- Telcos talk a lot about AI use cases around network optimization, customer service and process efficiency
- But unlike the healthcare and pharma industries, AWS exec Ishwar Parulkar said he hasn't heard them talk much about innovation and invention
- Slow adoption of AI solutions could be skewing operators' ROI calculus
Operational efficiency. Network optimization. Customer experience. These are the three key areas where operators are applying AI and seeing good returns (annoying chatbots notwithstanding). But there’s one big bullet point absent from the telco AI conversation: innovation.
“Some of the other industries like healthcare or life sciences, they are using AI for innovation and research and creating new things, not just productivity or operations,” Ishwar Parulkar, AWS’ CTO for Telecom and Edge Cloud, told Fierce. “In general, that conversation I find missing in the telco world.”
So, what might thinking outside the box look like?
Well, Parulkar suggested, perhaps AI could be used to help create new protocols or write telecom standards. Maybe it could be used to create portions of the 6G architecture based on inputs from a technical committee. Maybe telcos can use it to speed product development cycles.
“I’m looking to see how telcos can create new stuff,” he said. “I don’t see enough conversation around how telcos can use AI to increase the topline.”
AI ROI curve
Why is this? Well, telcos, like other enterprises have spent the past year or two sifting through AI use cases to figure out which ones deliver a reasonable return on investment (ROI). In practice, that is easier said than done.
A recent CEO survey conducted by IBM found that only 25% said AI initiatives have delivered the expected ROI. That means operators have likely had their hands full piloting use cases that have ended up on the cutting room floor.
The IBM survey also found that only 16% of successful AI initiatives have scaled enterprise-wide.
Parukar noted that the AI scale and adoption curve could be part of the problem in achieving ROI for certain use cases.
“It takes time to adopt some of these use cases,” he said. “You might have something in production, but how many people use it and how many times is what gets it traction.”
He pointed out that Amazon itself has run up against this issue with its Rufus AI assistant for its retail shopping experience. Even though most people use Amazon for online shopping, it took a while to raise awareness and encourage use of Rufus, he said.
“To get operators to start using it takes time, and that’s one of the challenges I see in this space,” he concluded. “There’s a change in behavior required for many of these use cases, and that it one of the things that is making it take some time.”
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