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When promoting the adoption of Generative Artificial Intelligence (GenAI), telecom companies should look for use cases that truly add value, otherwise they could be faced with having to deal with upcoming problems.
Noting that artificial intelligence just isn’t a brand new technology for telecommunications companies, GSMA Intelligence chief Peter Jarich said GenAI has grow to be the lexicon largely since it has democratized using such tools and generated widespread interest in them.
The key query now’s how telecommunications should benefit from these recent opportunities. He pointed to 5G, which is the fastest-growing mobile technology, but has not proven to be as effective in increasing operators’ profits and revenues. This is the explanation why a lot discussion is revolving around monetizing 5G and leveraging its capabilities to provide useful services.
He further noted that interest in GenAI amongst operators stays low – 56% continues to be within the testing phase, and the variety of commercial implementations is low.
While there are valid reasons for operators to crawl – because they operate networks that support critical infrastructure and must consider regulatory implications within the event of outages – the challenge now is determining how to get them beyond the GenAI testing phase and into commercial launch, he said.
There’s a lot hype around GenAI that telecommunications companies need to sift through the noise and determine how to leverage the technology to deliver real value, said Jarich, who spoke to ZDNET ahead of this week’s Mobile World Congress (MWC) in Barcelona. Spain.
The biggest obstacles operators face are unclear return on investment (ROI) and technology maturity. He urged the industry to discover a possible GenAI proof of concept that would generate revenue and establish one to two compelling use cases.
Currently, there are a lot of players demanding market share and offering a wide selection of products, including various chips and AI features. Tying GenAI to anything as a part of a marketing slogan could end in consumer disappointment if the services don’t provide any real value, he said.
Therefore, the industry must watch out when selecting GenAI or risk losing customer confidence within the technology, Jarich said. He emphasized the necessity for a transparent message and basic knowledge about available tools.
The give attention to GenAI and broader AI must be on reducing operational costs and providing a greater customer experience. He noted that operators will want to use these tools to develop recent services that may add value and construct stronger connections with consumers.
He added that there has also been a push amongst device makers resembling Samsung and Google to offer phones with artificial intelligence. With smartphone sales stabilizing or declining, these market players had to look for ways to encourage consumers to purchase recent models. This led, for example, to the introduction of foldable vehicles, he added.
He added that they now expect GenAI to do the identical, resembling improving search and adding more useful features.
This will increase the necessity for open APIs to enable developers to construct GenAI tools that leverage 5G capabilities, including low latency, which can further enable recent 5G use cases and drive demand and traffic, he said.
GSMA predicts that the variety of 5G connections will increase from 1.6 billion to 2.1 billion by the tip of 2024.
Jarich noted that use cases may vary by region and market, providing further opportunities for local telcos to capture recent revenues. And since most GenAI services are cloud-based, operators can play a differentiating role in facilitating them. For example, they’ll provide support for edge computing, which can be essential for some GenAI services resembling real-time language translation and smaller large language models (LLMs) that will be hosted on the device.
Dedicated basic model for telecommunications companies
Domain-specific LLMs are also provided to help discover GenAI use cases specific to the needs of a selected sector, resembling finance or healthcare.
This week, Huawei launched an entry-level telecommunications model that it says operators can use to improve operational efficiency and optimize network productivity. Its telecommunications model includes two key applications: role-based co-pilots and scenario-based calling agents, Huawei board member and president of ICT products and solutions Yang Chaobin said on the sidelines of MWC.
The artificial intelligence model enables natural language interactions for various roles and scenarios, analyzing complex processes and coordinating operations to provide higher customer support, Yang said. They are tailored to roles resembling network optimization agent, user support agents, and error management.
He added that the entry-level model may power autonomous networks, providing telecom operators with three core functions, including service delivery and network maintenance.
Telecommunications companies consider that autonomous networks combined with technologies resembling artificial intelligence, big data, cloud and edge computing can deliver services faster, at lower costs and which are easier to deploy and manage. For example, TM Forum is leading an autonomous networks project that goals to define fully automated networks for vertical industries, enabling “self-configuration, self-healing, self-optimization and self-development” of telecommunications networks.
Stressing the importance of automation, Yang noted that carriers are facing rising operational costs (operating expenses), which have risen to about 70% of revenues. Software-defined and autonomous networks can assist alleviate these cost pressures, he said.
He added that Huawei’s telecom foundation model can support service delivery use cases where administrators can access “accurate multimodal assessment and rapid service delivery.” The AI model’s optimization capabilities further facilitate user-experience use cases, and cross-process evaluation and dialog-based support can improve troubleshooting cases, he said.
As data is increasingly utilized in artificial intelligence applications, Jarich said data security can be a serious concern and operators can play a task in managing user data. They can even need to ensure that their networks can cope with growing traffic as using GenAI-generated content and services increases, he noted.
And with the extensive data they have already got on their customers, telecommunications companies can leverage artificial intelligence to manage tailored services and higher deliver services that meet a user’s specific needs, he said. He added that it is a lesson they’ll draw from their experiences with 5G.
With core models and GenAI providing a “new level of intelligence,” Huawei Cloud CTO Bruno Zhang said companies will increasingly use AI-generated content in production and to support software engineering. Building your personal core models can be a challenge, nonetheless, because they require “systematic innovation,” Zhang said on the Chinese vendor’s cloud summit, held alongside MWC.
Huawei hopes to help by offering basic application-enabled AI models in addition to its own cloud services, he said. The Chinese tech giant also goals to facilitate AI adoption by providing key components including native AI storage and AI-powered data.
He noted that Huawei’s Pangu LLM system, released last yr, features industry-specific models trained with industry data and provides industry-specific scenarios and tasks, including autonomous driving and weather forecasting.
Singapore-based Eileen Yu reported for ZDNET on the Mobile World Congress 2024 in Barcelona, Spain, on the invitation of Huawei Technologies.
Credit : www.zdnet.com
