Início Tech The A.I. Boom Has an Unlikely Early Winner: Wonky Consultants

The A.I. Boom Has an Unlikely Early Winner: Wonky Consultants


After ChatGPT came out in 2022, the marketing team at Reckitt Benckiser, which makes Lysol and Mucinex, was convinced that new artificial intelligence technology could help its business. But the team was uncertain about how, so it turned to Boston Consulting Group for help.

Reckitt’s request was one of hundreds that Boston Consulting Group received last year. It now earns a fifth of its revenue — from zero just two years ago — through work related to artificial intelligence.

“There’s a genuine thirst to figure out what are the implications for their businesses,” said Vladimir Lukic, Boston Consulting Group’s managing director for technology.

The next big boom in tech is a long-awaited gift for wonky consultants. From Boston Consulting Group and McKinsey & Company to IBM and Accenture, sales are growing and hiring is on the rise because companies are in desperate need of technology Sherpas who can help them figure out what generative A.I. means and how it can help their businesses.

While the tech industry is casting about for ways to make money off generative A.I., the consultants have begun cashing in.

IBM, which has 160,000 consultants, has secured more than $1 billion in sales commitments related to generative A.I. for consulting work and its watsonx system, which can be used to build and maintain A.I. models. Accenture, which provides consulting and technology services, booked $300 million in sales last year. About 40 percent of McKinsey’s business this year will be generative A.I. related, and KPMG International, which has a global advisory division, went from making no money a year ago from generative-A.I.-related work to targeting more than $650 million in business opportunities tied to the technology over the past six months.

The demand for tech-related advice recalls the industry’s dot-com boom. Businesses stampeded consultants with requests for counsel in the 1990s. From 1992 to 2000, sales for Sapient, a digital consulting firm, went from $950,000 to $503 million. Subsequent technology shifts like the migration to mobile and cloud computing were less hurried, said Nigel Vaz, chief executive of the firm, which is now known as Publicis Sapient.

“In the mid-90s, C.E.O.s would say, ‘I don’t know what a website is or what it could do for my business, but I need it,’” Mr. Vaz said. “This is similar. Companies are saying: ‘Don’t tell me what to build. Tell me what you can build.’”

Consulting firms have been scrambling to show what they can do. In May, Boston Consulting Group hosted a one-day conference at a Boston convention center where it set up demonstration booths for OpenAI, Anthropic and other A.I. tech leaders. It also demonstrated some of its own A.I. work in robotics and programming.

Generative A.I. sales are helping the industry find growth after a postpandemic lull. The management consulting industry in the United States is expected to collect $392.2 billion in sales this year, up 2 percent from a year ago, according to IBISWorld, a research firm.

The work that consultants have been enlisted to do varies from business to business. Some consultancies are advising companies on regulatory compliance as regions like the European Union pass laws regulating artificial intelligence. Others are drawing up plans for A.I. customer support systems or developing guardrails to prevent A.I. systems from making errors.

For businesses, the results have been mixed. Generative A.I. is prone to giving people incorrect, irrelevant or nonsensical information, known as hallucinations. It is difficult to ensure that it provides accurate information. It can also be slower to respond than a person, which can confuse customers about whether their questions will be answered.

IBM, which has a $20 billion consulting business, ran into some of those issues on its work with McDonald’s. The companies developed an A.I.-powered voice system to take drive-through orders. But after customers reported that the system made mistakes, like adding nine iced teas to an order instead of the one Diet Coke requested, McDonald’s ended the project.

McDonald’s said it remained committed to a future of digital ordering and would evaluate alternative systems. IBM said it was working with McDonald’s on other projects and was in discussions with other restaurant chains about using its voice-activated A.I.

Other programs from IBM have shown more promise. The company worked with Dun & Bradstreet, a business data provider, to develop a generative A.I. system to analyze and provide advice on selecting suppliers. The tool, called Ask Procurement, will allow employees to conduct detailed searches with specific parameters. For example, it could find memory chip suppliers that are minority owned and automatically create a request for proposals for them.

Gary Kotovets, chief data and analytics officer at Dun & Bradstreet, said his team of 30 people needed IBM’s help to build the system. To reassure customers that the answers that Ask Procurement provides are accurate, he insisted that customers be able to trace every answer to an original source.

“Hallucinations are a real concern and in some cases a perceived concern,” Mr. Kotovets said. “You have to overcome both and convince the client it’s not hallucinating.”

Over seven weeks this year, McKinsey’s A.I. group, QuantumBlack, built a customer service chatbot for ING Bank, with guardrails to prevent it from offering mortgage or investment advice.

Because the viability of the chatbot was uncertain and McKinsey had limited experience with the relatively new technology, the firm did the work as a “joint experiment” under its contract with ING, said Bahadir Yilmaz, chief analytics officer at ING. The bank paid McKinsey for the work, but Mr. Yilmaz said many consultants were willing to do speculative work with generative A.I. without pay because they wanted to demonstrate what they could do with the new technology.

The project has been labor intensive. When ING’s chatbot gave incorrect information during its development, McKinsey and ING had to identify the cause. They traced the problem back to issues like outdated websites, said Rodney Zemmel, a senior partner at McKinsey working on technology.

The chatbot now handles 200 of 5,000 customer inquiries daily. ING has people review every conversation to make sure that the system doesn’t use discriminatory or harmful language or hallucinate.

“The difference between ChatGPT and our chatbot is our chatbot cannot be wrong,” Mr. Yilmaz said. “We have to be safe with the system we’re building, but we’re close.”

Over a four-month period this year, Reckitt worked with Boston Consulting Group to develop an A.I. platform that could create local advertisements in different languages and formats. With the push of a button, the system can turn a commercial about Finish dishwashing detergent from English into Spanish.

Reckitt’s A.I. marketing system, which is being tested, can make developing local ads 30 percent faster, saving the company time and sparing it from some tedious work, said Becky Verano, vice president of global creativity and capabilities at Reckitt.

Because the technology is so new, Ms. Verano said, the team is learning and adjusting its work as new tech companies release updates to the image and language models. She credited Boston Consulting Group with bringing structure to that chaos.

“You’re constantly having to move to the latest trends, to the newest findings, and learning each time how the tools respond,” she said. “There’s not an exact science to it.”



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