AI and the big question: why would you ever call McKinsey or Gartner?

For many years, McKinsey has been the go-to firm for advice and Gartner for research but, with AI, why bother? In fact, there is a lot of debate about whether AI will replace consultants and research firms such as McKinsey and Gartner. The thing is that this conversation misses the bigger change.

What’s that?

It is that AI will not destroy these companies.

AI does destroy the economic model that made these companies rich, however.

For decades, consultants sold expensive human labour wrapped around scarce knowledge, while research firms collected information, analysed markets, compared companies and packaged their conclusions into expensive reports.

AI turns that model upside down because knowledge is abundant, research is instantaneous and much of the analysis, benchmarking, modelling and presentation work that justified armies of junior consultants is automated.

This is why the consulting pyramid gets crushed from the bottom upwards.

The analysts doing research and building slides are hit first, followed by the consultants performing analysis and eventually much of the work undertaken by engagement managers. The partners survive because CEOs are not paying millions simply for information, but for judgement, relationships, influence and someone credible enough to stand beside them in front of the board when difficult decisions have to be made.

AI makes knowledge cheap and judgement expensive.

Research firms face an even bigger challenge because why would I buy a sixty-page report when I can interrogate the research?

Gartner's Magic Quadrant needs to become a Magic Conversation, where I tell its AI everything about my bank and ask which suppliers fit my strategy, architecture and budget, which implementations failed, what comparable banks discovered and which three vendors I should meet tomorrow.

The irony is that McKinsey, Gartner and their peers possess exactly what is needed to build incredibly powerful AI systems because they have decades of proprietary research, benchmarks, methodologies and experience, but turning that knowledge into AI also cannibalises the business that created it.

If AI can accomplish in an afternoon what ten consultants previously spent twelve weeks producing, clients will soon question why they are still paying twelve-week consulting fees.

But the biggest disruption might not happen inside consulting at all … it could happen inside the banks.

Banks already possess extraordinary amounts of knowledge spread across board papers, strategies, technology architectures, risk reports, regulatory submissions, customer data, vendor contracts, project reviews and decades of consultant reports, but that knowledge is fragmented across departments and disappears as executives leave, teams reorganise and documents sink into SharePoint.

AI can turn all of that into something banks have never possessed before: institutional intelligence.

Imagine a bank AI that remembers every acquisition, transformation programme, technology failure, regulatory problem, customer initiative and strategic decision the organisation has made, while continuously combining that history with external information about competitors, markets, regulation and technology.

Instead of hiring consultants for three months to discover why something happened, management can ask the bank itself.

That changes consulting completely because McKinsey stops being the source of the answer and becomes the challenger to the answer. The bank no longer needs fifty consultants to tell it what it already knows, but it might pay handsomely for three exceptional people who can challenge its institutional AI, bring knowledge from outside the organisation and tell the board where its machine is wrong.

The institutional AI then evolves from memory into adviser because it can identify patterns management has missed, challenge assumptions in investment proposals, compare forecasts with previous failures and warn that the bank is about to repeat a mistake it made ten years ago.

Eventually every board proposal could arrive with two views: what management thinks and what the bank thinks. This creates a far more interesting space than whether AI replaces consultants because, once the institutional intelligence becomes powerful enough, someone has to decide who it works for, who controls what it knows, who can override it and whether the board, shareholders, auditors and regulators should be able to see conclusions management would rather ignore.

For centuries banks accumulated capital and data. AI allows them to turn their history, knowledge, decisions and mistakes into institutional intelligence that never leaves the company.

That leaves McKinsey, Gartner and the rest of the professional services industry with a rather uncomfortable question:

What can you tell my bank that my bank doesn't already know?