PARTNER CONTENT: Every enterprise sector will eventually use artificial intelligence (AI) if they do not already, EIU analyst Dexter Thillien predicted, as he pointed to the vast potential for operators combining AI with mobile connectivity in the 5G era and beyond.

Speaking in the WinWin Live extended reality studio, lead analyst of technology and telecoms at EIU, Dexter Thillien indicated just as every enterprise segment has been using the internet and cloud services, eventually this will extend into AI.

In terms of more traditional forms of AI technology, rather than the currently popular and highly hyped generative flavour, he highlighted work by players in multiple sectors across a number of years on applications already making an impact.

Here, the expert pointed to use of: predictive analysis and logistics in agriculture and retail; fraud detection within financial services; use for healthcare R&D; manufacturing benefits enjoyed by automotive players; and smart grids in the energy sector.

Telecoms itself was also cited as a major user of AI technology for predictive maintenance, incident response, network optimisation, traffic management, security and in some cases radio asset planning.

“If you start adding connectivity to AI, including 5G, I believe it can supercharge its potential,” the analyst enthused.

As an example, he explained “if you combine real-time sensor data and visual analytics data from drones, AI can provide farmers with the forward guidance to improve crop yield prediction and also to detect pest and disease infections”.

For the automotive industry while “AI is used for vehicle design, workflow solutions and robotics at many production lines” it can also “power in-vehicle infotainment systems enabling navigation and security through biometric recognition for insurers”.

Generative AI
In terms of generative AI, the analyst indicated many companies have piloted the technology, though few had scaled to a complete solution.

Deployments of this form of AI, the EIU notes, currently fall under three main use cases: operational efficiency, developing new revenue streams and improving customer service.

The latter Thillien described as “probably the most interesting,” citing the ability to create “better client-facing customer experiences” which can be bolstered by connectivity.

In the automotive sector, he noted, “some companies have been using generative AI to launch a chatbot within the vehicle that allows the driver to control various features with their voice: the infotainment system, navigation system and air conditioning system, in a sense improving the driving experience”.

Operator opportunity
Moving forward he expects much greater integration between mobile connectivity and AI to aid third parties, for example in manufacturing where he anticipates increasingly AI-driven sensors and other IoT kit.

Thillien said greater use of AI is expected to “help operators improve their offerings in terms of private networks, potentially the rollout of small cells and also the development of fixed wireless services”.

As for the scale of the opportunity ahead, he noted “something to bear in mind is that we are very, very early in terms of adoption”.

For operators themselves he expects both “internal and external changes” in this mobile AI era.

Internally, he pointed to improved network slicing impact and use of genAI for better customer service chatbots, aiding staff, security and network management. Sustainability was also cited, with AI able to “help in designing the best possible network in terms of energy usage and making sure the highest quality of service is available”.

“You can even imagine that AI could automatically heal a network. Maybe that sounds a bit like science fiction, but in a virtualized world that could happen as well,” he added.

In the consumer segment, the analyst said “the combination of AI and telecoms can give users a much more interactive and immersive experience”.

“Operators can also use generative AI to offer different products and services in many different languages and I think in some parts of the world that’s going to be very interesting in terms of increasing and improving their addressable market going forward”.

Network challenge
One of the potential challenges highlighted for this mobile AI era is traffic management with audio and video applications, and potentially wider adoption of smart eyewear, likely to have a knock-on effect on demand.

“This increased traffic will obviously impact the network, especially if most of the data goes to the cloud because customers are going to be expecting the lowest latency possible and won’t really care whether it goes to the cloud or not,” he said.

“Upgrading the network to meet such demand will be critical, as well as improving capabilities at the edge which will lower the amount of traffic going back and forth between the data center and the consumer”.

For some countries and companies being more advanced or offering more products and services, for example, network operators in China and the Middle East have already launched 5.5G networks, “I think it’s very good to see what can be done, what can happen, and obviously for companies which are maybe a bit behind to learn and to decide what they can implement within their own market and what they can offer for their own consumers going forward,” Thillien stated.

Critical move

Concluding, he urged operators to move “beyond pure connectivity,” describing connectivity as “still critical” but “no longer enough”.

“You need other services added to the proposition. That means carriers will need to either provide new services from scratch, or more likely, have to partner with a bunch of other companies specialising in different segments, which can provide a full solution”.

“Operators traditionally have good relationships with the end-clients, the customers or even the enterprises and they work with them for years,” he added. “That puts them in a very good position to offer compelling new products and services to these clients”.