Artificial intelligence is fundamentally challenging the consulting industry's traditional business model, particularly its reliance on billable hours and junior consultant hiring pipelines [1]. According to KPMG's global head of consulting Svilena Tzekova, the intellectual property and knowledge that historically formed the basis of consulting work are becoming increasingly accessible to clients, who can now obtain advice quickly through AI tools that previously took consultancies days or months to deliver [1]. Tzekova stated: "Anyone can go and very quickly get to the level of advice that we used to deliver within whatever days or months at times. We were making quite a lot of money by providing advice. I think that part of our business is literally nonexistent anymore" [1].
The industry faces a critical transition in pricing models as clients increasingly demand outcome-based compensation rather than time-and-materials billing [1]. However, procurement departments continue to compare consultancies based on headcount and hourly rates, creating a disconnect between client preferences and purchasing practices [1]. Additionally, AI introduces new cost structures that firms must incorporate into their pricing equations, including computing power expenses and fees from AI providers based on text processing volume, alongside traditional employment costs [1]. Tzekova acknowledged the challenge: "It's very difficult to be able to arrive at a commercially sensible outcome-based pricing model. Largely, firms are still working out the equation, and that will take some time" [1].
Smaller, AI-native consultancies are positioning themselves to capitalize on this disruption as the Big Four firms—Deloitte, PwC, EY, and KPMG—race to modernize [1]. Elixirr, a London-based challenger consultancy, argues that firms like theirs have a competitive advantage because they have never relied on time-and-materials billing [1]. According to Elixirr's head of investor relations Emiko Caerlewy-Smith: "AI is amplifying and exaggerating the way that we were already trying to show up to the market. Clients will pay for fixed deliverables, fixed outcomes and value. They really shouldn't be caring about the amount of time it takes to create the inputs to create the outcome" [1]. This structural advantage suggests that consulting's traditional giants may face margin pressure and talent pipeline challenges as the industry shifts toward outcome-based models.
CONCLUSION
AI is fundamentally reshaping consulting economics by making traditional advisory work commoditized and forcing a transition from billable hours to outcome-based pricing [1]. While established firms struggle to reconcile client demands for value-based compensation with existing procurement practices and new AI-related costs, smaller AI-native consultancies are better positioned to thrive in this new environment [1]. The industry's inability to quickly resolve pricing models presents both a challenge to traditional consulting margins and an opportunity for disruptive competitors.