Posted by: Angus Ward
As expected, AI dominated the conversation at Mobile World Congress (MWC) 2024. On opening day, five global carriers announced the Global Telco AI Alliance, a joint venture to develop large-scale language models (LLMs) specifically to meet the needs of carriers. This could be revenue-singing for the parties involved, as there is a commercial benefit and an opportunity to not hand over control of AI workloads to hyperscalers. Elsewhere, the showroom floor was littered with stories about AI-powered services that could lift the industry out of its identity crisis.
The telecommunications industry faces significant pressure to drive innovation and efficiency as it grapples with growth challenges. The impact of AI has never been greater, delivering lower operational costs, improving customer journeys, and defining new revenue streams in non-traditional communications markets. But what most companies touting AI solutions at MWC don't admit is that they're all just concepts. Few of them are ready for “prime time”. That's because training AI solutions requires time and customer data. My estimate is that he needs 2 years and 30 customer datasets. What we really saw from the industry was more of a statement of intent than a readiness to initiate use cases.
What's interesting about the current state of AI is that there are still so many unknowns and unexplored parts. The potential applications seem almost limitless, which highlights how important it is for communications service providers (CSPs) looking to establish AI leadership to embrace the concept. At the end of the day, AI isn't something you buy; it's something you build together.
There is no one-size-fits-all solution, so solutions to customer problems are not always prescribed. Every situation is different, and it is difficult for one company to provide all remedies. But AI brings breakthroughs. This is more automation combined with faster and more intelligent decision-making capabilities. This opens the door for CSPs and their customers to explore deeper into the problems they are trying to solve and deliver more meaningful solutions.
Fundamentally, AI is a means to an end, not the end game. For CSPs, that purpose is expressed by eliminating inefficiencies and leveraging technology to deliver more accurate and relevant solutions that meet customer, partner, and business objectives. Efficiency is currently the main focus, but AI is actually about achieving it. This allows CSPs to go places they could not go before due to a lack of skilled talent or a deep understanding of the vertical market. From now on, they will become ecosystem orchestrators who can earn his long-awaited B2B revenue and finally be able to step into new industries.
To put this in perspective, AI offers countless benefits for CSPs who are concerned about monetization and achieving ROI from their 5G and IoT business investments. Let's frame it in the context of the agricultural sector. Farmers are keen to adopt new technologies and modernize their operations to balance the growing demand for food production with sustainable practices. The implementation of this technology in agriculture is sometimes referred to as “precision farming.” However, its integration faces many challenges regarding the introduction of advanced technologies. These include existing infrastructure, lack of technology maturity, lack of means of integration with existing agricultural practices, and limited general availability of customized agricultural technology solutions available through CSP. .
No, AI will not immediately solve these problems on its own. However, when combined with several other components, CSP becomes (in this scenario) a very powerful tool that can help accelerate the availability of precision agriculture solutions. CSPs are developing the provision of such services for vertical sectors through a combination of building a partner ecosystem and redesigning themselves as platform businesses that offer digital services from one central marketplace owned by telcos. I've been working on it for several years. CSP combines the high-bandwidth and low-latency capabilities of 5G with multi-access edge computing to deliver real-time data processing and specialized solutions from partners offering things like drone and robotics technology. However, the clarity of specific use cases may still be unclear.
AI can take things a step further and complete puzzles. It provides critical assistance in identifying solutions for tasks such as crop monitoring, disease detection, and automation of routine tasks such as irrigation and weeding. CSP can:
