Developers expect generative AI to be a big part of the future of software robotics, experts said at Automation Anywhere’s Imagine conference in September—it’s just a matter of how ready the tech is.
Sumit Johar, Automation Anywhere CIO, told IT Brew that since the end of 2021, generative AI has exploded in popularity precisely because it was clear it wasn’t a flash in the pan.
“I just had a session yesterday, and I asked people to raise their hands: ‘How many of you actually deployed it?,’” Johar said of generative AI. “And it was only, I would say, somewhere between 7% to 10% raised their hands. And then I said, ‘How many of you are really excited to deploy it?’, and 30% to 40% hands raised.”
Along with robotic process automation, or RPA, generative AI has software engineers and IT professionals alike excited for the future. As the tech evolves and use cases for its application increase, the key is not to overly lean on the tech, Johar said—it’s to find applications for it that align with existing processes, like the software robots his company develops.
“I am strongly advising everybody, combination of automation technologies and gen AI,” Johar said. “You need these together to be able to really see the promise that this has for everybody at the enterprise level.”
Caution was a recurring theme at Imagine. Automation Anywhere CEO Mihir Shukla told reporters at the conference that generative AI has its place in the automation space, but urged that its importance not be overemphasized.
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“The developer misconception that somehow generative AI will solve all problems and if people think of it, almost godlike? That’s not true,” Shukla said. “I think in reality, just within generative AI models, each one is specialized, just like human beings are.”
But not everyone agreed. KeyBank Business Technology Domain Manager Mike Reynolds is more bullish on the technology’s capabilities. He told IT Brew that his philosophy on technology is to move fast, break things, and innovate—sacrificing caution for getting ahead.
“I always hate slowing down; I like failing faster,” Reynolds said, adding, “if you can get the funding and really get the business case and push forward, that’s when you can accelerate in this space.”
Johar conceded there are reasons for moving fast to adapt generative AI, particularly when it comes to cybersecurity. In part, it’s about keeping abreast of threat actor attempts to deploy the technology to attack. Defenders, therefore, need to be sure they can stay ahead of the competition.
“All the more reason for us to invest more in generative AI; otherwise, we’ll be caught unprepared,” Johar said. “Because the bad actors are not going to wait; they’re going to start right now.”