it, and accept that the advantage it produces is temporary because every other firm is doing the same thing.

Innovation is a competitive question. Who is building a new way of meeting the same client need, and what is the firm’s position when the new way arrives? Some firms will choose to build the new way themselves. Others will partner. Others will reposition around the parts of the work the new way cannot touch. All three are legitimate. Doing none of them is the strategic risk.

Elimination is the deeper question, and the one with the longest time horizon. Where is the underlying need for what the firm does being removed, not just delivered differently? Elimination is rarely instant. It tends to play out over a decade or more. But by the time it is visible in revenue, the strategic options have already narrowed. The firms that handle elimination well are the ones that saw it coming and built different revenue streams before they had to.

Most conversations about AI in surveying right now are happening at the automation layer. The bigger transformations are and will happen at the innovation and elimination layers.

Three questions worth holding in mind

For each service the firm offers:

Can AI help us do this work more efficiently? That is the automation question. The answer is almost always yes.

Is there a different way of delivering the outcome this service produces, and is anyone building it? That is the innovation question. The answer is more often yes than firms realise.

Is the underlying need for this service being removed by something happening elsewhere? That is the elimination question. The honest answer for some services is yes too, on a longer time horizon.

Next Monday: how to plan for a capability that does not yet exist

And to be clear, I do not like the idea of surveying as a profession changing fundamentally, but I want to share how I see things evolving in the future.

Nina

Want to go deeper into AI and Surveying?

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