Back in the unenlightened days of April 2023 — the spring after ChatGPT came out and its generative AI capabilities had everyone wondering how it would change everything — more than half of US companies had yet to evaluate their business use cases of generative AI, according to new data from ETR, a firm that continually surveys companies’ tech decision makers about how they’re spending their budgets.
One whole year later, that’s down to just 20%.
Everyone wants to know how generative AI is going to help their companies work better, faster and cheaper. In practice that’s largely meant using it to summarize text and data, create marketing copy, and support customers with chatbots.
The problem is, like with many new hyped technologies, it’s gonna take a while to actually happen — if it happens at all.
Of the organizations that have started evaluating the use of generative AI, about a third have yet to implement any in their businesses, a percentage that’s been basically constant since last fall. Companies are worried about data privacy, legal compliance, and whether they can actually afford it.
“I do think the hype cycle, because of how quickly it moved, the pendulum is stalling and swinging back a little bit,” ETR’s Chief Strategist and Research Director Erik Bradley told Sherwood. “People are recognizing it's still important, it's still going to be there. It might not be the panacea, the savior of their enterprise at this stage.”
Indeed the ETR found quite a disconnect between those in upper leadership who are boosting generative AI and the engineers who actually have to implement it when asked when the technology has or will start generating returns.
The C-suite was 10 percentage points more likely to say they expect a ROI in 3 months than those in technical decision-making positions like engineers. Meanwhile the leadership was 10 percentage points less likely to say they didn’t know, than the tech workers. Note that though the initial survey was of 1,800 tech decision makers, by the time it’s drilled down to tech workers and C-suite at companies who’ve implemented gen AI, we’re talking about 450 people.
“The hype is there, the excitement's there, but then we actually have to get it to work,” Bradley said.
That’s in line with recent reporting from The Information that found that some enterprise generative AI customers “are being cautious or ‘deliberate’ about increasing spending on new AI services, given the high price of running the software, its shortcomings in terms of accuracy and the difficulty of determining how much value they’ll get out of it.”
They reported that a Gartner analyst recently warned Amazon Web Services sales people pushing generative AI technology that the industry could be at the peak of its hype cycle, meaning it could soon enter the “trough of disillusionment,” as expectations outshadow reality.
So despite recent grand predictions from leaders like Elon Musk and Jamie Dimon, AI’s impact on industry may be a distant, if ever, reality.
