New Business Models for Consulting Firms: Tokenized, Knowledge-Based, and Co-Created
Imagine this: an analysis that once took three consultant-days now takes two hours with AI support. The result is better, and client satisfaction is high. And yet: how do you bill for it? Two hours at the same day rate produces a number that looks absurd to the client, and one that does not truly compensate you for the methodology applied and the knowledge built over years. The classic model, which trades knowledge and time for money, no longer fits.
Consulting firms are at a crossroads. Gartner describes a fundamental shift in the over-6-trillion-dollar professional services industry: away from selling time, towards guaranteeing results. By 2028, Gartner predicts that 30 percent of what B2B software provides today will be replaced by providers delivering complete business outcomes as AI-automated services. Firms that wait until their model breaks before adapting will have waited too long.
The classic consulting model monetises presence, not impact. Hours are sold, not change. That was tolerable as long as analysis and preparation genuinely required time. But AI accelerates exactly those steps. Tasks that once took ten hours now take two. Apply the same hourly rates and revenue shrinks. Raise rates and the number becomes hard to justify to clients. The model is caught in a bind from which no optimisation offers a way out. Transformation is what is needed.
Consulting has never really sold time. It has sold knowledge, trust, and the capacity to drive change. These values can be repackaged into models that work with the AI reality instead of against it. Three directions are becoming clear.
Tokenized: Pay-per-result, not pay-per-hour. The tokenised model transfers the logic of API billing to consulting services: you pay for the outcome, not for the hour in which it was produced. Gartner noted in 2026 that cost-per-result tokenisation creates a competitive advantage for AI-driven providers. For consulting firms, this means pricing tied to outputs: answered queries, developed concepts, completed analyses. The methodology behind them remains the firm's intellectual property. How long it takes internally stops being a factor.
Knowledge-based: knowledge as an asset, not as availability. A firm that curates, structures, and makes its expertise available as an always-on system builds an asset rather than a service. The key step is turning implicit knowledge, proven approaches, decision principles, sector-specific experience, into a form that scales without multiplying the person. An AI agent built on this curated knowledge can answer baseline questions around the clock and frees the consultant for work that genuinely requires human judgement. The human stays at the centre; the AI amplifies, it does not replace.
Co-created: continuous instead of project-based. The third model moves away from project logic. Instead of delivering one-off outputs, consultants build alongside their clients, iteratively, data-driven, in continuous partnership. Knowledge flows in both directions. Clients develop internal capability; consultants deepen their sector expertise. The kind of client loyalty that a one-off project rarely achieves emerges almost naturally; the value proposition goes far beyond handing over a report. One concrete example of this model is the Orange Butterfly Reisepass: continuous support rather than one-time consulting. Firms combining subscription, usage, and outcome components report more than double the margin improvement of those using purely time-based billing.
In practice, it might look like this: an HR consultant with fifteen years of experience has built her methodology across dozens of projects. Today she supports twenty clients, not through twenty parallel engagements, but with a curated AI agent based on her verified knowledge that handles 80 percent of recurring questions autonomously. She is brought in when something sensitive arises or when a decision genuinely requires experience, and always with the full context of the conversation so far. Billing is per interaction unit, not per hour of availability. The result: greater reach, more stable income, and, somewhat surprisingly, more time for the conversations that truly matter.
Consulting firms that do not adapt their business model will not lose because of inferior advice. They will lose because competitors build a stronger knowledge foundation. The transformation starts with one decision: treating knowledge as an asset, not as an attendance obligation. At thinking services, we started this journey with ourselves and we help consulting firms take it too.
Frequently asked questions about new consulting business models
What does "tokenized" mean in the context of consulting firms?
Tokenized consulting means billing not by the hour, but by outcome or interaction, similar to API pricing in the software world. Instead of "8 hours of analysis" you invoice "1 strategy assessment". This decouples revenue from personal availability and makes the pricing model independent of how fast AI completes the work.
What distinguishes a knowledge-based model from classic products like handbooks or frameworks?
A handbook is static: it becomes outdated, sits in a drawer, and is never available exactly when needed. A knowledge-based model is dynamic: the knowledge is curated, continuously updated, and queryable as an AI agent at any time. Rather than "here is the document, please read it", every question gets a direct, source-backed answer in the context of the specific situation. That is the difference between knowledge as a publication and knowledge as infrastructure.
Do I lose control as a consultant when an AI agent communicates my knowledge?
No. When the model is set up correctly, you gain control. You decide which knowledge is curated and released. The AI agent only responds based on this verified knowledge and flags gaps as gaps rather than inventing answers. For sensitive or complex queries, the human expert is brought in directly (human-in-the-loop). Quality control stays with you.
How do you start building a knowledge-based consulting model?
The first step is curation, not technology. Identify which questions your clients ask repeatedly and which answers from your experience are truly reliable. Structure that knowledge: context, decision rules, typical exceptions. Only then build the agent on top of it. Curating knowledge matters more than collecting it: a structured foundation of 50 high-quality entries beats 5,000 unsorted notes.
Is co-created consulting compatible with existing client contracts?
Usually yes. Co-created consulting often starts as an extension of an existing mandate: instead of "we deliver the report by Friday", you agree "we build this together over the quarter". The fee structure shifts from project lump sums to retainers or hybrid models with a subscription component. Many clients welcome this, because it gives them continuous support rather than episodic interventions.
The human stays at the centre — AI amplifies, it never replaces.