Technology is starting to loosen some of the relationships professional services has relied on for years: between headcount and growth, hours and value and the amount of effort involved in a piece of work and what a client will pay for it.

Across six conversations in our recent Unlocking Value tech disruption mini-series, we heard different views on how quickly those changes will happen. But there was much more consistency around what they could mean for the way professional services businesses operate.

AI inevitably featured heavily, but the discussions ranged much further: how firms grow without simply adding more people, where expertise sits within the business, what clients will continue to pay for, how delivery needs to evolve and what happens to the commercial model when work that once took days can be completed in a fraction of the time.

The interesting question is not simply how much AI professional services firms will use. It is what kind of businesses they can build as some of the constraints that shaped the traditional model begin to change.

Six lessons stood out.

1. Saving time isn’t the same as improving the economics of the firm

There are already plenty of examples of AI making individual tasks quicker. Research can be completed faster, meeting notes written automatically, reports drafted more efficiently and a growing amount of project administration handled with much less human involvement.

All of that is useful, but there is a commercial question sitting behind it that firms will eventually need to answer: what happens to the time you have saved?

If 100 people each save two hours a day, what happens to those 200 hours?

They might allow the firm to take on more work without increasing headcount. They could create more time for business development or client work. They might allow the same revenue to be delivered with a lower cost base. In some cases, the work itself may change enough that the firm can offer something different altogether.

What doesn’t necessarily happen is that those individual productivity gains automatically appear in the P&L.

We heard examples during the series of firms grappling with exactly this question. The technology has made people more efficient but converting that efficiency into improved revenue or margin requires decisions about capacity, utilisation, roles and the way work is delivered.

Different firms will make different choices, but the important thing is to be deliberate about where that additional capacity goes. This becomes even more important once technology starts changing the work itself, rather than simply removing administration around it.

2. More of the value is moving from analysis to implementation

A considerable amount of consulting work has traditionally gone into getting to the answer.

Researching the market, gathering information, analysing data, identifying patterns, developing options and eventually arriving at a recommendation all take time. They also account for a meaningful part of what clients have historically paid for.

Technology is reducing the effort involved in some of that work; while also giving clients access to capabilities they previously needed external help to obtain.

That doesn’t remove the need for external expertise, but it does change where that expertise is likely to be most valuable.

Getting to an answer may become quicker. Knowing whether it is the right answer, understanding how it applies to a particular organisation and actually getting something to change are different problems.

We heard this described during the series as value moving further into implementation and execution. The analysis still matters, but the harder part increasingly comes after it: turning an answer into an outcome that moves the client’s business forward.

That could start to change the shape of consulting engagements. Rather than spending a large proportion of the project getting to a recommendation and handing it over, there is an opportunity to get to an initial answer more quickly and spend more of the engagement working alongside the client to put it into practice.

For firms whose value proposition has traditionally been weighted heavily towards analysis, that is worth thinking about now.

3. Bespoke doesn’t have to mean starting from scratch

Professional services firms are understandably cautious about standardisation. Clients have different circumstances; the problems are often complicated and much of the value of an experienced consultant comes from knowing when the standard answer doesn’t apply.

None of that means every engagement needs to begin with a blank sheet of paper.

If a firm has solved a similar problem 20 times, there should be something from those 20 experiences that makes the 21st engagement better. It might be a methodology, a diagnostic, a clearer way of scoping the problem, a delivery framework or simply a much stronger understanding of where the project is likely to go wrong.

This is where we think the discussion about productising professional services becomes useful, provided productisation isn’t confused with making everything identical.

The opportunity is to become much clearer about the problems the firm solves repeatedly and to build more of what it has learned into the way those services are sold and delivered. There will still be plenty of room for judgement and tailoring, but the consultant starts from the accumulated experience of the firm rather than reconstructing it for every client.

Apart from the obvious delivery efficiencies, that also makes a firm less dependent on particular individuals knowing how everything should be done.

Which leads to another theme that appeared repeatedly during the series.

4. Firms need to get more of their expertise out of people’s heads

Knowledge management is hardly a new challenge for professional services, but the potential value of solving it has changed.

Most established firms have accumulated an enormous amount of experience. The problem is that the useful parts of that experience are often spread across previous project files, methodologies, meeting notes and, most importantly, the memories of the people who did the work.

When somebody leaves, some of that knowledge inevitably leaves with them. Even while they remain in the firm, it can be difficult for everybody else to access what they know at the point when it would be useful.

AI creates some interesting possibilities here, but only if the underlying knowledge is available and sufficiently well organised to be used.

One of the ideas we discussed during the series was the possibility of making every consultant more like your best consultant: giving people access to the lessons, approaches and experience accumulated across the firm when they are scoping or delivering a piece of work.

We don’t think that means attempting to capture every piece of knowledge the organisation has ever created. The more useful starting point is probably to identify the expertise that genuinely differentiates the firm and the knowledge that repeatedly improves client outcomes.

If that still depends on knowing which partner to call, there is an opportunity to make it much more valuable to the wider business.

If knowledge becomes easier to reuse, experienced people can also spend more of their time applying judgement to the situations where it is genuinely needed, rather than repeatedly reconstructing knowledge the firm already possesses.

5. The commercial model will have to follow the changes in delivery

The relationship between delivery, pricing and value came up repeatedly across the six conversations. It’s a subject we’ve also explored in more depth in When time stops being the measure of value, looking specifically at what happens when the effort required to deliver the work is no longer a reliable basis for what a client pays.

Time has historically provided professional services firms and their clients with a relatively straightforward way of putting a price on work. If something requires five days of an experienced person’s time, both sides have a reference point from which to have the commercial conversation.

If the same task can eventually be completed in five hours, or five minutes, that reference point becomes less useful.

That doesn’t mean outcome-based pricing becomes the default. In many engagements, results depend on actions on both sides, so time and materials, fixed fees, retainers and hybrid models will continue to have a place.

What does become more important is understanding what the client is actually paying for.

If it is primarily the effort involved, then reducing that effort creates an obvious commercial problem. If it is access to expertise, a reduction in risk, a faster implementation or a measurable improvement in the client’s business, there is a different conversation to be had.

Professional services firms have spent a long time getting very good at measuring the inputs into their work. As the relationship between those inputs and the price becomes less predictable, understanding and demonstrating the value created on the other side becomes increasingly important.

6. Growth doesn’t have to start with the next new client

The final theme is one we think is particularly relevant for firms looking for more predictable growth.

Professional services growth strategies tend to devote a lot of attention to acquiring new clients. That’s understandable, but it can mean less attention is paid to what happens commercially once a client has been won.

A different way of looking at it is to map the problems a client is likely to face over a longer period.

Some problems genuinely need solving once. Others return periodically, perhaps because the organisation changes, new people join or another part of the business reaches the same point. And some create an ongoing need that lends itself naturally to a recurring service.

Understanding that journey doesn’t mean trying to manufacture another sale at the end of every project. The current work still has to create enough value for the client to want the relationship to continue.

If a firm can solve something valuable, demonstrate what changed and understand what the client is likely to need next, successful delivery becomes part of the growth model. It creates a much more natural route into the next project, an ongoing service or a broader relationship elsewhere in the organisation.

For firms that currently depend heavily on winning another new logo or finding another large project every year, there is a lot to be said for understanding how much more of their growth could come from clients who already know what they’re capable of.

What does this mean for the professional services model?

There are plenty of predictions being made about how quickly AI will change professional services. We don’t think trying to predict the exact pace of that change is particularly useful.

Across the six conversations, several of the assumptions that have underpinned the traditional professional services model kept coming into question.

The relationship between headcount and growth is changing, as is the relationship between hours worked and value created. Firms have more opportunity to reuse the expertise they’ve already built, to introduce greater repeatability into delivery and to think about the work they’re doing today as part of a longer client relationship.

There is a practical implication too. Technology is unlikely to compensate for an inconsistent operating model, fragmented knowledge or poor data. In many cases, it will make the need to address those things more pressing.

None of those changes requires professional services firms to abandon what has made them successful.

Clients will continue to value expertise, judgement, trust and people who understand their business. The opportunity is to build a better operating and commercial model around those things.

For us, that’s the more interesting question coming out of the series. Not how much AI professional services firms will use, but what kind of firms they can build as some of the constraints that shaped the old model begin to change.

Unlocking Value: The Tech Disruption Story explores these issues across six conversations with people working in and around professional services.

Featuring perspectives from Jason Soar, Jon Stead, Sri Ganesan, Sarah Edwards, Deb Ashton and Jonathan Corrie, the series explores everything from AI, delivery and pricing through to operating models, expertise and the future of professional services. 

Listen to the full series here.