AI isn't killing consulting—it's exposing time as a poor measure of value

Over the past few months, the author has heard clients ask a pointed question: "Why am I paying a consultant for something AI can do in 15 minutes?" On the surface, it seems fair. Generative AI can draft documents, analyse data, write code, and create presentations in a fraction of the time they once took. If a task now takes minutes instead of hours, the logic goes, why maintain the old pricing?

The author's answer hinges on a distinction between what consulting firms sell and how they have priced it. About ten years ago, while working at Risual, the author regularly delivered a consulting engagement called a Vision and Scoping Document that took around ten days. Sales colleagues described it to customers as a "ten-day engagement"—a description that bothered the author. The customer was not buying ten days; they were buying clarity: a clear understanding of where they were, where they wanted to be, and a roadmap to get there. Ten days was simply the firm's estimate of the effort required to deliver that outcome. If the work was completed in eight days, the firm made extra profit. If unforeseen issues extended it to twelve days, that was the firm's problem, not the customer's. Yet over the years, knowledge work became comfortable being priced in terms of days, hours, and rates, with time serving as a convenient proxy for the value being delivered.

This pattern extends beyond consulting. The author recently collected a car after repair work and was charged for one hour of labour at £95 plus VAT, even though the visit lasted only forty minutes. When queried, the garage explained it was "a plug in"—their term for a fixed-price job. They were not charging for exactly sixty minutes of someone's time; they were charging a standard amount for the repair. In other words, the garage was already engaging in value-based pricing, but presenting it as time and materials. Time was simply an easy way of arriving at a price. The irony is that by describing it as "an hour of labour," the garage encouraged the customer to question the price rather than the outcome.

The locksmith thought experiment makes the same point. If a locksmith arrives at your house, examines the lock for a few moments, and opens the door in thirty seconds, most people do not argue that the bill should be lower because it took only half a minute. You are paying for the years of training, the specialist tools, and the confidence that the door will open without damage. You are paying for the outcome. If the locksmith had spent two hours trying different techniques before succeeding, you would likely have less confidence in their expertise, not more. Yet consulting firms are routinely questioned on price when the same principle should apply.

Warren Buffett once observed that "Price is what you pay. Value is what you get." For years, consulting has treated time as though it were synonymous with value. AI is forcing a reckoning. Customers are not buying typing, prompt engineering, or someone to spend ten days producing a document. They are buying judgment, experience, and confidence. They are buying better decisions, reduced risk, and faster progress. AI changes the cost of delivering those things, but it does not diminish their value. If anything, it increases the importance of knowing when to trust AI, when to challenge it, and how to turn its output into something genuinely useful.

AI is already an extraordinary amplifier of expertise. When put in the hands of someone who understands the problem they are trying to solve, it often delivers better work faster than ever before. Put it in the hands of someone without that experience, and it often produces something that looks convincing but lacks the judgment that comes from years of practice. AI compresses effort; it does not compress experience. Anyone can ask AI to generate a strategy document, but producing one that reflects an organisation's objectives, culture, constraints, and appetite for change is something else entirely.

The author does not think AI will kill consulting firms. Instead, it will accelerate a move away from charging for effort and towards charging for outcomes. Firms that continue to sell "ten-day engagements" may find customers asking increasingly uncomfortable questions. Those that sell measurable business value and use AI to improve the efficiency of delivering it should become more competitive. Perhaps the biggest commercial shift AI will bring is not the end of consulting, but the end of pretending that time is a good proxy for value.

The article articulates a tension that has long existed in knowledge work but is now impossible to ignore. For a decade, the author noted that consulting engagements were marketed and priced by duration ("ten days"), even though the customer was paying for a deliverable—a clear roadmap and understanding—not the calendar time. The estimate of ten days was simply a cost model for the consulting firm to earn a return; if work finished in eight days, the firm pocketed extra profit. This conflation of time with value persists across many industries: the author's garage visit and the locksmith analogy both reveal that value-based pricing (whether explicit or hidden) is already the norm when the outcome is visible and verifiable.

Generative AI has made this friction acute. When a task that once required hours now takes minutes, clients naturally ask whether the price should fall proportionally. The article argues this is a category mistake: the price reflects expertise and judgment, not typing speed. AI amplifies the productivity of skilled practitioners (those who know when to challenge the model, how to interpret its output, and what context it lacks) while potentially creating risk for those without experience—they can produce convincing-looking work that lacks the hard-won judgment of practice. The real commercial shift, then, is not the end of consulting but a realignment: firms that continue packaging time-based services will lose competitive pressure, while those that transparently sell outcomes (faster delivery, lower risk, better decisions) and use AI to achieve them will strengthen their position.