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 agents 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.
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.
