From historic AI spendings to ambitious 6G roadmaps, test and measurement players have their eyes set on some of the biggest trends of 2026
The top technology trends of 2026 are not isolated shifts — but tightly interwoven themes representing a world that is complex, hyperconnected, and driven by AI.
Viavi CTO, Sameh Yamany, emphasized this while talking about what to expect in 2026 in a video presentation for NextGenInfra.io. He said, “As we look ahead to 2026, our industry is entering a new phase where networks, security, AI, photonics, and sensing are no longer evolving independently. They are actually converging, and this convergence will fundamentally change the way we design, deploy, and test networks, data centers, and critical infrastructure.”
In this new world, the only way to guarantee success is to follow the demand. And test and measurement companies have their eyes on the prize — or rather prizes.
Resumption of 5G deployment
Although 5G buildouts yielded strong returns in the first phase, things haven’t looked very promising in the last couple years — largely due to investment slowdowns resulting from factors ranging from cost cutbacks to lower customer adoption to poor ROI.
The lull has eased off as deployment of 5G Stand Alone (SA) kicked off in 2025. According to Omdia, 5G SA builds peaked making 2025 a “breakout year.”
“With 5G SA deployments picking up pace, the industry is finally realizing the true potential of 5G,” analyst Alexander Thompson wrote in his analysis.
How will that play out in 2026? “By 2026, 5G Standalone (SA) will be mature enough to support network slicing at scale, to guarantee specific SLAs. Private 5G will deliver connectivity for hard-to-connect industries,” Fierce Network’s analyst Mitch Wagner told Fierce.
Spirent’s Steve Douglas predicted that most Tier 1 operators will transition to 5G SA cores in 2026, and start planning or implementing 5G-Advanced (5G-A) capabilities.
The first wave of 5G-A deployment is taking place across China, U.S — and in the Gulf region where over 10,000 base stations were deployed last year. 2026 will see that momentum continue with mass-market acceleration expected in 2027 and onward.
6G on the way
6G networks mark a transition from fast to faster speeds, and low latency to microsecond-level latency. Once here, it will be the connective tissue that links massive IoT infrastructures with AI-enable industrial complexes.
With commercial launch predicted in 2028, 2026 will see more operators setting up the infrastructure for the next-generation connectivity, while industry bodies establish roadmaps for implementation.
And as telecom operators gear up for 6G, 6G RAN R&D will pick up as vendors and operators strive to understand its performance requirements and limitations.
The AI gold rush
AI is perhaps the most influential trend driving innovation in 2026. Gartner predicts global AI spending to skyrocket in 2026, hitting $2.5 trillion — a 44% jump year-over-year. According to its analysis, AI infrastructure will contribute roughly $401 billion toward that, while investments in AI servers will drive the spending by 49%.
This will create an organic demand surge for infrastructure benchmarking, performance monitoring, and lab-to-live testing across layers spanning chips, memory, Ethernet fabric, high-speed interfaces and interconnects, and AI models in data centers.
With new architectures come new challenges, and that will further drive need for integrated, fabric-aware testing and validation methodologies to ensure the network is fit to support the demands of AI workloads.
Further to that, AI agents are expected to play an integral role in the evolution of telecom in 2026. Ericsson is developing AI agents to optimize the radio access network (RAN) and as uptake starts, AI agents will bring the vision of autonomous, self-healing networks to life with capabilities like real-time detection, automated multi-step troubleshooting, and continuous network optimization.
AI-RAN: Vision to life
Nvidia is pushing AI-RAN hard on telcos. It’s been a hard sell on account of the unconvincing business case, but the GPU giant is leaving no stone unturned. The company has pumped money into companies in the frontlines to fast-track innovation and lead the transition — case in point its billion-dollar partnership with Nokia.
“The next leap in telecom isn’t just from 5G to 6G — it’s a fundamental redesign of the network to deliver AI-powered connectivity, capable of processing intelligence from the data center all the way to the edge,” said Justin Hotard, president and CEO of Nokia, highlighting the importance of reimagining the network architecture to support AI.
The concept of AI-RAN is built on the premise of enhancing RAN performance by making it more intelligent, efficient, and optimized for AI. Nvidia argues that putting AI on RAN can uplevel the network in many ways, including optimizing resource utilization, enabling new AI applications — generative AI, agentic AI, and physical AI — to run on RAN, and making it more energy-efficient.
2026 will see AI-RAN move from theory to production, as telecom operators like T-Mobile starts testing the technology as part of 6G innovation.
The age of AI-driven attacks — and Q-Day
The rapid proliferation of AI has revealed a dark side of the technology and its potential in the hands of bad actors. According to data, AI-assisted cyber attacks have jumped across industries, reflecting a 73% rise in incidents in 2025. An IBM survey estimates that the average cost of each data breach in 2025 was approximately $4.4 million.
As AI-assisted tools are increasingly bypassing traditional cybersecurity technologies, there is a growing demand for security testing, stress testing, vulnerability scanning, pen testing, and compliance testing for rapid identification and containment of threats. Digital twins will see a deeper integration in this landscape, unlocking real-time representation and continuous updating of complex ecosystems.
To add to that, quantum computing is getting closer to primetime. In that future, classical security systems are at risk of failing if post-quantum cryptography is not implemented timely. This is steadily creating a market for quantum characterization and validation solutions to ensure that as the technology moves from the lab to the real world, companies have a blueprint and toolchain to manage and mitigate the cryptographic risks that comes with it.
AI at the edge
“AI is increasingly living closer to where the data and users are, which is out at the edge, on the device, in the real world,” John Roese, CTO of Dell Technologies, said in a conversation with R&D World.
The AI infrastructure is rapidly scaling out to the edge with the arrival of edge inferencing and deployment of robotics. This industry-wide pivot to the edge is prompted by the startling discovery that edge models — which are more compressed — are faster, more private, and a lot less hungry for power than their larger counterparts in data centers. This could give companies the sovereignty and autonomy they need.
Stephen Doughlas of Sirent noted in his article on RCR Wireless News, “To avoid leaving money on the table, [operators] are exploring how they can host AI infrastructure themselves within their networks, especially at network edge locations. We’ll be seeing a growing array of operators offering differentiated, profitable AI as a Service for specific use cases.”
The rise of AI at the edge of the telco network will generate a fresh wave of demand for service assurance that will be critical to maintain operational resiliency and service continuity.
