Why Legal Services demand is about to grow, not shrink
I recently spoke with a successful technology entrepreneur who built and exited a business with more than 50 percent share in its target market. As is the case with many such entrepreneurs, he also owns several other businesses, including a successful software services company. It will be no surprise that he is now operating at the forefront of AI adoption, actively embedding it into how the software services business delivers work.
I asked what many in professional services are quietly trying to understand: "What does this mean for people and revenue?" The expectation, at least in some corners, is that AI will reduce both. His answer, however, suggested the exact opposite.
Clients are not asking for fewer people; they're asking for more senior people. "Now that you're using AI; can you apply the value to deploying several more experienced operators on the project? Not less spend, but the same spend deployed differently. The objective is not to reduce cost but to increase what can be achieved with it…"
This is not a simple story of efficiency leading to lower prices and therefore lower demand. It reflects something more structural - that organisations are not currently operating at their optimum level of legal services consumption.
This observation challenges one of the more persistent assumptions about AI in professional services - that efficiency will naturally lead to reduced demand, rather than a reallocation of effort toward higher-value work.
In reality, many organisations are consuming less legal capability than they would ideally choose to. Internal capacity constraints, prioritisation trade-offs and operational friction mean that a significant portion of potential legal work is never progressed.
The assumption that demand is fixed
There is a widely held view in legal circles that as AI improves efficiency, the cost of our services will fall and so too will demand. The logic appears sound: if work can be done faster, clients will expect to spend less… however that assumes demand is static. In practice, it very rarely is.
Most organisations operate with a sizeable backlog of initiatives they would pursue 'if' they had the capacity. Strategic programmes are delayed, operational improvements are deferred and risk issues are managed incrementally rather than resolved at scale and quickly. The constraint here is not a lack of ideas or intent; but a lack of time and the capacity to execute.
AI does not remove that demand - it just exposes it and as the time required to deliver work compresses, the limiting factor shifts - moving away from execution and toward judgement, experience and the ability to prioritise and act.
In doing so, AI relaxes those constraints. It unlocks backlog, reduces friction and enables organisations to progress work that was always there but previously inaccessible. In that sense, AI does not create demand from nothing - it induces demand by making latent demand actionable.
There is an adjacent economic intuition here. In other domains, efficiency gains have at times led to increased overall consumption rather than less - a phenomenon sometimes referred to as the Jevons paradox. While not a perfect analogy, it points to the same underlying dynamic: when something becomes easier to use, it is often used more widely.
Two schools of thought
This is where the divergence in schools of thought becomes even more apparent…
Entrepreneurs tend to approach AI through a lens of abundance. They see (in AI) increased capacity, faster iteration and the ability to pursue opportunities that were previously out of reach. To them, it's logical that more capability leads to more activity, not less.
Professional services, and law professionals in particular, often approach the same shift through a lens of scarcity. Their focus is on margin pressure, pricing compression and the potential erosion of traditional models and the billable hour. Efficiency is interpreted as a threat to value rather than a driver of it.
Both perspectives are understandable - but they lead to very different outcomes.
Where value moves
AI compresses the production of work and tasks like drafting, basic analysis and a range of other repeatable tasks can now be completed quickly and at a lower cost. This is not insignificant, but it is also not where lasting value ultimately resides. As execution becomes easier, the relative importance of what cannot be automated increases and framing the right problem, navigating ambiguity, making trade-offs and standing behind decisions become more central. Clients are not paying for output in isolation but for confidence in outcomes. In this context, AI does not diminish value - it shifts it.
And as this shift occurs, legal capability is not withdrawn - it is redeployed. It is applied across a broader set of decisions, risks, transactions, governance activities and strategic initiatives that were previously deprioritised or left unaddressed.
Why spend will not fall
The entrepreneur's insight is instructive. Clients are not looking to reduce their spend on capability - they are instead looking to expand what that spend delivers. When capacity increases, it is rarely banked as a saving; it is simply redeployed. More initiatives are progressed, more strategic work is undertaken and more issues are addressed within the same budget envelope. What if AI can function less as a cost-cutting mechanism and more as a capacity multiplier? Once this capacity is unlocked, it tends to be consumed very quickly.
The implication is that efficiency does not reduce the need for legal input - it simply broadens its application. Legal services extend into areas where the cost, time or friction previously made that involvement impractical.
The risk around wrong framing
If AI is approached purely as an efficiency tool, the response becomes defensive and the conversation centres on protecting margins, pricing faster work and maintaining our existing models. These are necessary considerations, but they are not sufficient in terms of strategy.
The more strategic question is where value sits once execution is no longer the constraint and firms that answer this well will expand into areas that were previously inaccessible. Those that do not risk optimising a model that is gradually becoming less relevant…
A shift in posture
This is not a call to abandon discipline or ignore risk. It is just recognition that risk also exists in under-reaching because in viewing AI only through the lens of cost pressure, organisations may overlook the opportunity to reposition their work more fundamentally.
This requires a shift from viewing legal demand as fixed, to recognising it as contingent - shaped by the ease with which organisations can access and deploy legal capability.
The direction of travel
AI does not reduce demand but simply reveals the gap between what organisations currently deliver and what they could be capable of delivering. For those willing to operate from a position of abundance, that gap represents opportunity but for those anchored in scarcity, it presents as pressure. The differentiator will be how it is interpreted, and how quickly this interpretation translates into action.
