While 89% of executives name AI and generative AI among their top three technology priorities in 2024, the vast majority appear to have made little progress so far, according to a recent BCG X survey.
BCG X polled over 1,400 C-suite executives in 50 markets and over a dozen industries. They found that despite the overwhelming majority of executives who say AI is a top short-term priority, 90% of respondents remained what BCG X identified as AI “observers”—expecting the technology to take more than two years to mature, exploring its use in only a limited fashion, or both.
What’s more, the poll found many enterprises aren’t making much progress on how to actually do anything with AI. Just 6% of respondents said they had managed to train at least a quarter of their staff on generative AI tools, while 62% reported a shortage of talent and skills. Almost as many (59%) reported little or no confidence in their executive team’s proficiency with AI technology.
Nearly half (47%) said their organizations lacked clear investment priorities on AI, and nearly as many (42%) reported not having any strategy on how to deploy the technology responsibly. Only 19% of respondents named cost as their top concern when choosing AI solutions.
Sesh Iyer, managing director, senior partner, and North America co-chair of BCG X, told IT Brew the survey results show the “real chasm” between supply and demand on AI.
“Take a look at executives who have the strategic lens,” Iyer said. “What they’re looking for is real competitive differentiation, top line revenue, productivity, cost to serve, risk.”
While executives appear ambitious to harvest gains from AI, the “heterogenous” state of the tech poses difficulties, Iyer added: “There are so many service providers that are actually coming up with their own solutions, so there's this entire body of work around selecting and picking technologies.”
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For those enterprises which are investing heavily in AI, expectations are high. The BCG survey shows organizations planning on investing at least $50 million into AI or generative AI in the next year are 1.3 times more likely than others to expect cost savings, and 1.5 times as likely to expect cost savings of more than 10%.
Some enterprises are leveraging existing AI technology, like productivity tools, enterprise data search and retrieval, or generated summaries of meetings, Iyer said. However, he said few have integrated AI into “critical functions.”
“What is really sucking up a lot of oxygen in this new technology that's out there is the LLMs [large language models] like GPT or Llama 2,” Iyer said. “I think that is a very narrow view of what it takes to implement a solution.”
Iyer also pointed out that an LLM is only one part of how an enterprise can integrate AI into its operations, as implementation also requires systems which compile useful data, integrate with an LLM to deliver insights, and make conclusions available to end users. All of those components have their own metrics of accuracy, latency, and cost, according to Iyers, which organizations will have to take into account when trying to move beyond hype.
“In 2023, we saw many organizations that were starting things without a real business case,” Iyer said. “I think what we’re starting to see now as we go into 2024 is more organizations asking for meaningful business cases before they invest.”