Smarter Networks, Better Service: AI in Telecom

Nearly half of telecom executives see artificial intelligence (AI) as one of the industry’s most transformative technologies in the next five years, yet 68 percent feel their organization is struggling to keep pace with rapidly evolving technologies and customer needs, according to a 2024 MeriTalk study commissioned by Dell Technologies.

In a recent interview with MeriTalk, Manish Singh, chief technology officer, telecom systems business, at Dell Technologies, and Ronnie Vasishta, senior vice president, telecom, at NVIDIA, discussed how communications service providers (CSPs) are addressing these challenges by bringing together infrastructure, services, software, and silicon from across the ecosystem to deliver AI throughout their networks.

MeriTalk: During the past year, how has AI impacted infrastructure, operations and services for telecommunications companies?

Vasishta: We’ve observed a significant increase in AI adoption by communications service providers, with many moving from proofs of concept to tangible customer service management deployments. In NVIDIA’s 2025 State of AI in Telecom report, 44% of respondents said they’re investing in AI for customer experience optimization and 40% said they’re deploying AI into their network planning and operations. We are also seeing broad AI infrastructure deployment to support generative AI (GenAI), and telecom companies will play a very important role in building and deploying that infrastructure. We have already seen over 15 telecom companies worldwide becoming NVIDIA Cloud Partners (NCPs) to build and deploy revenue generating AI factories in their regions that services the growing need from startups, enterprises, governments, and researchers.

Singh: The pace is picking up as CSPs are adopting AI. Three trends I see emerging are building capabilities to offer GPU-as-a-service or AI-as-a-service, bringing AI capabilities closer to where the data resides (the edge) and driving more automation for the lifecycle management of the network itself.

MeriTalk: It sounds like some of the most impactful opportunities for AI in telecommunications right now are around customer service and network operations. Do you have some early success stories?

Singh: Telecommunications companies are now starting to leverage the power of large language models (LLMs) for customer care by implementing GenAI-powered chat agents that understand the intent and the context of the customer, delivering a better experience. GenAI is very good at understanding intent, predicting churn and initiating mitigation plans accordingly. We worked with SK Telecom to take this a step further to offer new plans or new devices based on the customer’s intent.

Vasishta: We’re working with independent software vendors, global system integrators and telecommunications companies to deploy AI solutions that enhance customer experience. For example, we’re collaborating with Amdocs on its amAIz platform for GenAI-powered billing, which can analyze real-time data to offer personalized billing options, anticipate customer needs, and resolve issues proactively.

For network operations, we have partners, including ServiceNow, that have developed AI-powered service ticket solutions that enable telecom customers to deploy customized systems that generate more insightful service tickets, accelerating problem resolution across the network.

We also have CSP customers using accelerated computing for routing field technicians to quickly troubleshoot and repair network infrastructure. This approach is significantly faster, leading to a much more efficient fleet management system for CSPs.

MeriTalk: We’re observing that successful AI deployments are enabled by a comprehensive ecosystem. To support AI applications across diverse network environments, how can CSPs find the right partners to collaborate with?

Singh: In partnership with NVIDIA, we’re constructing a curated ecosystem tailored to telecommunications providers, facilitating rapid deployment around AI use cases, and enabling optimized business outcomes. Our comprehensive suite of solutions, Dell AI for Telecom, simplifies and accelerates AI deployments for CSPs.

We’re forging strong partnerships with AI innovators. Ronnie mentioned Amdocs. We’re working with them on the amAIz platform, which is preloaded with GenAI use cases for telecom, designed to provide seamless support, manage billing inquiries, and facilitate conversational selling.

For network troubleshooting, our partnership with Kinetica makes it quicker and easier for CSPs to ingest, fuse and visualize network data for faster analysis and more timely decision-making.

We are continuing to expand our AI for Telecom ecosystem, announcing new partnerships that enable CSPs to seamlessly integrate AI into their networks. By combining our robust ecosystem with the Dell AI Factory with NVIDIA, we offer a comprehensive solution that includes hardware, software, and AI expertise. This integrated approach delivers significant benefits, including improved operational efficiency, enhanced reliability, cost savings, and new monetization opportunities for telecom providers.

MeriTalk: How do you foresee AI transforming telecommunications networks and services in the coming year?

Vasishta: A year is a long time in AI. The rapid evolution of GenAI, particularly its deployment closer to data at the edge, presents exciting opportunities for CSPs because they occupy the edge of the infrastructure and the edge of the network. CSPs can offer GenAI-driven network automation and customer care solutions. One example is a copilot model where GenAI assists network engineers and field technicians, driving productivity, reducing network downtime, and improving KPIs.

I think the deployment of GenAI in devices will rapidly accelerate. The integration of software-defined radio access networks with GenAI applications will obviously be beneficial to the telecom operators and the ecosystem. This will enable opportunities to deliver personalized AI assistants on smartphones and AI-powered applications for mixed reality headsets and glasses.

Singh: Over the next year or so, I see the rise of agents. The agentic frameworks are coming into play, driving more complex autonomy in terms of planning, reasoning, and execution.

In addition, I see the rise of sovereign GenAI transforming how applications and use cases are developed and experienced across country and cultural landscapes. Telecommunications companies are positioned to leverage LLMs and develop capabilities that include local languages, communication styles and cultural contexts, opening new revenue streams in the delivery of personalized digital experiences.

So, the future looks very exciting, whether you’re looking at it from offering sovereign AI capabilities to drive more full autonomy in terms of your network planning, network lifecycle management, network operations or enhancing customer expertise.