“Misconceptions” Stalling Many Gen AI Liftoffs

There’s a recipe for success with artificial intelligence rollouts, but too many companies aren’t following it.

As bright as the outlook is for artificial intelligence, C-suite officials are finding there’s hype and there’s reality when launching AI campaigns. That scenario is leading to readjusted expectations on AI deployment progress, according to a new report.

The study from MIT Technology Review Insights and Australia-based telecoms company Telstra shows while companies look to disrupt their industries using generative AI, only a low percentage say they’ve found the proper balance of technology and other attributes such as funding, culture, and skills.

The news is even worse for companies that haven’t fully prepared for AI campaigns.

“Those with the most experience of rolling out generative AI have even less confidence in their IT, suggesting many businesses underestimate the requirements for its effective deployment,” the report stated. “This implies their plans to be disruptors—rather than the disrupted—may well flounder over problems that many respondents appear not to appreciate fully.”

As a result, only 9% of the 300 company leaders surveyed said their firms were “significantly” using AI. That’s a figure far below user expectations set by media and AI advocates.

“There is a misconception about how easy it is to run mature, enterprise-ready, generative AI,” said Stela Solar, inaugural director at Australia’s National Artificial Intelligence Centre, in the report. “Its adoption may require companies to “improve data quality and capability, privacy measures, AI skilling, and implement organization-wide safe and responsible AI governance,” she added.

“There are surrounding elements like the app design, connection to data and business processes, corporate policies, and more that are still needed,” Solar added.

Bad Decisions Out of the Gate

One big issue on the “misconception” front is related to IT investment. In short, too many companies mulling AI adoptions aren’t budgeting correctly and making optimal IT choices.

“Many countries are still in the early stages of adopting generative AI, with the technology only recently becoming available in productivity suites suitable for a wider audience,” says Laurence Liew, director of AI innovation at AI Singapore. “The requirements for effective implementation of generative AI include access to real datasets, AI engineers, and computer infrastructure.”

Companies face a dilemma in accessing the necessary hardware today, Liew says. “Choices include outright purchase and pay-as-you-go outsourcing, both of which carry their own risks. Additionally, data quality, storage, and talent remain bottlenecks for effective deployment,” he added.

What’s the way forward for companies preparing first-time AI launches? Address your information technology deficiencies or risk falling short of your AI expectations, the MIT report warns.

“Fewer than 30% of respondents rank IT attributes at their companies as conducive to rapid adoption of generative AI,” the study states. “Moreover, these results may be overly optimistic. Those with the most experience rolling out generative AI have even less confidence in their IT.”

“Many in this group (65%) say their available hardware is, at best, modestly conducive to rapid adoption,” MIT Insights adds.


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