Consulting firms trade hourly fees for AI risk-sharing

The shift toward outcome-based fee structures marks a departure from standard consulting models. In these arrangements, firms receive a minimum base payment, with the remainder of their compensation contingent on specific gains such as efficiency improvements, cost savings, or stock-price targets. This transition is largely driven by the inherent instability of AI integration, where the return on investment remains difficult to forecast.

Bret Greenstein, chief AI officer at West Monroe, notes that the transformational nature of AI makes it a moving target, prompting clients to demand more accountability. Major players are responding to this pressure by reorganizing their internal operations. Firms are deploying proprietary generative AI tools—such as McKinsey’s Lilli or BCG’s Deckster—to automate manual tasks, effectively allowing smaller teams to deliver complex results faster. Consequently, clients are questioning the necessity of large, long-term engagements that were once the industry standard.

These changes are already taking hold at the highest levels of the sector. Christoph Schweizer, CEO of BCG, confirmed that three-quarters of the firm’s largest AI engagements now operate under variable-fee structures. While outcome-based billing is not entirely new to the consulting world, the speed and scale of AI implementation have turned it into an industry necessity. Firms now face a dual challenge: they must prove their value in a market where AI-enabled efficiency could naturally drive down traditional project costs, all while putting their own revenue at risk to win over skeptical clients.