IBM CEO Arvind Krishna: AI Adoption Will ‘Explode’ As Costs Drop

IBM CEO Arvind Krishna reportedly said Tuesday (Feb. 11) that the lower costs said to have been achieved by DeepSeek will help boost demand for artificial intelligence (AI).

“We will find that the usage will explode as costs come down,” Krishna told Bloomberg Television.

IBM has shifted its focus to high-growth software and services and has booked about $5 billion in generative AI-related business since mid-2023, mostly consulting, Bloomberg reported Tuesday.

Lower AI model costs are expected to help companies like IBM offer AI features to more customers, according to the report.

DeepSeek’s launch of a new AI model in late January drove a plunge in tech stock prices, because the company claimed to use substantially fewer Nvidia chips to achieve comparable performance to those of its U.S. rivals.

“DeepSeek challenges the narrative that innovation must come at an unsustainable cost,” Gokul Naidu, a consultant for SAP, told PYMNTS in an interview posted Jan. 27. “For businesses, this means AI could soon be accessible to small and medium enterprises, not just tech giants with deep pockets.”

BofA Global Research said Jan. 28 that the $5.58 million cost of training a foundation model that was claimed by DeepSeek is “misleading” because the company did not include costs related to research, experiments, architectures, algorithms and data, but added that the bigger picture is that the startup introduced innovations that show less costly training is possible.

“Cost is the biggest hurdle to adoption of AI applications,” BofA Global Research analysts Brad Sills and Carly Liu wrote in a note published Jan. 28. “We believe advancements in cost could drive price even lower and therefore adoption higher.”

Anthropic CEO Dario Amodei wrote in an essay posted Jan. 29 that claims about DeepSeek’s potential threat to U.S. AI leadership is “greatly overstated” and that the drop in chip maker Nvidia’s stock driven by the release of DeepSeek’s AI models was “baffling.”

Amodei wrote that a closer look shows that the DeepSeek model is close to the performance of U.S. models that are between seven and 10 months older; is “an expected point on an ongoing cost reduction curve;” and was trained by a company whose total spend as a company is not so different from U.S. AI labs.

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