KPMG executive says AI is eroding paid advice as firms rethink fees and training

KPMG’s global consulting chief says AI has made advice that once earned substantial fees readily accessible. In interviews published by CNBC on November 12, executives at KPMG, EY and Elixirr describe the resulting pressure on how firms charge—and how junior employees learn when software takes over some of their foundational work.

Svilena Tzekova, KPMG’s London-based global head of consulting, told CNBC that clients can now quickly obtain advice that previously took consultants days or months to deliver. The knowledge and intellectual property underpinning that work are becoming more accessible, she said, raising expectations of what consultants should provide.

We were making quite a lot of money by providing advice. I think that part of our business is literally nonexistent anymore.

Svilena Tzekova, KPMG’s global head of consulting, speaking to CNBC

The commercial response is less settled. Clients increasingly want to pay for measurable outcomes, Tzekova said. Yet their procurement departments still compare proposals using the number of people assigned to a project and their hourly rates. That leaves firms negotiating results-based work through a purchasing process still focused on staffing and time.

AI also adds expenses beyond salaries. Computing power and provider charges based on how much text models process must enter the calculation, Tzekova said. Firms are still working out how to turn those costs into commercially sensible outcome-based prices; she cautioned that reaching an answer will take time.

Elixirr’s head of investor relations, Emiko Caerlewy-Smith, offered a different starting point. She said the London-based consultancy has never charged on a time-and-materials basis, meaning fees tied to staff hours. Instead, it charges for fixed deliverables, outcomes and value. In her view, clients should care about the result rather than the time spent producing its inputs.

She also described a shift from recommending changes to building working systems. Elixirr recently helped a global insurer develop an AI-based motor insurance platform, she said. Her account illustrates the kind of implementation work she says clients now seek, rather than advice alone.

Internal preparation remains part of that transition. Caerlewy-Smith said Elixirr spent six months getting its data into a format its AI models could fully use. She argued that smaller firms can move faster than much larger rivals, questioning how long comparable preparation would take at an organization employing tens of thousands of people.

The staffing question reaches beyond pricing. Research, data analysis and presentation production have traditionally given new consultants entry-level work; CNBC describes those tasks as increasingly open to automation. Claire Trachet, founder of advisory firm Trachet, said AI helps junior employees work faster, but questioned how they develop professional judgment without doing foundational work themselves.

In auditing, that shift includes checking figures against source documents. EY’s global assurance innovation and digital leader, Paul Goodhew, told CNBC that AI can perform the first preparation of this verification work for an audit professional. He also described new roles EY is developing:

• Data delivery professionals who prepare data for audit teams.
• Product managers who help develop technology platforms.
• Specialists who understand clients’ technology strategies and risks.

Tzekova rejected eliminating graduate recruitment as the answer. Instead, she said junior consultants will need to take more responsibility earlier, adding that some graduates and junior employees already rank among KPMG’s strongest contributors to its new way of working. Caerlewy-Smith stressed the urgency of moving employees into other tasks, arguing that the economics of traditional staffing pyramids otherwise no longer work.