Adobe’s Scott Belsky talks generative AI — and why it’s not going to end up like web3


Woman thinking creatively and pictures appear behind her representing her creative process.
Image Credits: metamorworks / Getty Images

Scott Belsky, chief product officer and executive vice president for Adobe’s Creative Cloud, believes there’s a big difference between the hype cycle around web3 last year and what we’re seeing this year with ChatGPT and other generative AI models.

Belsky, who was interviewed by Forbes reporter Alex Konrad at the Upfront Summit in Los Angeles today, says web3 did not promise to reduce the time it takes to complete tasks, and generative AI most definitely does in his view.

“Web3 did not promise to reduce the workflow, the work that has to be done across any idea or action in the organization. And in fact, it added more friction and more work,” he said.

He believes that the real value of generative AI is speeding up tasks from hours or minutes to seconds, and that’s powerful. In fact, he sees it as being more like the value that collaborative products have brought to the enterprise — products like Figma perhaps, a collaborative design product that Adobe is in the midst of trying to acquire for $20 billion. The transaction is facing several regulatory roadblocks, which could explain why he didn’t mention it in the interview.

“I think it will be more akin to the sort of trend of collaborative products replacing every sort of function in an organization — you know, there’s a whole suite of startups that have actually been quite successful reimagining every function of the enterprise to be more collaborative and web-based, as opposed to like old clunky on-premise software,” he said. “I think that AI will do the same thing to reduce the workflow around all these job functions, and we’re starting to see a lot of examples of that, and I think we’re in the early days of that.”

Further, he believes that in the hands of creative individuals, generative AI could enhance their skills, rather than replacing them.

“If you ask any great creative what makes them great, it’s having more surface area for discovery and having more time to see more possible solutions so that they can have more choices of which path to follow,” Belsky said. “What an amazing opportunity for AI to actually suggest — instead of like a whole room of interns, here’s some amazing new possibilities.”

Belsky speculates that as AI becomes more deeply embedded in the creative process, there may be an audit trail built into the work’s metadata to help users determine what parts were created by AI and what role humans had in the work’s creation.

He says that it’s a bit early for enterprise users to trust it because of the need to understand that audit trail, as well as that proper permissions were given by the work’s original creator and any adjacent people such as the models used or other people involved in the content’s creation.

“A lot of our very big enterprise customers are very concerned about using generative AI without understanding how it was trained. They don’t see it as viable for commercial use in a similar way to using a stock image and making sure that if you’re going to use it in a campaign you better have the rights for it — and model releases and everything else. There’s that level of scrutiny and concern around the viability for commercial use,” he said.

Ultimately, Belsky thinks the stuff that wows us today probably won’t be where companies are attacking generative AI. Instead, they’ll be exploring much more practical business use cases that reduce manual work and speed up processes.

“Some of the use cases of generative AI that we see on social media [wow us], but actually the more practical ones that may end up really being a business opportunity are things that just enable content velocity and personalization.”

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