At the forefront of artificial intelligence innovation is the critical balance between strategic implementation and investment returns, as industries worldwide pivot to harness the transformative power of both large and small language models.

“There is a massive interest in AI — we’ve come from 2023, where there was a lot of understanding about what’s going on with large language models,” said Stephen Rose (pictured), general manager of global industries at IBM. “I think people trying to get their heads around that. They’re trying to understand what is the efficacy of the use cases, what’s the strategic considerations around the implementation of the technology and particularly what’s the cost to do so. What’s the return on invested capital for those things.”

Rose spoke with theCUBE Research analysts Dave Vellante, John Furrier and Shelly Kramer at MWC Barcelona, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how AI is revolutionizing industries, with a focus on using AI for growth opportunities, real-time data analysis, and the culture shift around early use cases. (* Disclosure below.)

AI and how telco operators are changing their go-to-market approach

Telco operators are shifting their mindset to address the enterprise market and are recognizing the need to become more sophisticated in their go-to-market approach, according to Rose. The focus is shifting from cost control to using AI to create growth opportunities and changing mindset and KPIs accordingly.

Real-time data analysis is changing the way operations are done, providing insight into customer sentiment and allowing for a digital representation of a business, according to Rose. AI is transforming customer care, for example, by providing real-time tonality and language analysis to assist agents in handling calls and providing historical experience and network data.

“You get a lot of information through a chatbot. But, actually, if you’re a customer care agent and you do receive a call, imagine if you’re that agent and the AI is actually starting to infer and tell you in real-time, or very near real time, what is the tonality it can observe,” Rose said. “What is the tonality in that call? What is the language being used? Then it can actually suggest to you what types of next best action you should be taking as a care agent.”

Large language models can be applied to various business use cases, but the challenge lies in running specialty models and integrating them with other models. Organizations should focus on quickly implementing new use cases and determining whether to buy, build or borrow models, as creating large parameter models can be costly, according to Rose.

“What people are starting to understand is how do I take a large language model and apply that to within use cases to my business — and to what extent am I ready to run those types of use cases,” Rose said. “Where maybe the data lineage is not the same confidence I get on a model that I own with my own propriety data. That might be a small language model at the edge. I’m much more in control of that.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of MWC Barcelona:

(* Disclosure: TheCUBE is a paid media partner for the MWC Barcelona event. No sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE