Like 5G, telcos must seek commercial use cases to move GenAI forward

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Like 5G, telcos must seek commercial use cases to move GenAI forward

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In driving the adoption of generative artificial intelligence (GenAI), telcos should seek out use cases that actually add value or they could face having to deal with issues ahead. 
Noting that AI isn’t a new technology for telcos, GSMA Intelligence’s head Peter Jarich said GenAI has become much of the lexicon because it democratized the use of such tools and driven widespread interest in them.
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The key question now is how telco should tap the new opportunities. He pointed to 5G, which has been the fastest-growing mobile technology but hasn’t been as successful in driving profits and revenue for operators. It is the reason so much discussion continues to revolve around the monetization of 5G and leveraging its capabilities to deliver services that are useful. 
He further noted that GenAI interest among operators remains low, with 56% still in the testing phase and the number of commercial deployments small. 
While there are valid reasons for operators to move slowly — since they run networks that support critical infrastructures and need to consider regulatory repercussions when there is a downtime — the challenge now is to look at how to move them beyond the GenAI testing phase and into commercial launch, he said. 
There also has been so much hype around GenAI that telcos need to sieve through the noise and figure out how they should leverage the technology to deliver real value, said Jarich, who was speaking to ZDNET ahead of this week’s Mobile World Congress (MWC) in Barcelona, Spain. 
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The biggest obstacles operators face are unclear returns on investment (ROI) and tech maturity. He urged the industry to identify potential GenAI proof of concepts that can generate revenue and establish one to two compelling use cases. 
There currently are multiple players clamoring for a share of the market and pushing a broad array of products, including different AI chips and functionalities. Linking GenAI to everything as a marketing tagline can result in disenchanted consumers if these services fail to deliver any actual value, he said. 
The industry, hence, needs to be careful about how it wants to pitch GenAI, or risk customers losing trust in the technology, Jarich said. He stressed the need for clear messaging and a basic understanding of the tools available. 
Focus on GenAI and the broader AI should be on decreasing operational costs and providing better customer support. He noted that operators will want to use these tools to devise new services that can drive value and build stronger connections with consumers.
There also has been a push among device manufacturers, such as Samsung and Google, to offer AI-powered handsets, he added. With smartphone sales plateauing or on the decline, these market players had to look at ways to entice consumers to buy new models. This had led to the introduction of foldables, for example, he said. 
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They now are looking to GenAI to do the same, such as improving search and including more useful features, he added.
It will drive the need for open APIs to enable developers to build GenAI tools that leverage 5G capabilities, including low latency, further pushing new use cases for 5G and fueling demand and traffic, he said. 
GSMA projects that 5G connections will grow from 1.6 billion to 2.1 billion by the end of 2024. 
Jarich noted that use cases can differ for regions and markets, giving local telcos further opportunities to find new revenue. And with most GenAI services running on the cloud, operators can play a differentiating role in facilitating these. For instance, they can provide support for edge computing, which will be important for some GenAI services such as real-time language translation and smaller large language models (LLMs) that can be hosted on the device. 
Domain-specific LLMs also are being made available to help identify GenAI use cases specific to the needs of a particular sector, such as financial or healthcare. 
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Huawei this week launched a telecom foundation model it said carriers can use to improve operational efficiencies and optimize network productivity. Its Telecom Foundation Model covers two key applications: Role-based copilots and scenario-based call agents, said Huawei’s board member and president of ICT products and solutions Yang Chaobin, on the sidelines of MWC. 
The AI model powers natural language interactions for different roles and scenarios, analyzing complex processes and orchestrating operations to deliver better customer experience, Yang said. These are customized for roles such as network optimization agent, user experience agents, and fault management. 
He added that the foundation model also can power autonomous networks, providing three core capabilities for telcos, including service provisioning and network maintenance. 
Telcos believe autonomous networks, coupled with technologies such as AI, big data, cloud, and edge computing can deliver services more quickly, at lower costs, and that are simpler to roll out and manage. TM Forum, for instance, runs an Autonomous Networks Project that aims to define fully automated networks for vertical industries, enabling “self-configuration, self-healing, self-optimizing and self-evolving” telecom networks.
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Stressing the importance of automation, Yang noted carriers have been faced with growing Opex (operating expenditure), which has climbed to some 70% against the ratio to revenue. Software-defined and autonomous networks can help alleviate these cost pressures, he said. 
He added that Huawei’s Telecom Foundation Model can power service provisioning use cases, in which administrators can access “accurate multi-modal assessment and quick service provisioning.” The AI model’s optimization capabilities further facilitate user experience assurance use cases, while its cross-process analysis and dialog-based support can enhance troubleshooting cases, he said. 
As data is increasingly leveraged in AI applications, Jarich said data security will be a big focus and operators can play a role in being stewards of users’ data. They also will need to ensure their networks can cope with the growing traffic as the adoption of GenAI-generated content and services climbs, he noted. 
And with the vast data they already have on their customers, telcos can tap AI to manage bespoke services and better provide services that cater to a user’s specific needs, he said. That is the lesson they can take away from their experience with 5G, he added.
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With foundation models and GenAI driving “a new level of intelligence,” Huawei Cloud CTO Bruno Zhang said businesses increasingly will tap AI-generated content in production and to support software engineering. Building their own foundation models, however, will be challenging as these require “systematic innovation,” Zhang said at the Chinese vendor’s cloud summit, held alongside MWC. 
Huawei hopes to help by offering AI foundation models that power applications as well as its own cloud services, he said. The Chinese tech giant also aims to ease AI adoption by providing the key components, including AI-native storage and AI-powered data. 
He noted that Huawei’s Pangu LLM, released last year, contains industry-specific models, trained using industry data, and provides industry-specific industry scenarios and tasks, including autonomous driving and weather forecasting. 
Based in Singapore, Eileen Yu reported for ZDNET from Mobile World Congress 2024 in Barcelona, Spain, on the invitation of Huawei Technologies.  

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