Capgemini’s Strategy Chief: AI Won’t Replace Consultants, Here’s Why

(SeaPRwire) –   Welcome to Eye on AI. This edition covers…Nvidia projecting $1 trillion in AI chip sales by 2027…Meta postponing its latest AI model launch (again)…Moonshot AI creating a new architecture for large neural networks…and potential future concerns over ‘moral crumple zones.’

Following the launch of ChatGPT in November 2022, the consulting profession is frequently cited as being obsolete. The rationale is that consultants provide strategic advice, assist with business restructuring and new processes—often involving third-party technology—and offer or facilitate outsourced services like customer support or software development. Advanced AI models can now deliver strategic guidance, recommend organizational changes and software, and AI agents can integrate systems, code, and handle customer service. This suggests the end for consultants, correct?

However, this has not been the case. As a recent Wall Street Journal article noted, AI companies have realized they require consultants, also known as “systems integrators,” to help sell their AI agents. Effectively deploying AI agents demands significant organizational change—data cleansing, workflow redesign, and human resource reallocation—plus strategic planning to gain a competitive edge.

AI vendors lack the resources to offer this advisory support broadly; OpenAI has roughly 70 “forward deployed engineers” for on-site client implementation, and Anthropic has a comparable number. Although AI could theoretically perform this role, it faces a trust issue—corporate boards prefer advice from firms like McKinsey or BCG over ChatGPT. (A more skeptical view: CEOs use consultants to validate their decisions to boards and to have a scapegoat if things fail.)

OpenAI established its Frontier Alliance with McKinsey, BCG, Capgemini, and Accenture to assist clients with its Frontier platform for AI agents. Anthropic has similar partnerships with Deloitte, Accenture, and Cognizant, and is allegedly in discussions with private equity firms like Blackstone to deploy Claude-based solutions.

I recently spoke with Capgemini’s Chief Strategy Officer, Fernando Alvarez, about his firm’s perspective on consulting’s future in an AI-driven world.

Domain expertise matters

Alvarez notes that while clients are eager to use AI agents, they also understand the necessity to govern them, ensure robust cybersecurity, and guarantee compatibility with legacy systems and disparate data sources. Providing guidance and implementation support in these areas is Capgemini’s core business, and clients continue to demand these services, not yet ready to entrust them entirely to AI.

Another major advantage for consulting firms, according to Alvarez, is their profound industry-specific knowledge. Frontier AI labs lack expertise in optimizing a pharmaceutical plant or managing logistics for a fast-fashion retailer, whereas consulting firms possess it. This expertise is crucial for successful AI agent deployment. Alvarez states that client discussions focus not on the number of agents or their orchestration, but on the question: “Do you have the domain expertise to understand my problem?”

‘People want the cake, not the recipe’

This does not imply that Capgemini avoids using AI to assist clients. Alvarez explains that Capgemini and rivals like Accenture are shifting from selling technology and advice to selling outcomes. In this approach, the consulting firm assumes the risk of determining how to achieve a specific result, such as enhanced customer support, whether through outsourcing to lower-wage countries or via AI agents.

He analogizes that clients want the final product, not the instructions. The new proposition is straightforward: “Here is the problem. Here is the risk I’m willing to take, and this is the outcome I give you.” Payment is based on improved key performance indicators, like customer issue resolution rates and net promoter scores, rather than traditional per-person project billing.

Alvarez adds that AI allows firms like Capgemini to target previously inaccessible midmarket segments. Previously, the staffing costs for such engagements were prohibitive, but AI has reduced these requirements, enabling profitable service offerings at attractive price points for mid-sized companies.

However, the most significant challenge for consultancies may be retraining their staff to collaborate with AI agents. “Some people will make it, some people will not,” Alvarez remarks.

Despite the upheaval, Alvarez is clearly enthusiastic, describing this era as “probably the best opportunity I’ve seen in the history of technology.” The pivotal question is whether Capgemini and its peers can adapt themselves as rapidly as the technology evolves—precisely the advice they give their clients.

On that note, here is additional AI news.

Jeremy Kahn
jeremy.kahn@.com
@jeremyakahn