Originally posted on venturebeat.
More than half (54.6%) of organizations are experimenting with generative artificial intelligence (generative AI), while a few (18.2%) are already implementing it into their operations, but only a few (18.2%) expect to spend more on the technology in the year ahead. That’s according to the early results of a new survey of global executives in data, IT, AI, security and marketing, conducted by VentureBeat ahead of the recently concluded VB Transform 2023 Conference in San Francisco.
The spending mismatch showcases challenges for enterprises seeking to adopt AI tools, namely: constrained budgets, or a lack of budget prioritization for gen AI.
The targeted survey, which began in June and is still ongoing, expects to conclude with more than 100 respondents. The full results are being made available exclusively to conference attendees.
Promise and challenges of generative AI adoption
AI has been called the most powerful and transformative technology since the advent of the internet itself, according to several prominent leaders in business and tech.
“The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone,” wrote Microsoft founder Bill Gates on his blog in March. “It will change the way people work, learn, travel, get health care, and communicate with each other.”
“I have never been as excited and as scared in my 20 years of doing venture capital because of gen AI,” said Tim Guleri, a venture capitalist at Silicon Valley firm Sierra Ventures, in an exclusive interview with VentureBeat back in June.
Despite these strong endorsements, organizations across industries are taking a cautious and measured approach to adopting new generative AI tools. Why is this the case?
How organizations are experimenting with generative AI so far
VentureBeat’s survey also asked organization leaders and stakeholders how they have been using gen AI so far in their early forays into the technology.
The largest use case (46% of respondents) was for natural language processing (NLP)-related tasks such as chat and messaging, followed by content creation (32%).
Yet a surprising number (32%) said they were deploying gen AI for other use cases, or not using the tech at all yet.
Of course, with gen AI being a relatively new technology for broad-based applications, and with new AI products, features and companies being announced daily, organizations may find themselves overwhelmed by the plethora of options and possible uses.
At the same time, the rapid pace at which gen AI products, services and features are being unveiled means that the landscape is shifting rapidly — so organizations that may not have found a good reason to seek out a gen AI solution in the past few months, could look again today and find one that better fits their needs.
Clearly, the generative AI story is just beginning, and the survey appears to reflect that, with organizations still in the process of sussing out how they can best deploy it to achieve their business goals, and very few willing to commit more spending on it. But as we’ve just discussed, the situation is changing rapidly — and survey results will likely look strikingly different next year.