IBM CEO: AI is near a key tipping point, but generalized AI is still decades out – ZDNet

When it comes to generalized AI, “we have no idea how this is going to happen,” IBM CEO Arvind Krishna says. That isn’t stopping IBM from building AI tools that are now close to necessary for businesses to stay competitive.
Stephanie Condon is a senior staff writer for Red Ventures based in Portland, Oregon, covering business technology for ZDNet.
The global market is on the cusp of hitting a critical AI tipping point that will unlock major productivity gains, IBM CEO Arvind Krishna said to reporters this week, ahead of the annual IBM Think conference in Boston. 
Supporting that assertion, IBM released its Global AI Adoption Index 2022, which surveyed 7,502 senior business decision-makers. It shows that currently, 35% of companies are using AI in their business, up to four points from 2021. Additionally, 30% say employees at their organization are already saving time with new AI and automation software and tools.  
Krishna said he believes those numbers will steadily climb until “you kind of reach a tipping point around 50%. Then it tips over to 90% very quickly. This means we’re just before this tipping point, and that is what unlocks all of this productivity.”
Krishna said that level of AI adoption could add nearly $16 trillion to the economy by 2030, referencing a well-cited PWC report
At the conference in Boston this week, IBM is showcasing how it’s working with customers like McDonald’s to deploy practical AI use cases. Krishna intends to show customers, partners and investors how IBM will remain relevant in the burgeoning AI market, even after years of missteps that raised questions about IBM’s role in advancing AI. Earlier this year, IBM had to sell off Watson Health — once considered one of IBM’s “strategic imperatives.”
While IBM is still gunning for a leadership position in AI, the company won’t be focusing on “moonshots,” Krishna told reporters this week. 
“We have to work on those things… that provide value this year, and next year, and the year after for our clients,” he said. “In addition, we might work might work on a couple of what we’re labeling as moonshots.
“I do believe some of the healthcare examples [in AI] will happen,” he continued, “but they may make take a half-decade, or a decade more, to come to fruition, just given how hard those problems are. And those problems are life and death.”
As for the ultimate moonshot — developing generalized AI — Krishna said he believes that’s still a long way out. Surveys of scientists show most expect generalized AI to be achieved somewhere between 2050 and 2075. 
“Having grown up as a scientist… if anything is 25 years away, my conclusion is we have no idea how this is going to happen,” Krishna said. “Is it worth working on? Sure. Is it worth making that the majority of the effort? I think that is too stretched.”
In the meantime, he said, companies like IBM can help companies automate key processes. McDonald’s, for instance, is using IBM AI to automate the process of taking orders from customers. Big Blue is also working with customers to apply AI to IT processes. 
“The reason AI is advancing rapidly is that we’re at  2.5 quintillion bytes of data being produced each day,” Krishna said. “That’s 2.5, followed by 18 zeros. There is no way any amount of humans are ever going to process that. Old analytics and database techniques are insufficient. AI is the only tool able to harness and harvest that data for insights.”
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