AI, pricing and the slow unravelling of the time-and-materials model in Marcomms.
For years, Agency pricing has been under strain. Margins have tightened, procurement pressure has intensified and delivery models have grown more complex. AI has not caused those issues but it has accelerated them and made them harder to ignore.
Our conversation with Derric Ciccone and Tracey Shirtcliff gets to the heart of why traditional time-and-materials pricing no longer reflects how agencies actually create value, and why incremental tweaks will not be enough.
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About our Panel
Derric Ciccone – CFO, Omnicom: Derric has extensive experience across finance, commercial strategy, M&A and business transformation and during his career has worked with WPP, Publicis and now Omnicom. He’s known for his ability to bridge creative and commercial priorities – combining financial rigour with a forward-thinking approach to technology, data and operational excellence.
Tracey Shirtcliff – CEO & Founder, SCOPE Better: With over 20 years’ experience working with the industry, Tracey brings real-world insight and innovative thinking to a space often overlooked – transforming pricing from a pain point into a competitive advantage. SCOPE Better is an award-winning platform revolutionizing how creative agencies price and scope their work.
The Key Takeaways
How AI has exposed agency economics
A recurring theme throughout the discussion is that agency pricing models are now structurally misaligned with the work being delivered. Agencies are building faster, more sophisticated and more integrated solutions, yet pricing is still anchored to a logic that assumes value is created through hours worked.
As Derric puts it, agencies are investing heavily beneath the surface:
“We’re building infrastructure, we’re building orchestration layers that are helping us do work faster. And yet the models still aren’t changing.”
AI speeds up execution, but the work has not become simpler. In many cases it has become harder — requiring new skills, new governance, new tooling and new operating disciplines. Pricing models that treat speed as efficiency gains miss that reality entirely.
The persistence of time and materials and why it no longer fits
Despite years of debate, most agencies remain anchored to time-based pricing. Tracey highlights just how dominant the model still is:
“Still 70% of businesses in the agency space are based on time and materials.”
That creates an immediate contradiction once AI enters the workflow. If delivery becomes faster, the client expectation is predictable:
“If we’re speeding up the work that’s being done, the expectation from clients is that the billable hours come down.”
What disappears from that conversation is the growing cost base required to enable that speed in the first place.
Overhead has fundamentally changed but pricing has not
Agency overhead used to be relatively stable. Offices, core systems and people costs could be absorbed and smoothed through multipliers. That is no longer the case.
Today’s overhead include compute data, bespoke AI integrations – orchestration layers that evolve continuously. Derric is clear that this is not a temporary spike:
“In order to bring these ecosystems to life, it takes a ton of compute data, a ton of partnerships, and a ton of orchestration, and that isn’t going to stop.”
Treating these investments as background costs rather than core infrastructure creates a widening gap between how agencies operate and how they charge.
Fewer hours, rising complexity, the internal reflex problem
One of the most damaging dynamics discussed is internal rather than client-driven. When AI reduces visible delivery time, agencies often default to discounting.
Derric describes the reflex clearly:
“People see fewer hours and immediately think it should be cheaper, without understanding what it actually takes to deliver the outcome.”
This behaviour locks agencies into a defensive posture before value has even been articulated. Speed becomes a liability rather than an asset.
AI is not a tool cost, it is an operating system
The discussion strongly rejects the idea that AI should be priced like a line-item tool or passed through transparently on a project-by-project basis.
Clients are not paying for access to ingredients. They are paying for judgement, integration, orchestration and outcomes. AI increasingly sits at the centre of that system.
Which leads to a more fundamental conclusion:
“Foundationally, we’re built on this tool. No matter what, you have to buy into the tool.”
Productisation, not ‘charging for AI’, is the real shift
Tracey is explicit that the answer is not simply adding AI surcharges. The real commercial shift is productisation.
“Agencies need to move to a productised approach, bundling time, tools and expertise into packaged products.”
Productisation changes the economics of agency work. It reduces reset costs, allows learning to compound and creates scalable value rather than bespoke reinvention.
As she explains:
“Instead of starting from scratch every time, you get revenue scalability because you have a set of products you can use.”
AI enables this shift, but it is the packaging and repeatability that unlock margin improvement.
Language is shaping the wrong commercial conversations
A subtle but powerful insight is that agencies often undermine themselves through the language they use.
Tracey summarises the issue:
“We talk about cost when we should be talking about price. We talk about hours when we should be talking about results.”
Language anchored in inputs invites procurement-led scrutiny. Language anchored in outcomes supports commercial partnership.
The future pricing model is layered, not binary
Neither speaker argues for abandoning time and materials entirely. Instead, a layered model begins to emerge:
- A foundational AI or platform layer that underpins delivery
- Productized outputs tied to outcomes and value
- Selective time and materials for genuinely bespoke or overflow work
As Derric notes:
“Time and materials doesn’t have to be all or nothing.”
The shift is about what sits at the core of the model, not eliminating flexibility altogether.
This is an internal transformation before it is a client one
Perhaps the most important takeaway is that pricing reform is not primarily blocked by clients. It is blocked internally.
Fear of disrupting long-term contracts, lack of shared output metrics and ingrained habits all slow progress. Until agencies align finance, client service and leadership around a coherent value story, change will remain incremental.
AI has made the gap impossible to ignore. The question now is whether agencies continue to price for hours, or begin pricing for the systems and outcomes they are already delivering.
