Hello and welcome to Eye on AI. In this edition…Nvidia sees $1 trillion in AI chip sales by the end of 2027…Meta delays the debut of its latest AI model (again)…Moonshot AI develops a new architecture for large neural networks…and why we may soon be worrying about ‘moral crumple zones.’ Since the advent of ChatGPT in November 2022, one of the professions that people often claim is now toast is consulting. After all, what is it that consultants do? They advise companies on strategy; they help them restructure their businesses to create new organizational designs and processes, often with the help of technology from third-party vendors; and they act as providers of outsourced services, or at least conduits to outsourced services, such as customer support or software development. Well, a frontier AI model can offer strategic advice. It can also advise on how to restructure an organization and about which software to buy. AI agents can actually help stitch some of those systems together too. Finally, AI agents can also now handle coding and customer support. So it’s lights out for consultants, right? Well, it hasn’t turned out that way so far. AI companies have discovered that they need consultants, or “systems integrators” as they are sometimes called in the software world, to help them sell their AI agents, as a story in last week’s Wall Street Journal highlighted. The reason is that using AI agents effectively often requires quite a lot of organizational transformation—cleaning up data, redesigning workflows, and thinking about how to redeploy human workers—as well as strategic thinking about how AI might be used to provide a real competitive advantage. The AI model vendors have found they don’t have the resources to provide this kind of advice at scale—OpenAI only has about 70 so-called “forward deployed engineers” who go on site with customers to help them implement solutions based on their AI models; Anthropic is thought to have a similar number. And while it is possible that AI itself could serve this function, AI still suffers from a trust deficit—most boards would still rather put their faith in advice from McKinsey or BCG than ChatGPT. (A more cynical take: CEOs still like to use consultants to justify their own decisions to boards, as well as to have someone else to blame if it all goes wrong.) OpenAI has formed what it calls its Frontier Alliance with McKinsey, Boston Consulting Group, Capgemini, and Accenture to help clients use its Frontier platform for building and managing AI agents. (You can read my coverage of that announcement here.) Anthropic has struck similar deals with Deloitte, Accenture, and Cognizant and is reportedly in talks with private equity groups, such as Blackstone, to implement Claude-based solutions in their portfolio companies. I recently caught up with Capgemini’s Chief Strategy Officer Fernando Alvarez to talk about how his firm is viewing the future of consulting in an AI world.
Domain expertise matters
First, Alvarez says that while every client wants to use AI agents, they also recognize the need to govern those agents, make sure there is adequate cybersecurity around them, and ensure they can interact with legacy systems and fragmented data sources. Advising clients on all of that stuff and often helping them build it has been Capgemini’s bread and butter. He says clients still want Capgemini to provide these services. They aren’t ready to hand it off to AI. The other big selling point for the consulting firms, Alvarez says, is deep industry and domain expertise. The frontier AI labs don’t have the expertise in how to optimize a pharmaceutical manufacturing plant or the best way to run logistics for a fast-fashion retailer. Consulting firms do. And that makes a difference when trying to use AI agent successfully. Alvarez says the conversations clients want to have are not about how many agents you can spin up or how you orchestrate them. “The conversation is, do you have the domain expertise to understand my problem?” he says.
‘People want the cake, not the recipe’
That doesn’t mean that Capgemini itself isn’t using AI to help serve clients. Alvarez says the big shift that Capgemini, as well as some competitors such as Accenture, are trying to make is to move from selling technology and advice, to selling outcomes. In this model, the consulting firm takes on the risk of trying to figure out how to deliver, say, better customer support, whether that is through business process outsourcing to humans in lower wage countries, such as the Philippines or India, or through AI agents. “At the end, people want the cake,” he says—not a tour of the ingredients or the recipe. The new pitch boils down to a simple proposition: “Here is the problem. Here is the risk I’m willing to take, and this is the outcome I give you.” The client pays for the outcome: improved KPIs like successful customer issue resolutions and improved net promoter scores. The difference too is that the consultants in this model charge for the outcome, not by the number of people deployed on a project as some consultants have traditionally billed. Alvarez says that AI is also enabling Capgemini and other consulting firms to move into market segments, such as midmarket companies, that it couldn’t service previously because the economics didn’t make sense. The engagements often required more staff and cost than the client was willing to pay for. But now AI has lowered those staffing and cost requirements, meaning that Capgemini can offer a solution at a price point that is attractive to midmarket companies while maintaining a decent enough profit margin.
Perhaps the biggest challenge for consulting firms, though, is retraining their own people to work alongside AI agents. “Some people will make it, some people will not,” Alvarez says. For all the disruption, Alvarez is unmistakably energized. He calls this moment “probably the best opportunity I’ve seen in the history of technology.” The question now is whether Capgemini and other consultants can rewire themselves as fast as the technology demands—which is, of course, exactly what they are advising their clients to do.
With that, here’s more AI news.
Jeremy Kahn [email protected] @jeremyakahn
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