According to Nokia, communications networks are critical drivers of artificial intelligence (AI) innovation and success. They unlock the potential of AI applications by enabling seamless data transmission between devices, cloud platforms, data centers, and edge infrastructure.
As industries such as manufacturing, education, finance, healthcare, transport and government embrace AI-driven mission-critical services, they need robust connectivity to make sure these services can function efficiently.
This creates significant opportunities for service providers, Nokia said. By building an AI-optimized network infrastructure, you can develop new revenue-generating services, such as network slicing, that cater to specific industry needs.
Nokia says that service providers are turning to AI to simplify network operations, optimize performance, improve security, reduce energy consumption, and predict and prevent downtime.
AI is a key enabler of autonomous networks, as envisioned and defined by TM Forum, which can self-configure, self-optimize and self-heal with minimal human intervention. At the highest levels of autonomy, AI plays a crucial role by enabling the network to manage complex operations, adapt to changes and ensure continuous performance optimization all on its own.
Nokia announced in November this year a reorganization of its business into two primary operating segments, which will take effect on January 1, 2026. More on this can be read here.
Also Read: Nokia Unveils Strategic Overhaul to Lead AI-Driven Network Era and Capture Value From AI Supercycle
What They Said: Timeline
November 2025:
Capital Markets Day 2025
During Nokia’s Capital Markets Day 2025 webcast, Pallavi shared insights on AI-native networks. She said: “As a technologist, I have a strong eye of spotting when the next wave of disruption is going to hit, ride that wave and then be the disruptor. I was born doing networking. And then a decade back, I moved to go back and build the compute for the AI infrastructure, started with the cloud, then to the edge and then to the data center.”
“Now as I have been building the AI infrastructure, I can now see that the next wave of disruption is coming. And this time, it is going to disrupt the networks. Fundamentally, if you look at it, the AI supercycle, it has put an exponential growth on the demands of these networks. Now whether it is latency, whether it is capacity, whether it’s bandwidth, whether it’s reliability. And these metrics, they’ve always been vital. But today, they are increasingly becoming critical in scale and in urgency because this demands a new kind of network, networks that connect intelligence and networks that become smarter by using that intelligence. And Nokia is the only Western company which has a comprehensive portfolio, spanning radio, core, access, transport, IP, all the way up to the cloud, uniquely positioned to shape and deliver the networks of today and tomorrow. And this is why I’m so excited to have joined Nokia as the Chief Technology and AI Officer.”
From Cloud to Agentic AI
Explaining the evolutions of networks toward cloud and AI, she said:
“ChatGPT, I think it started with about 117 million parameters. And today, it’s close to about 2 trillion parameters. And today, we have entered the world of agentic AI. This is where intelligent agents interact, and there’s massive machine-to-machine chatter. Now if you see, we’ve had massive technology disruptions in such a short span of time. And the key to this transformation was actually fueled by open ecosystems, open data, open framework, open models because openness fosters innovation and collaboration.”
Physical AI: Where Milliseconds Mean Safety
“Now throughout this AI supercycle, networks have been foundational and networks have also gone about and changed, whether you’re talking about scaling up for machine learning, whether we are talking about scaling out for generative AI or we are talking about scaling across for agentic AI. But now there is another disruption waiting to happen in this AI supercycle. And I can actually see it coming because AI is now on the cusp of the next wave of transformation, which is physical AI. This is where the boundaries of the physical and the digital worlds are going to get blurred,” she continued.
“Now think about it. This is the autonomous vehicles, drones, AR/VR glasses, intelligent factories, health care. This is the world where critical essential services will demand that the network should always be on, where subsplit second decisions need to be made and every millisecond matters. And with physical AI, we will have robots standing hand-to-hand with humans, with heavy machinery. And now just imagine that these robots, the safety and the motion control loops that they need, they need decisions to be taken in the matter of microseconds. Now one network slip and the robot can actually miss a safety stop. So in these environments, it’s about safety.”
“Gen AI was 3 years back. 2025 is the year of agentic AI. And now I can clearly see that physical AI is knocking at our doors. And this evolution of AI will exponentially change the dimensions of the network themselves. Now whether it is bandwidth, whether it is capacity, whether it is latency, whether it is reliability, all of these KPIs are changing with AI.”
Showcasing a demo example, she said:
“The traffic is bursty, the traffic is unpredictable. And what you also see in here is that the uplink traffic is higher than the downlink traffic. In fact, my teams in Bell Labs are predicting that in the new world, today, the downlink to uplink ratio is 12:1, and it’s going to move to 4:1. And we are seeing more and more AI-native traffic originating from mobile devices, 48 percent of ChatGPT, 61 percent of Gemini’s AI traffic is originating from mobile devices.”
“What we just saw was just 1 AR experience on one device. Tomorrow, the connected landscape will look radically different. AR glasses are going to be common, as common as smartphones. We will be using them for navigation, for shopping, for translation. 50 percent of autonomous vehicles will be driving by themselves. Tens of thousands of robots will be delivering parcels. AI agents will be there in every store for pricing, for merchandising, for better customer engagement. And then think about all the city edge AI factories that will be orchestrating traffic, energy, logistics, all in real time.”
“Today’s networks, they deliver 99.999%. Now what does 99.999% mean? It means that the networks — there could be minutes of downtime in a year. But we were talking about robots on a factory. When robots on a factory floor are working hand-in-hand with humans, the downtime has to shrink to seconds. And we are now starting to talk about 99.9999%. 99.9999% reliability because one missed safety signal can cause an accident.”
“Now let’s look at bandwidth. We talked about – we showed you an AR/VR example. We have so much of AI inferencing that is happening. And all of this – because of this, the bandwidth has already jumped 7x to 400 gigs per port. But tomorrow’s network, they need terabit class capacity to feed these giant AI models and real-time video streams. Now think about all the AR glasses that are going to render 3D environments, autonomous vehicles, all of them streaming sensor data at the same time.”
“And now let’s look at the third metric, which is latency. Today, latency is about 10 to 20 milliseconds, and that works well for video calls. But imagine, once again, the robots in a factory floor, when they are making safety decisions, we are talking of sub-millisecond latency. And when you look at these numbers, you might feel like, okay, these are some small jumps that we are talking about. But as a technologist, having done this in my life, I can tell you that in order to make these leaps, it is a lot of hard work and a lot of research and development that goes in order to make it happen. Because when the industry moved from 9.99% to 99.999%, it took us a lot of work. And now we are pushing even further to get these networks ready for AI-native traffic.”
Speaking about the core network, which is cloud-native and hardware-independent, she said the team is making it more AI-native:
“Team is working on making it more AI native because in the world of AI applications, in the world of AR devices, in the world of robots, they are not going to speak 3GPP. So we are evolving the core beyond the traditional boundaries, making it programmable, making it agentic, making it service aware, making it ready for AI-native functions, functions like real-time translation, fraud detection and much more.”
She added:
“The KPIs that the networks of the future demand is very hard. And that is why myself, as the Chief Technology and AI Officer, I’m hyper-focused on taking all of Nokia’s differentiating assets and doing the hard thing, which is harnessing the rich data, the deep insights and the domain expertise that we have built over years and bringing AI into the protocols and the algorithms that made these networks happen. Now in short, what I’m talking about is that the networks that have powered AI are now going to become more intelligent by using AI.”
Building Autonomous, Anticipatory Networks with AI
Introducing WaveSuite, a software application layer, she said:
“Now we are starting to talk about networks that just do not react. These are networks that are now anticipating. In fact, in a live trial with du in the UAE, we saw that by using this, the optimized performance modeling, it cuts the planning time in half, and it actually improved the design efficacy by 30%.”
She concluded:
“Our pursuit is simple. We will use every ounce of intelligence available to us, our assets, our data, our domain expertise and our partnership, our deep partnership with telcos and hyperscalers to build networks for the new era of AI-native traffic, networks that just don’t carry intelligence, but networks that continuously learn, adapt, protect and improve. And as we build these networks, we will partner with the best-in-breed partners.”
“We will partner with folks in silicon, with folks in software, with folks in platforms to help our customers unlock their next wave of growth.”
Also Read: What They Said: Puneet Chandok of Microsoft on AI
December 2025:
New research commissioned by Nokia, surveying more than 2,000 technology and business decision-makers in the U.S. and Europe, shows strong demand for AI solutions – and a clear industry consensus that connectivity and network infrastructure must evolve to support the next wave of AI growth, Nokia said in a statement on December 16, 2025.
While the U.S. continues to lead global AI deployment and mass-market adoption, 88% of U.S. respondents expressed concern that the expansion of network infrastructure may not keep pace with AI investment. In Europe, 86% of enterprise respondents said current networks are not yet equipped to handle widespread AI adoption. Two-thirds of those surveyed said they already have AI in live use, and more than half have already experienced challenges such as downtime, latency, and throughput constraints associated with increasing data demands.
“The first wave of the AI supercycle has already reshaped industries and accelerated innovation,” said Mahajan while releasing the new study by Nokia. “This research shows a clear understanding across the ecosystem that future waves will demand more advanced, AI-native networks and substantial investment to strengthen network requirements. Connectivity, capacity, and low-latency performance are becoming ever more essential ingredients for transforming how devices interact, industries operate, and people live and experience technology as AI moves forward.”
The research comprises two reports: Infrastructure First Is the New America First (U.S.) and AI Is Too Big for the European Internet (Europe).
In an article titled Advancing Connectivity in the AI Era, dated December 16, 2025, Mahajan wrote: “The AI supercycle has begun, and much like the Internet revolution, it is fundamentally reshaping the role of connectivity and how we use and experience technology. It is also changing the traffic patterns in telecommunications networks.”
“At Nokia, we believe that secure, advanced connectivity infrastructure is an integral enabler of AI innovation, connecting intelligence across the world’s devices, the network edge and data centers. We are collaborating closely with our strategic partners and customers to drive the convergence of AI and radio access networks, capturing the benefits of AI.”
She reiterated that 88% of U.S. telecommunications providers and enterprises and 78% of European respondents see connectivity and infrastructure as the biggest barriers to scaling AI.
AI-RAN, Nvidia, and the Road to 6G
In October 2025, Nvidia and Nokia announced a strategic partnership to add Nvidia-powered AI-RAN products to Nokia’s RAN portfolio. Nvidia also announced a USD 1 billion investment in Nokia to accelerate AI-RAN innovation and the transition from 5G to 6G.
T-Mobile U.S. is working with Nokia and Nvidia to integrate AI-RAN technologies into its 6G development process. Trials are expected to begin in 2026, focused on field validation of performance and efficiency gains for customers. The move will enable massive improvements in performance and efficiency, helping ensure that consumers using generative, agentic and physical AI applications on their devices will have seamless network experiences. It will also support future AI-native devices, such as drones or augmented- and virtual-reality glasses while being ready for 6G applications such as integrated sensing and communications, Nokia said.
Also Read: What They Said: Jamie Dimon of JPMorganChase on AI
Commenting on the partnership (Nokia and Nvidia), Mahajan said Nokia is bringing the AI-RAN vision to life: “Our AI-RAN solution, powered by the Nvidia ARC-Pro computing platform and Nokia anyRAN software, enables RAN and AI workloads to run on a shared, GPU-accelerated platform, supporting software-defined RAN evolution,” she said.
“Physical AI systems, such as robotic AI, autonomous vehicles, and advanced devices that enable immersive experiences, will demand ultra-low latency and massive uplink capacity. Networks will need to respond in milliseconds and in the next phase, even less than one millisecond, to enable real-time communications,” she highlighted, noting that “Nokia has a key role in developing AI-native 6G architecture, which will be crucial for making these capabilities a reality.”
Once-in-a-Generation Opportunity for Connectivity
Mahajan concluded: “The AI supercycle is a once-in-a-generation opportunity. To ensure that connectivity does not become the bottleneck for AI innovation, we need close collaboration and co-innovation across the industry ecosystem.”
This is a developing story, and more quotes and insights from Pallavi Mahajan will be added as they become available.
A small group of TelecomTalk readers helps keep this platform running. Support us if you find our work valuable.
Support Telecomtalk
