Scott Belsky, chief product officer and executive vice president of Adobe’s Creative Cloud, said there’s a big difference between last year’s hype cycle around web3 and what we’re seeing with ChatGPT and other generative AI models this year. I believe there is.
Interviewed by Forbes reporter Alex Konrad at the Upfront Summit in Los Angeles today, Belsky said web3 didn’t promise to reduce the time it takes to complete a task, but that generative AI would certainly reduce it in his view. It says it will.
“Web3 didn’t promise to reduce workflow, the work that needs to be done across ideas and actions within an organization. And in fact, it added more friction and more work.” he said.
The true value of generative AI, he believes, is in speeding up tasks from hours or minutes to seconds, and it is powerful. In fact, he sees it as something of a value collaboration product brought to the company. Perhaps he’s a product like Figma, which Adobe is trying to buy him for $20 billion. The deal faced some regulatory hurdles, which may explain why he didn’t mention it in the interview.
“I think it’s similar to the trend of replacing all sorts of functions within an organization with collaboration products. There’s a series of startups that are really successful in reimagining every function in an enterprise to make it more collaborative. Yes, it’s web-based, as opposed to the old, hard-to-use on-premises software,” he said. “I think AI will do the same thing to reduce the workflow for all these jobs.
Moreover, in the hands of creative individuals, he believes generative AI can enhance, rather than replace, their skills.
“When you ask a great creative what they are good at, it is more discovery potential and more time to consider more solutions. will have more choices about which way to go,” said Belsky. “What a great opportunity for AI to actually offer. Not like the whole intern room, there are some amazing new possibilities here.”
Belsky says that as AI becomes more deeply embedded in the creative process, an audit trail will be built into the metadata of the work, allowing users to determine what parts were created by AI and what role humans played in the creation of the work. I’m guessing it could be.
He says it’s a little premature for enterprise users to trust it because they need to understand the audit trail. Also, proper permission has been given by the original creator of the work and the parties involved such as the models used and other parties. Create content.
“Many of our very large enterprise customers are very concerned about using the generated AI without understanding how it was trained. And if you use it in a campaign, just as you make sure you have model release and all other rights, we don’t consider commercial use viable. has that level of scrutiny and concern,” he said.
Ultimately, Belsky believes it’s not where companies are attacking generative AI that amazes us today. Instead, he explores cases for more practical business uses that reduce manual work and speed up processes.
“Some of the generative AI use cases we see in social media are: [wow us], but really, the more practical things that could actually be a business opportunity are the ones that enable content velocity and personalization. ”
