Part 3: Rethinking pricing models for AI-augmented consulting

Consulting has always been a people business. We’ve grown by building smart teams, applying structured thinking, and delivering solutions and outcomes. And we’ve mostly priced that work in familiar ways:

• Fixed-price for a defined scope
• Time-and-materials when things are less clear
• Retained teams when the need is ongoing
• In some cases, outcome-based fees tied to impact

These models have served us well. They still do.

But the work itself is changing.

AI tools are starting to accelerate delivery. Team sizes will soon begin to shrink. Reusable IP and automation are playing a bigger role. The levers that once drove growth—hours, scale, headcount—are under pressure.

We’re not in a new era yet. But we’re moving toward one.

And the firms that want to keep growing profitably need to start adapting how they think about value, margin, and price.

Time, effort, and value: The old equation

Most pricing models in consulting rely on a simple equation:

Time × Effort × People = Value Delivered

That worked when most tasks depended entirely on human input. The more complexity, the more time and people required.

But AI changes this equation.

We’re starting to see tools that:

• Analyse documents in seconds
• Draft strategies and slides
• Synthesise research
• Generate and refactor code
• Map journeys, user flows, and test cases

That doesn’t mean people are out of the picture. But it does mean the relationship between effort and value is shifting.

The input might be smaller.

The outcome might be faster.

The impact might still be big.

That creates tension, especially when your pricing model is still tied to time.

And if the way we price is changing, the way we measure performance needs to change, too.

How our metrics need to change

When the way we deliver work changes, the way we measure it has to change too.

Most consultancies still track performance using the same core metrics: utilisation, average billing rate, project margin. These have worked well in a model built around hours and headcount. But when work gets faster, teams get leader, and tools take on more of the load, those numbers start to tell the wrong story.

Take utilisation. If a team finishes a task in half the time, the work still gets done—but on paper, they look underused. In reality, they were just more efficient.

Margins can get harder to read, too. A project might require fewer people or fewer weeks, but if pricing hasn’t changed, it can appear as though revenue dropped, even when the value delivered remained the same or increased.

As firms start to use more tools and reusable assets, revenue may come from different places: not just services, but subscriptions, fixed-fee access, or licensed IP. If we don’t track those separately, we miss what’s actually driving growth.

This doesn’t mean we throw out our old metrics. But we do need to look at them differently. That might mean:

• Tracking how fast we deliver, not just how many hours we use
• Measuring outcomes per team or project
• Separating service revenue from asset or tooling revenue

If your performance metrics don’t reflect how your delivery model is changing, you’ll misinterpret what’s really happening in the business—and make bad decisions as a result.

Why time-and-materials still works—for now

Let’s be clear: time-and-materials isn’t broken.

It’s a good model for agile delivery. It supports iterative work and flexible scope. It helps build trust through transparency.

Clients understand it. Teams can work within it. And if managed well, it can still be profitable.

But it’s also a model that assumes effort and duration are the main drivers of cost and value.

As delivery becomes faster and more AI-augmented, this starts to break down:

• Fewer hours doesn’t always mean less value
• Smaller teams don’t always mean lower impact
• Faster outcomes don’t always mean simpler problems

At some point, that disconnect becomes hard to explain—and harder to defend.

Fixed-fee and retainers: Still useful, still limited

Fixed-price models offer predictability. They work well for clear scopes and repeatable work. Retainers give clients flexibility and ongoing access.

But both depend on estimating time and effort accurately. And both carry risk, especially if the delivery model is shifting underneath them.

A project that used to take six weeks and six people might now take three weeks and three people, with the right setup. If you haven’t updated how you scope, staff, and price that work, your margin disappears fast.

Outcome-based pricing: Not new, but not yet mainstream

Some top consultancies have used outcome-based models for years, often in transformation, cost reduction, or performance improvement work.

The idea is simple: align your fee with the client’s result. If the project hits the agreed outcome, you earn more. If it doesn’t, you earn less.

It creates alignment. It builds trust. And it changes the risk-reward equation.

But it’s not easy:

• You need clear, measurable outcomes
• You need reliable ways to track impact
• And you need delivery models you can trust to perform

As AI makes delivery faster and more variable, this kind of pricing becomes more relevant, but also more complex. It requires discipline, data, and a high level of maturity on both sides.

Still, it’s the direction many clients want to go. And it’s one every firm should be ready for.

Where new value pools are emerging

As we move beyond selling time, we need to understand where new value lies.

It’s not just in advice or execution. It’s in the tools, systems, and ways of working we bring to the table.

This includes:

• Reusable AI agents
• Custom GPTs trained on client data
• Internal, custom toolchains that accelerate delivery
• Proprietary IP and frameworks
• Platforms that enable self-service or automation
• These assets aren’t people. They’re not time. But they create value—sometimes faster and more reliably than people alone.

And they open up new pricing levers:

• Licensing
• Subscriptions
• Usage-based access
• Bundled accelerators within fixed or outcome-based work

This isn’t about becoming a software company. It’s about recognising that value now comes from more than human effort.

How to protect margin without losing trust

When pricing shifts, trust can suffer, especially if clients feel the change is about protecting your margin, not serving their goals. That’s why transparency matters:

• Be clear about what’s human and what’s automated
• Show how speed and quality are still being maintained (or improved)
• Share how your delivery model is evolving—and what that means for scope, outcomes, and fees And above all, avoid the trap of selling AI as magic.

We’re still early. Most tools are powerful but imperfect. Human oversight is essential. Complex problems still need complex thinking.

But what’s changing is the speed and shape of that thinking—and the role tools play in it.

A path forward for profitable growth

So where does this leave us?

With a clear challenge—and a clear opportunity.

If you want to grow profitably in the age of AI, you’ll need to evolve both how you deliver and how you price.

That doesn’t mean abandoning the models that work. It means adapting them:

• Updating scopes to reflect faster delivery
• Creating hybrid models that bundle access, tools, and expertise
• Testing outcome-based structures where the value is clear
• Licensing IP or accelerators, where they create independent value
• Being open with clients about what’s changing and why

This isn’t about getting everything right overnight. It’s about starting the shift before it’s forced on you.

Because the firms that wait too long will find their margins eroding, and their value harder to defend.

Pricing is strategy

In a world where delivery is evolving, pricing isn’t just a commercial decision.

It’s a strategic one.

It shapes how clients see your value. It determines how your business scales. And it sets the tone for how you work, hire, and invest.

The old levers—people, time, scale—won’t go away overnight. But they will lose their power in time. Some might argue they already are.

The firms that succeed next won’t just deliver differently.

They’ll price differently, too.

And they’ll do it in a way that protects their margin, earns trust, and sets them up for long-term, AI-augmented growth.

Originally published on Linkedin pulse