How AI is changing consulting fees and graduate hiring

Artificial intelligence is challenging the building blocks of the consulting industry, from the fees firms charge clients to the armies of graduates who have traditionally powered its business model. 

Svilena Tzekova, KPMG’s London-based global head of consulting, agreed that the industry is changing. The intellectual property and knowledge that once formed the basis of consulting work are becoming increasingly accessible, she said, so clients have higher expectations than ever before.

“Anyone can go and very quickly get to the level of advice that we used to deliver within whatever days or months at times,” Tzekova told CNBC. “We were making quite a lot of money by providing advice. I think that part of our business is literally nonexistent anymore.”

But the industry has yet to work out exactly how to charge for this new kind of work. Although clients increasingly say they want to pay for outcomes, their procurement departments still tend to compare consultancies on the number of people assigned to a project and their hourly rates, Tzekova said.

AI is also introducing new costs that firms need to factor into their pricing models, including computing power and the fees AI providers charge based on how much text their models process, alongside the traditional costs of employing people, she said.

“It’s very difficult to be able to arrive at a commercially sensible outcome-based pricing model,” Tzekova said. Largely, firms are still working out the equation, and that will take some time, she said.

Smaller, AI-native consultancies hope to gain a competitive advantage as the likes of the Big Four — professional services giants Deloitte, PwC, EY and KPMG — race to modernize.

Emiko Caerlewy-Smith, head of investor relations at London-based challenger consultancy Elixirr, argued that firms like hers are better positioned for the AI era. She said they’ve never billed clients on a time-and-materials basis, which means charging for the hours staff spend on a project.

“AI is amplifying and exaggerating the way that we were already trying to show up to the market,” Caerlewy-Smith told CNBC. “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.”

Clients now want consultancies to help them build solutions, she said, not just advise them on what to do. In one recent project, Elixirr helped a global insurer build an AI-based motor insurance platform, Caerlewy-Smith said.

Another advantage smaller consultancies may have is the speed of adopting AI internally. Elixirr took six months to get its data into a format that could be fully used by its AI models, Caerlewy-Smith said, questioning how long the same process might take at a company employing tens of thousands of people.

“The issue they have is that they are enormous and we are nimble,” she said.

Another element of the consultancy business model is being questioned: its graduate recruitment pipeline.

The industry traditionally hires thousands of graduates from universities each year, setting them on a career ladder that often begins with entry-level tasks that can now be largely automated: research, data analysis and producing presentations. 

Claire Trachet, a former Deutsche Bank mergers and acquisitions banker turned founder of London-based advisory firm Trachet, told CNBC that AI is helping junior employees do their jobs faster. But she questioned how they would gain the experience needed to progress if they no longer have to do the foundational work themselves. 

Some are also questioning why they should put in long hours on tasks that AI can complete with a click of a button, she said.

“The problem is you can’t form your judgment, your intuition,” Trachet said. “Your professional sound judgment is built through reputation. It’s a craft. The ones who will stand out later will be the ones who own that for themselves.”

Large established firms are responding by rethinking how they develop their people. Paul Goodhew, EY’s London-based global assurance innovation and digital leader, said AI is already changing the work traditionally done by junior auditors, such as checking figures against source documents.

“The traditional view of the auditor was someone, particularly a junior auditor coming into the profession, who would be spending a lot of their time doing manual ‘ticking and tying’ at work,” Goodhew told CNBC, referring to the process of verifying figures.

“Now today, AI is bringing about the potential that AI can actually do the first preparation of that work on behalf of the audit professional.”

EY is also developing new roles, including data delivery professionals who prepare data for audit teams, product managers who help develop technology platforms, and specialists who understand clients’ technology strategies and risks, Goodhew said.

KPMG’s Tzekova said the answer for firms isn’t to get rid of graduate recruitment altogether. Instead, junior consultants will need to take on more responsibility much earlier in their careers as the traditional shape of consulting firms evolves. Some of KPMG’s graduates and junior employees are already among the best and brightest at driving the firm’s new way of working, she said.

But traditional consulting firms need to redeploy their employees to other tasks quickly, Caerlewy-Smith said.

“We just need them to do other things, otherwise the economics of the pyramid models don’t work anymore,” she said.