Every enterprise plans to increase AI spending next year

A survey of 600 companies globally released Thursday, conducted by the MIT Technology Review’s Insights group, found that all of the companies’ executives plan to increase spending in the coming year “on modernizing data infrastructure and adopting AI.”

The study, sponsored by data warehousing firm Databricks, was conducted from June through August of this year, and surveyed companies with half a billion or more in annual revenue, based in 12 countries in North America, Europe, Asia-Pacific, and the Middle East, said MIT Tech Review.

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Executives surveyed were mostly C-level executives, in positions such as chief information officer, chief data/analytics officer, head of IT, AI, or data engineering, and similar roles.

The report’s overall conclusions: 

• Enterprise adoption of AI is ready to shift into higher gear.
• Technology executives are moving quickly to deploy or experiment with it.
• Organizations are sharply focused on retooling for a data and AI-driven future.

The companies generally have very upbeat expectations, note the report’s author, Denis McCauley, editor Teresa Elsey, and publisher Nicola Crepaldi. “Eighty-one percent of survey respondents expect AI to boost efficiency in their industry by at least 25% in the next two years; one-third say the gain will be at least 50%,” writes McCauley.

The survey emphasizes that the firms also expect artificial intelligence programs to offer new routes to products and revenue. “While 70% of survey respondents say it’s very important for AI projects to help reduce costs, the same percentage say it’s very important that these projects enable new revenue generation (although there is variation across industries and geographies),” the report states. Executives clearly do not consider this a time to batten down the hatches.”

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Almost half of the firms surveyed said they will boost spending on data infrastructure and AI by more than 25%, the survey notes. 

The survey includes some examples from executives who were willing to go on the record. For example, Jon Francis, the chief data and analytics officer at car maker General Motors, relates that:

“With advances in AI and machine learning and the investments we’ve made, we’re better able now than a few years ago to create efficiencies […] “We’ll do so in the back office with HR chatbots, on the factory floor with predictive maintenance, and in IT operations by scaling and productionizing software development.” 

At the US Transportation Security Administration, CIO Yemi Oshinnaiye told the author, “LLMs are definitely in our future. It’s very important from a customer engagement perspective that we are able to leverage things that are going to become normal,” referring to large language models, LLMs, a form of generative AI program.

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The survey has a wealth of data points regarding companies’ priorities. For example, among the top use cases for generative AI, in order of importance, respondents cited “Personalization and customer experience,” “Supply chain optimization,” and “Quality control.”

The study also cites a number of differences globally. For example, in terms of readiness to deploy generative AI, Japan is well ahead of the US, with 35% of respondents saying their firm is “investing and adopting it” compared to just 26% of US respondents. 

Regarding the increased spending, the majority of the respondents perceived that peers in their respective industries are moving ahead with spending at a fast pace, the survey notes. 

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“Most survey respondents perceive similar actions by their peer organizations — 60% of survey respondents say AI adoption in their industry is “fast” or “very fast,” the survey notes. 

“Though the dynamics vary somewhat by industry, the trend is that AI adoption in the enterprise is moving ahead at pace, and data modernization to support it remains a priority.”