- Nokia Bell Labs and e&, a UAE telecom operator, are collaborating to develop AI use cases on industrial networks
- The collaboration will explore immediate AI opportunities including worker safety and health
- Another key focus of the AI partnership is environmental monitoring
More applications are cropping up to show us what’s possible when artificial intelligence (AI) goes beyond buzzwords and starts solving real-world problems. And all players — telco operators, enterprises, vendors — stand to benefit. In addition, even though AI is generally thought of as bad for the environment, it could also have a positive impact by optimizing digital processes and energy usage.
A new research and development deal between Nokia Bell Labs and e&, a UAE state-owned telecom operator, serves as the latest example of this. By integrating Nokia’s AI research with e&’s network, the two are collaborating to create AI use cases that could transform industrial sectors.
While specific use cases haven’t been finalized yet, Nokia and e& are evaluating opportunities related to “worker safety and health,” as well as “environmental monitoring,” said Thierry Klein, president of Solutions Research at Nokia Bell Labs.
Klein noted AI can create digital representations of physical operations by using network data, otherwise known as digital twins, for better understanding and optimizations of industrial environments. “AI is critical in creating this bridge between the physical and the digital worlds,” he told Fierce Network.
To date, there is a “significant challenge for any enterprise in leveraging AI effectively,” said Eric Hanselman, chief research analyst for TMT at S&P Global Market Intelligence. Many organizations could benefit from any opportunity where AI-based optimizations can be put to work across infrastructure, rather than integrated into individual products or services.
Working with a telco operator like e& to harness the operational data generated by the network that interconnects an industrial facility offers a “unique value,” Hanselman told Fierce. Rather than simply putting AI to work in an environment, it’s creating the source of operational telemetry, creating potential to “significantly expand operational visibility.”
Industrial AI as a telco play
Nokia is largely looking at this partnership from an enterprise and industrial perspective. “We are very much focused on the application of AI technologies to solve enterprise and business challenges in a variety of different vertical sectors,” Klein said.
But that doesn’t mean there isn’t huge opportunity for e&, and telcos in general, when it comes to integrating AI across their industrial networks.
As AI becomes increasingly important for network optimization and improving customer experiences, partnerships with companies like Nokia, that have extensive automation tools and research, can open up new avenues for telcos.
For example, Hanselman mentioned that logistics and fleet operations could be AI’s low-hanging fruit in the near term, offering telcos an immediate avenue for adding value through AI-driven network enhancements. While the long-term potential of industrial automation is also there, these shorter-term applications could give operators the breathing room they need to scale up AI initiatives.
“Industrial applications are longer term opportunities with significant potential,” he said. “Realizing the benefits will take time, but there is value in the near-term visibility that it provides.”
Can AI really reduce carbon emissions?
A cornerstone of Nokia’s collaboration with e& is reducing carbon footprints and increasing the sustainability and resilience of industrial operations. Specifically, it promises to get e& closer to its ambition of reaching net-zero status in the UAE by 2030.
The question is, how much of a difference can AI really make when it comes to sustainability?
According to Hanselman, the potential for AI to contribute to net-zero goals is promising, especially in industrial settings, where processes are less digitized compared to most other telecom operations that are already well-optimized. “There’s the potential for AI to provide incremental improvements in both telecom and industrial environments, with the greater promise in industrial,” Hanselman said.
“There’s room for optimization and most of this is in reducing energy demand growth as networks become denser. On the industrial side, there’s more opportunity to optimize processes that have been more gradual in digitization.”