Generative AI takes off in business – but don’t call it a bubble

Businesses aren’t quite sure what to do with AI. Though consultancies are happy to write reports to help, they don’t always agree. And we’re not talking about agreeing with each other, but with themselves.

Take Goldman Sachs. The famous analyst firm made waves earlier this year with a report that said AI wasn’t delivering on value. The research, entitled “Too Much Spend, Too Little Benefit?”, suggested tech companies would spend $1 trillion on AI in the next few years, but wouldn’t have much in the way of a return on investment. 

But, as the Financial Times wrote, note the question mark: Goldman Sachs wasn’t quite sure. And now the analyst firm is out with an update that calls the heavy spending not a tech bubble but “rational exuberance”.

Now, Goldman Sachs wants to make it clear: you can make money with AI.

“There is a much greater probability that the generative AI opportunity is indeed real and that software applications and platform companies are able to re-invent and therefore re-accelerate growth – especially as interest rates start to come down,” writes Kash Rangan, Head of US Software Research in Goldman Sachs Research, in a post.

And no wonder then, that Goldman Sachs research suggests companies are setting aside a good chunk of their IT budgets for generative AI. Up to 9% over the next three years, according to a survey of CIOs.

Rangan suggests we look to cloud computing to understand how generative AI will impact businesses, as finding a “killer app” took some time and it was difficult to predict the return on early investments.

“Going through transition points like this can be very unnerving,” he writes.

No kidding – and no wonder Goldman Sachs can’t decide if generative AI will have a ROI because no-one is really sure what to do with it yet.

Generative over all other AI

That isn’t holding back generative AI when it comes to business deployments. Research by S&P Global Market Intelligence and commissioned by WEKA shows that generative AI has overtaken all other AI applications – and may, perhaps, be starting to pay off.

The research surveyed 1,500 industry leaders, with 88% actively investigating generative AI, well above other tools, such as prediction models (61%), classification (51%), expert systems (39%) and robotics (30%).

A piffling 11% of those surveyed have no plans for generative AI at all.

The research also found that 33% of respondents were implementing AI across their business, to boost product or service quality (42%) , target revenue growth (39%), boost productivity (40%) and boost IT (41%).

That said, although AI projects are maturing, average organisations are more likely to be working on pilots or limited deployments, rather than deploying at scale.

What’s holding back generative AI? On the technology front, storage and data management was the main concern, at 35% – well above compute, security and networking. Data quality remains the top challenge, the research said.

Although two-thirds of organisations are concerned about the environmental impact of AI due to their high energy use, it isn’t slowing adoption.

“Like the internet, the smartphone, and cloud computing before it, AI represents a paradigm shift that will leave an indelible mark on business and society and is already defining a new generation of industry leaders and disruptors,” says Liran Zvibel, cofounder and CEO at WEKA.

“Unlike past technology transitions, AI’s adoption and maturation are growing with unprecedented velocity.”

Unprecedented velocity! No wonder there’s so much “rational exuberance”.

Now we just need to figure out what AI is for, how to scale it and then – hopefully – the revenue will start flowing in.

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