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

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

Generative AI sales are helping the industry find growth after a post-pandemic lull. The management consulting industry in the United States is expected to collect $US392.2 billion in sales this year, up 2 per cent 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 AI customer support systems or developing guardrails to prevent AI systems from making errors.

For businesses, the results have been mixed. Generative AI 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.

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IBM, which has a $US20 billion consulting business, ran into some of those issues on its work with McDonald’s. The companies developed an AI-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 AI.

Other programs from IBM have shown more promise. The company worked with Dun & Bradstreet, a business data provider, to develop a generative AI system to analyse 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,” Kotovets said. “You have to overcome both and convince the client it’s not hallucinating.”

Over seven weeks this year, McKinsey’s AI 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 Yilmaz said that many consultants were willing to do speculative work with generative AI without pay because they wanted to demonstrate what they could do with the new technology.

The project has been labour-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 the system doesn’t use discriminatory or harmful language or hallucinate.

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“The difference between ChatGPT and our chatbot is our chatbot cannot be wrong,” 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 AI platform that could create local advertisements in different languages and formats. With the push of a button, the system can turn a commercial about its Finish dishwashing detergent from English into Spanish.

Reckitt’s AI marketing system, which is being tested, can make developing local ads 30 per cent 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, 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 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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This article originally appeared in The New York Times.

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