Exploring the trends, challenges, and innovations from Mobile World Congress 2026, driving the next generation of intelligent, autonomous networks
This year’s most significant connectivity event, celebrating the 20th anniversary of Mobile World Congress (MWC), may be over now, but the technologies, themes, and challenges it highlighted will influence the mobile industry throughout the upcoming year.
As Vivek Badrinath, GSMA Director General, noted, “MWC26 has shown us what happens when the world’s brightest minds come together around genuinely hard problems, from open and inclusive AI and realizing the full potential of 5G, to keeping the world safe from the growing threat of fraud and cybercrime.”
With approximately 105,000 attendees from 207 countries and around 2,900 exhibitors, one theme stood out above the rest: a critical focus on the customer. Speaker after speaker emphasized that technology innovation must deliver real value to users, not just through features and performance, but in the most cost-efficient way possible. As John Stankey, CEO at AT&T, emphasized, “We should all be thinking, how do we bring that promise to our customers?” and “What do we think our customer wants?” By linking innovation directly to customer value and operational efficiency, operators can ensure that investments in next-generation networks also optimize total cost of ownership (TCO) and long-term business sustainability.
Below are some of the key takeaways from this year’s event:
Native AI Takes Center Stage
One concept that appeared everywhere at this year’s MWC was Native AI, or networks that are AI-native by design, rather than merely AI-enhanced. The industry is already shifting away from treating AI as a bolt-on capability or external tool toward embedding machine learning directly into the core network architecture and operational frameworks.
Across the show floor, AI was no longer presented as a simple decision-support tool, but as a foundation for autonomous operations, enabling capabilities such as predictive fault detection, intelligent resource allocation, and automated network optimization.
Several initiatives aimed at advancing AI-native telecom architectures were introduced during the event. TM Forum unveiled its AI-Native Blueprint, designed to help operators move AI from isolated pilots into production-grade operational deployments. The framework includes three initial projects: Models-as-a-Service (MODaaS), Data Products Lifecycle Management, and Agentic Interactions Security.
Meanwhile, the GSMA launched its Open Telco AIinitiative, focused on developing telecom-specific AI models trained on industry datasets, ensuring that frontier AI models are optimized to understand the complexity of network data and operations.
Industry leaders emphasized that AI must now move from experimentation to strategy. Bret Taylor, Chairman of OpenAI, highlighted the enormous opportunity ahead, suggesting that even if AI development were to pause today, trillions of dollars in value could still be realized across engineering, customer service, legal functions, and more.
However, building truly AI-native networks will require more than deploying new models. It will also demand breaking down the traditional silos that separate data, operations, and network domains. Only with unified data and operational visibility can networks deliver the performance, intelligence, and scale required to support an increasingly AI-driven digital ecosystem, from video and data to voice and beyond.
Data: The Foundation of the AI-Driven Network
Another topic that repeatedly surfaced across discussions at Mobile World Congress was data. Whether the conversation focused on AI-native networks or AI agents, the message was consistent: without the right data, AI simply cannot deliver value. As one speaker put it, “If the data isn’t there, the agent won’t work.”
The telecom industry is reaching a critical inflection point. Operators are generating enormous volumes of network telemetry and behavioral data, yet many still lack the ability to interpret and act on that data in real time.
Hiroshi Mikitani, Founder, Chairman, and CEO of Rakuten Group, emphasized that operators are sitting on a goldmine of data. In fact, he noted that telecom operators “have more data than Google” and should leverage that advantage to strengthen their AI capabilities. At Rakuten Group, data from across mobile services is aggregated and analyzed to maximize operational efficiency and improve competitiveness.
AT&T’s Stankey also highlighted how data is becoming a strategic differentiator. “How do you give yourself a strategic advantage?” he asked. “This is the next step… using our data and our insights. What do we know that someone else doesn’t know? That’s the next frontier.”
At AT&T, data-driven insights are already being used to dynamically manage the wireless network, responding to changes in traffic demand in real time. For example, AI can help realign antennas or shift capacity to areas experiencing increased load, improving performance and efficiency.
The central message was clear: data is no longer just a byproduct of telecom networks. It has become foundational infrastructure, powering AI, automation, and the next generation of telecom business models. While AI will run the telecom networks, data will determine whether it works.
Economic Sustainability and Total Cost of Ownership
While Mobile World Congress is known for showcasing bold visions and future technologies, it also serves as a forum for confronting a pressing reality: how to build the next generation of networks economically. As operators invest in AI, automation, and advanced connectivity, a key question remains: how can networks become more intelligent, secure, and high-performing while keeping total cost of ownership (TCO) under control?
AI and automation clearly provide significant efficiency gains, with the potential to cut operational costs and boost productivity. However, many speakers warned that automation alone does not guarantee savings. When automation is based on incomplete or inaccurate network data, it can cause cascading service issues, automation loops, service degradation, costly outages, and ultimately higher operational costs rather than reducing them.
John Stankey emphasized that improving efficiency is essential not only for operators but also for customers. “If we get more efficient, we can use those savings to ultimately come back and offer customers more value,” he said. A key step toward achieving this efficiency, he noted, is to build more open, software-driven networks. As he explained, the industry needs to become “more software focused moving forward… software is so flexible today.” With customers demanding continuous innovation and new capabilities, software-based architectures provide operators with the agility to introduce new services without relying solely on hardware upgrades.
Rakuten’s Mikitani also highlighted the importance of deep virtualization in reducing costs and improving flexibility. At Rakuten Group, the network is built almost entirely on software, running on the company’s own cloud infrastructure with internally developed OSS and an evolving BSS stack. “End-to-end, we are a fully virtualized, software-based network -probably the largest in the world,” he said.
By running network functions on general-purpose hardware and dynamically scaling resources, virtualization enables operators to lower infrastructure costs, improve operational agility, and accelerate innovation.
Ultimately, the discussions at MWC made one thing clear: achieving economic sustainability in telecom will require more than new technologies alone. It will demand smarter architectures, better data, and intelligent automation that together reduce complexity and drive long-term TCO efficiency.
To Summarize: The Future is Intelligence, Collaboration, and Customer Focused
The vision emerging from Mobile World Congress was unmistakable: AI-native, data-driven, and autonomous networks are no longer a concept; they are the future. Turning that vision into reality, however, requires more than new technologies. It demands smarter networks, deep observability, open architectures, and a relentless focus on the customer.
At RADCOM, we leave the show energized and focused on clear priorities: working closely with our partners and never losing sight of what consumers demand. By combining AI-driven insights, software-defined architectures, and end-to-end network intelligence, operators can deliver seamless services, optimized networks, and superior customer experiences. Because, ultimately, the networks of tomorrow will only succeed when intelligence, collaboration, and customer focus are built into their very foundation.
Contact us to see how RADCOM can support your transition to next-generation networks https://radcom.com/contact/
