AI labs eye the consultants they despise - and SA's professional services sector should take note

The Economist's Schumpeter column cuts to the heart of AI's existential commercial challenge: model-makers like OpenAI and Anthropic aren't yet generating returns that justify their valuations, so they're pivoting into consultancy — the very white-collar world their founders publicly disdain. Accenture, which has 30,000 staff training on Anthropic's Claude, has lost half its market value this year as investors question whether traditional consultancies survive the disruption. For South Africa, where the big four accounting firms and specialist strategy consultancies dominate corporate advisory work, the question is urgent: as AI labs deploy their own "forward-deployed engineers" directly into client organisations, what happens to the Johannesburg and Cape Town consulting model?.The Economist.From The Economist, published under licence. The original article can be found on www.economist.com© 2025 The Economist Newspaper Limited. All rights reserved..The most important question in financial markets can be put thus: will companies like JPMorgan Chase and Walmart find artificial-intelligence models useful enough to buy them at a price such that OpenAI and Anthropic can stay in business? If they do: rock ’n’ roll. If not, investors will tire of funnelling capital into the AI model-makers, thereby destroying confidence in the vast construction of data centres, and the semiconductors and gas turbines that power them, and so on into economic oblivion.Last year the answer was obvious, at least in Silicon Valley. The back-bending labour of office workers in the 21st century would soon go the way of the back-breaking tasks of the 20th. Which is to say it would disappear, but this time into computers rather than offshore: firms would buy tokens, not workers. The messianic confidence of tech bosses on this point has made them unpopular but not yet profitable. Partly it reflects their faith in the technology. But it also reflects a view of office work formed in the early 2020s, when tech firms hired vast numbers of paper-pushers whose emails, dashboards and coffee-chats their “technical” staff despised. Since then the “bullshit jobs” view of the world has simply given way to one about “bullshit tasks”.Yet the war on white-collar work has progressed far more slowly than techies anticipated. The information that constitutes modern companies is not easily organised and fed into AI models. The answers the models spit out are not easily acted on, either. How, for example, should a firm decide which tasks to automate? When should it use cheap open-source models rather than pricey cutting-edge ones? How should it calculate the returns on its investments? Can it hedge the cost of tokens? Answering these questions is arduous and possibly very lucrative work. Hence the idea—simple, elegant and brilliantly ironic—that model-makers should become much more involved in how their inventions are used. The bullish case works like this: companies get more out of AI; model-makers solve their existential cashflow problems; the world economy marches happily on.To destroy the consultant, then, become the consultant. Each of the AI labs has announced partnerships with big professional-services firms. OpenAI recently bought a small British tech consultancy. In May Anthropic and OpenAI both set up joint ventures with big private-equity houses, presumably hoping that AI models could turn around many software firms languishing in their funds. That private equity cannot sell what it owns is an existential concern for the industry; if things are as bleak even after the attention of the AI labs, it will be a concern for everyone.Bodies must be thrown at the problem, but how many and by whom? When big tech firms built their cloud-computing businesses in the 2010s, much of the grunt work was outsourced to Accenture, a multinational consultancy which grew enormous implementing the innovations of giants like Microsoft and Google in its client companies the world over. It has warm bodies in abundance, which it describes in the impenetrable language of the corporate central planner: 30,000 workers to be trained on Claude in “a major investment in talent, solutions, and go-to-market muscle”, it declared in December (just a small detachment of Accenture’s total corps of nearly 800,000 souls).The market does not believe Accenture will play the role of a cash-generating middleman this time. Its shares have lost more than half of their value this year. Perhaps investors are right. That said, snobbery is an underappreciated aspect of what firms choose to bring in house and what they leave in the marketplace: some at the top of the AI labs think a corporate culture that prizes individual genius is incompatible with hiring many thousands of unremarkable workers to plug their products into the economy. (Banks manage to combine star traders with huge back offices, though AI types are likely to find this analogy insulting, too.)Palantir is closer to what OpenAI and Anthropic might eventually build—and that firm’s share price has also collapsed recently at the thought. The crux of Palantir’s business is sending consultants into firms, sorting their data out and displaying it in a way that makes a middle manager feel as if he works at GCHQ. It is an impressive company, but also an impressive linguist. In its hands a firm’s data become its “ontology”. Consultants are elevated to the status of “forward-deployed engineers”. What distinguishes them from Accenture’s new “reinvention-deployed engineers” or OpenAI’s “forward-deployed experts”? Who knows, but pity any consultant who remains backward and undeployed.Which firms strike it rich telling companies how to use AI models depends to a large extent on whether model-makers develop a better understanding of the mind-numbing nuances of modern business than incumbent consultancies do of AI. Yet so far nothing the AI firms have done indicates the slightest understanding of how ordinary firms operate. Perhaps that is not surprising for an industry whose staff pride themselves on being incompatible with the bureaucratic corporate life.Model studentsWhether or not Silicon Valley’s AI labs become white-collar advisers, they have a great deal to learn from studying them. In investment banks, they will find instructive case studies on being hated and dealing with systemic risks: worryingly, popular mistrust is hard to dislodge and regulation generally only follows disaster. In elite law firms, they will observe the extraordinary longevity of small and focused companies. And in consultancies, there are lessons on expanding too much, as top firms like McKinsey have done in recent years, but also on the perils of making bold predictions about the future of capitalism. That is not a warning the masters of AI are likely to heed..Sign up for your early morning brew of the BizNews Insider to keep you up to speed with the content that matters. Register here.Support South Africa’s bastion of independent journalism, offering balanced insights on investments, business, and the political economy, by joining BizNews Premium. Register here.If you prefer WhatsApp for updates, sign up to the BizNews channel here.

AI labs eye the consultants they despise - and SA's professional services sector should take note

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