Will AI disrupt time-based models in consulting?
I recently flat-out rejected a so-called value-based consulting offer for being too intrusive, too greedy, and too vague on what exactly I was paying for.
Pundits claim that AI will disrupt consulting services and force the industry away from time-based models towards value-based models. The challenge of old-fashioned time-based models is that the only possible path forward is growth. Growth in number of billable hours and growth in prices. However, with AI tools, many of the tasks that have previously been billable hours are now solved by machines in seconds or minutes.
The shareholders therefore have a problem to solve: when the number of billable hours per project goes down, and prices cannot be increased to compensate for this reduction, revenue goes down. That means value per share goes down. The claim is that new revenue models will have to be designed to counter the apparent death of time-based fees.
Let’s first explaine the terminology used:
Time-based: The client pays for the hours worked, regardless of outcomes or value delivered.
Value-based: The fee reflects the perceived or realised value created for the client, rather than hours worked or milestones met.
Outcome-based: The client pays only when specific, pre-agreed, measurable results are delivered.
The latter two terms are partly overlapping. Outcome-based is a subset of value-based thinking, but more contractually precise. Value-based is a pricing philosophy whereas outcome-based is a contractual mechanism.
The billable hours trap
The problem is, though, that the need for change in the consulting industry's fee models is not driven by the clients, but by the consulting company partners'/owners' own desire for growth. Call it the billable hours trap. Revenue per project falls when AI does what juniors used to do. You cannot compensate with higher rates because the market won't bear it. So you need a new story. Value-based pricing is that story.
The clients have a different agenda
The clients, on the other hand, see this as an opportunity to reduce costs through reduced number of hours billed. They also want reduced risk of scope creep and increased financial predictability. Finally, this is also an opportunity to challenge the not very popular, but very common, project team organisation with multiple juniors per experienced resource.
A playground for expensive contract lawyers
The industry responds with attempts at "innovative" models, mostly variations over value-based pricing. In some domains, such as M&A advisory, equity raising, executive search, and purchasing, the market is already operating with fee models tying the fee directly to the actual outcome. The particular characteristic of these domains is that the outcome is unambiguous, attributable, and measurable within a defined timeframe.
However, for the majority of typical consulting projects, the value created and the outcome are not easily and indisputably attributable to one specific element. In most organisations, there are several ongoing initiatives at any point in time to improve or change operations. Market fluctuations may cause additional unforeseen shifts.
Value-based models require precise upfront agreements on scope, baseline definition, causality, KPIs, measurement methods, and time horizon. Both sides have incentives to game the scorecard once defined. Consultants may focus narrowly on measured outcomes at the expense of unmeasured ones. Clients may manipulate reported metrics. Do you see the potential legal battles lining up?
Once the market experiences the complexities of value-based models, the sales cycle and negotiation complexity will increase, with additional costs of both sides.
In the EU and EEA, public procurement rules add a further structural barrier. Directive 2014/24/EU requires contract value to be specified upfront, making pure outcome-based and success-fee models legally problematic or outright prohibited above directive thresholds. For organisations where a significant share of consulting spend goes through public procurement, this is a hard legal constraint.
The real winners may well be the contract lawyers.
So where does this leave us?
With the exception of domains where the outcome is unambiguous, attributable, and measurable within a defined timeframe, time-based models will remain a dominant approach, variably modified with a risk-reward bonus where reduced risk is swapped for premium fee. That's old news, too.
Due to the general availability of AI tools, consulting companies now have to deliver value at a much more demanding level, solving more complex problems. The clients are not willing to pay significantly more per hour, and as supply is higher than demand, there will always be another company willing to lower their prices. Hence, significant price increases are off the table.
Before you sign a value-based or outcome-based consulting contract, ask three questions:
What is the baseline?
Who verifies the outcome?
What happens if your own organisation fails to implement?
If the answers are vague, conflicting with other internal initiatives, or ambiguous, you are buying yourself a time-based fee contract with a premium price tag and a legal battle attached.
The time-based model is vibrantly alive. It has only got a few new skins. AI may reduce the number of billable hours spent on old tasks, but it will also create a whole new set of problems for consultants to solve.
Want to explore what AI means for your organization?
I work with leaders, boards, and organizations through keynotes and consulting around AI strategy, responsible adoption, business transformation, and the practical consequences of technological change.
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About the author
Elin Hauge is a keynote speaker, AI strategist, and trusted advisor to business leaders and boards. She specialises in helping organisations make sense of artificial intelligence beyond the hype, connecting technology to strategy, governance, and real-world value. With a multidisciplinary background in physics, mathematics, business, and law, Elin brings both analytical rigour and practical perspective. Her talks and advisory work empower leaders to ask better questions, make wiser decisions, and navigate AI with confidence.
Frequently Asked Questions
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AI is likely to reduce the number of billable hours required for many traditional consulting tasks, especially work previously done by junior consultants. However, hourly fee models are unlikely to disappear entirely. In many consulting projects, value and outcomes are difficult to define, attribute, and measure precisely.
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Consulting firms may turn to value-based pricing because AI can reduce the number of billable hours per project. If firms cannot compensate through higher hourly rates, they need alternative ways to protect revenue and growth.
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Outcome-based consulting contracts require precise agreement on scope, baseline, causality, KPIs, measurement methods, and time horizon. In complex organizations, outcomes are often influenced by multiple initiatives, market movements, and client-side implementation, making attribution difficult.
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Value-based or outcome-based pricing works best when the outcome is unambiguous, attributable, measurable, and tied to a defined timeframe. Examples may include M&A advisory, equity raising, executive search, and purchasing, where success criteria are often clearer.
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Clients should ask: What is the baseline? Who verifies the outcome? What happens if the client organization fails to implement? If the answers are vague or ambiguous, the contract may create more risk than value.