AI isn’t just changing how work gets done. It’s changing how clients expect to pay for it. The traditional time-and-materials (T&M) pricing model, long the default in professional services, is increasingly misaligned with the efficiency and flexibility AI enables.
Professional services leaders agree. Harvard Business Review says firms must evolve their business models, and industry leaders are openly declaring the T&M model obsolete. And while the shift to value-based pricing has been forecasted for years, AI is turning that slow evolution into a fast-moving imperative.
In our conversations with innovation leaders across B2B services, the message is clear: AI is eroding the rationale for T&M pricing.
One executive in the HR advisory space shared that their firm is already adjusting consulting targets based on aggregate AI productivity gains—without changing billable rates (yet).
A global legal services firm told us flatly: “Time and materials is dead.”
Consulting partners are piloting engagements where deliverables are enhanced by AI, not just performed faster, and billing based on value delivered, not hours logged.
Why now? Because AI is accelerating delivery without always reducing perceived value. Clients are beginning to ask: “If your team is twice as fast, why are we still paying by the hour?”
So how can B2B Professional Services firms transition away from time-based pricing without eroding trust or margin?
Start by measuring the impact of AI tools on:
Realization rates: Are engagements closing faster but at the same price?
Utilization unlocks: Are consultants freed up to take on more work?
Profit per engagement: Is automation enabling higher margin without discounting?
By tracking these indicators, you can build the financial case for a pricing model that reflects outcomes, not just effort.
Don’t overhaul your entire pricing structure overnight. Instead:
Identify a high-trust client with recurring needs
Define clear deliverables and success metrics
Introduce fixed or tiered pricing based on those outcomes
Pair this with AI-enhanced delivery (e.g., faster research, better recommendations, co-created deliverables) and demonstrate how the value proposition is evolving.
Clients don’t care if a deliverable took 20 hours or 5. They care about the results. Train client-facing teams to:
Shift language from “we’ll spend X hours” to “we’ll deliver Y result”
Frame AI as a capability, not just a cost-saving
Emphasize partnership over production
Making the pricing shift is complex. Here are pitfalls to watch for:
Overselling efficiency: If clients think AI makes everything instantaneous, they’ll expect steep discounts. Be transparent about where humans still add value.
Ignoring culture: Billing models shape team behaviors. Moving to fixed fees without adjusting incentives can backfire.
Skipping experiments: Pricing innovation requires iteration. Use test-and-learn cycles like you would with any new product.
It’s time to rethink not just how you deliver services, but how you price them. If you're experimenting with AI and want to align your pricing model with your value model, we can help.
👉 Talk to us about reimagining your pricing model