Building AI-First Organisations: Data, Products, and Enterprise Value

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The Fast Mode Podcasts: Breaking News, Analysis and Updates From Telecoms Industry 19 min 2 speakers 4 chapters transcribed 1 month ago
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Tara Neal 0:11
Welcome to the Fast Mode Podcast series. I'm Taranil, and with me today is Wasanth Raju, head of AI products at Rakuten. Rakuten Group is a global technology leader in services that empower individuals, communities, business, and society. Founded in Tokyo in 1997 as an online marketplace, Rakuten has expanded to offer services in e-commerce, fintech, digital. content and communications to two billion members around the world. Wasanth joins us ahead of TM Forum's DTW Ignite twenty twenty six taking place next week in Copenhagen. Welcome Raju. Great to have you on today's episode.
Unknown 0:52
Thanks for having me, Tara, and uh great to be here today with you.
Tara Neal 0:56
Awesome. Okay, so you know, um next week's uh DTW Ignite and uh you'll be speaking at the show. So what themes will you be touching on and what do you expect to be the biggest topics of conversations across the industry this year?
Vasanth Raju 1:13
Yeah, I think I'll I'll try to cover the later part of your question first, right? I I think uh fundamentally telco is that uh uh crossroads, right? So if you're looking at RPU year over year from 2020, 2026, uh it's gone down by 12.5% uh global output of users. Um and there's a record number uh amount of data usage at the moment. Uh so I think the real big question that's facing a lot of telecooperators uh is which business are we in, right? Like uh um I think A lot of the telco operators are wondering what should be my business model moving forward. And I think that's going to be a big theme, I expect. I think that's a good thing. And I would cover that as well in my speech.
Vasanth Raju 2:07
Obviously, understandably a lot. of models and how powerful they are today. Uh I think uh we expect a lot of conversations around uh um I think especially around moving beyond just pilots, right? Like I think people have tried it POCs, pilots, and uh we need to have it in production and uh are we seeing ROI in value. I see that's going to be a big part of the conversation too. Uh and I'm I'm gonna share like uh actual um ROI that Rockerton has been driving uh from some of these deployments that we've done at scale uh inside the company.
Tara Neal 2:42
Mm-hmm. Wow. So, you know, you mentioned AI, right? So I guess, you know, AI is um a a big topic um across, you know, all the telecom uh and even t a lot of tech events that we see this year. And you know why not? Because AI is expanding at such a rapid uh space and scale. And you know, uh we know that telcos are embracing AI, we see AI, agenting AI, a lot of uh things being incorporated. in their operations, right? So, you know, expanding on that, right, what does AI first product development and execution look like within a large scale digital ecosystem like Rakuten?
Vasanth Raju 3:21
Uh it's that's a great question, right? So Uh yeah at Raccoon we strictly believe, uh I mean uh generally believe rather uh that basically AI is not something that you bolt onto an existing product, right? Like and and call it uh an AI uh product. I think uh uh the main way we look at it is uh how can AI amplify the value of our ecosystem, right? Um so uh one of the big things That we've been doing is uh how do we build that scalably, right? So uh fundamentally, all the way from our model foundation uh to all our agent architectures uh that can scalably be deployed across all of our businesses. We have 70 of our businesses. Um so, for example, uh this year um we already uh we've already launched eight agents and 11 agents to come uh across different businesses of Rakuten.
Vasanth Raju 4:11
Yeah. uh our our AI uh powered customer service tool uh that we're deploying across 11 businesses or 10 businesses. Um and we are expected to basically realize a cost savings of over about 29 million dollars from this uh in 2026 alone, right? Uh so that's what we call an example of scaled deployment of AI rather than looking at AI as fundamentally just one agent here and one agent there. Uh we want to unify the architecture of data and agents and then deploy that across all our businesses and especially in use cases where we can realize a lot of value, uh whether it's cost savings or uh revenue addition.

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