The Australian info roberthyrons/Getty ImagesGenerative AI has captured the general public’s attention, but that sense of excitement doesn’t mean executives believe it’s ready to be deployed in the business
Just one in ten technology leaders globally report having large-scale implementations of AI, according to Nash Squared’s annual Digital Leadership Report, which is the world’s largest and longest-running annual survey of technology chiefs.
What’s more, the hype surrounding generative AI has done little to encourage further investment in artificial intelligence — Nash Squared reports the one in ten proportion who spend big on AI hasn’t changed for five years.
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From the outside looking in, it seems the bark of AI is a lot louder than the bite. While everyone’s talking about generative AI and machine learning, very few companies are investing in large-scale AI implementations.
However, Bev White, CEO of digital transformation and recruitment specialist Nash Squared, says in an interview with ZDNET that it’s important to place these headline figures in context.
Yes, few businesses are spending big on AI right now, but lots of organizations are starting to investigate emerging technology.
“What we are seeing is actually quite an uptake,” says White, who says interest in AI is at the research rather than the production stage.
Around half of companies (49%) are piloting or conducting a small-scale implementation of AI, and a third are exploring generative AI.
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“And that’s exactly what we saw when cloud started to really take off,” says White, comparing the rise of AI to the initial move to the cloud over a decade ago.
“It was, ‘let’s dip our toe in the water, let’s understand what all the implications are for policies, for data, for privacy, and for training,'” she says.
“Businesses were creating their own use cases by doing small but meaningful pilots. That’s what happened last time, and I’m not surprised that’s what’s happening this time.”
In fact, White says the hesitancy to spend big on AI makes a lot of sense for two key reasons.
First, cash is tight in many organizations due to heavy investment in IT during and immediately after the COVID-19 pandemic.
“Digital leaders are trying to balance the books — they’re thinking ‘what’s going to give me the greatest return for investment right now,'” she says.
“Small, careful, well-planned pilots — while you’re still doing some of the punchier digital transformation projects — will make a big difference to your organization.”
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Second, a lot of emerging technology — particularly generative AI — remains at a nascent stage of development. Each new iteration of a well-known large language model, such as OpenAI’s ChatGPT, brings new developments and opportunities, but also risks, says White.
“You’re accountable as a CIO or CTO of a big enterprise. You want to be sure about what you’re doing with AI,” she says. “There’s such a big risk here that you need to think about your exposure — what do you need to protect the people that work for your business? What policies do you want to have?”
White talks about the importance of AI security and privacy, particularly when it comes to the potential for staff to train models using data that’s owned by someone else, which could open the door to litigation.
“There’s a big risk that people can cut and paste,” she says. “I’m not saying generative AI isn’t good. I’m really a fan. But I am saying that you’ve got to be very consciously aware of the sources of data and the decisions you make off the back of that information.”
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