Traditionally, every generation of cellular technology has been mostly about moving data faster. However, 6G is shaping up to be a different kind of upgrade. The industry’s focus is shifting from how fast a network can move data to what new services and experiences it can deliver, with artificial intelligence enabling this shift.
6G is being designed to embed AI deeper into the radio access network (RAN) and core, enabling the network to predict demand peaks before congestion sets in and manage radio resources in real time. That same intelligence could also help the network make use of its own infrastructure and wireless signals to provide data and gather information about the physical environment.
AI already exists in 5G networks, but 6G is designed to integrate these capabilities more deeply into the network architecture. 6G is still being defined through the 3rd Generation Partnership Project (3GPP) standards process, and many of these technologies are in the trial stage. Still, the direction is becoming clear as AI, distributed computing, and sensing are becoming as integral as new frequencies, lower latency, and data rates.
6G standardization & 3GPP
3GPP started to study 6G in Release 19, which was completed in December 2025. Release 20 evaluates foundational items for 6G, including studies of AI, sensing, and new architecture of the 6G network, and it is expected to be completed by 2027. Release 21 is now open for contributions and will be the first normative 6G specifications, pending finalization of its scope and timeline, and is expected to build on top of Release 20 studies and be completed by 2030.
Commercial 6G systems are still expected around 2030, although pre-commercial deployments and field trials will appear earlier. Many of the technologies being considered for 6G are already being introduced through 5G-Advanced, giving vendors and operators a chance to test capabilities such as AI-driven network optimization and integrated sensing and communication (ISAC) before committing to larger 6G deployments.
At the same time, 6G development is not limited to consumer networks. Governments and defense departments are also exploring potential use cases, particularly where communications, computing, sensing, and real-time decision-making need to work together. The U.S. Department of Defense is exploring 6G technologies and prototypes for military applications, adding another potential source of demand for early 6G systems.
The U.S. government’s Mission 6G 28 initiative is another example of this push toward early testing. The initiative is encouraging industry-led demonstrations of technologies, including AI-driven networking and integrated sensing, ahead of the 2028 Los Angeles Olympic Games. These demonstrations use pre-standard technology, providing an early look at which concepts can move from research into real-world environments.
Vendors are also developing tools to support these early trials, giving operators and research and development teams a way to test new capabilities before the standards are finalized.
The standards process provides the industry with key milestones to watch. Release 20 is expected to conclude in 2027, followed by the development of the normative 6G specification in Release 21 and the final protocol freeze in March 2029. After that, the focus shifts to operators and equipment manufacturers to turn those specifications into reliable systems.
AI-RAN
One of the clearest examples of AI moving into the network is in the RAN, which includes the base stations and antennas that connect devices to the cellular network. Traditionally, RAN equipment has been built around proprietary hardware and custom silicon designed for telco-specific functions with long upgrade cycles. AI is starting to challenge that model, but the industry is not taking one single approach.
Ericsson is taking a more evolutionary approach. The company is embedding AI capabilities into the RAN infrastructure that operators already have, with the goal of improving performance without a costly, large-scale hardware replacement. Early trial results point to real gains in efficiency and throughput, particularly around scheduling and radio resource management.
Nokia and Nvidia are pushing something more transformative. Their AI-RAN uses graphics processing unit (GPU)-based computing alongside traditional telco workloads, turning the RAN into a more flexible compute platform.
Nvidia backed this vision with a $1 billion investment in Nokia, and the two companies already have live trials running with T-Mobile. Putting more GPUs into the RAN brings additional computing capacity but also higher power consumption, cooling requirements, and infrastructure costs. Operators will ultimately have to decide whether the revenue from running AI workloads at the edge is enough to justify those costs.
If operators mostly want better network performance, adding AI to existing RAN infrastructure may be enough. However, the case for GPU-based AI-RAN becomes stronger if operators see an opportunity to turn that additional compute into a new business around distributed AI workloads.
The 6G core
AI is also starting to reshape the network core, the part of the network responsible for routing traffic, managing connections, and allocating resources. In May 2026, 3GPP advanced two competing approaches for integrating AI into the 6G core, with both now being studied in parallel.
The first, Solution Variant #18.1, puts AI directly into the core through new, agent-based network functions. These functions could interpret an intent from a user or application and orchestrate existing network functions to carry it out.
The second, Solution Variant #18.3, keeps AI separate from the core. A dedicated AI domain would interact with existing network functions through a translator function, allowing AI to optimize and orchestrate the network without fundamentally changing the core itself.
Variant #18.1 is being pushed primarily by Chinese vendors and operators, including Huawei, ZTE, and the major Chinese carriers, while Variant #18.3 has support from Western vendors and operators including Nokia, Ericsson, AT&T, T-Mobile, Qualcomm, and Google. SK Telecom is notably involved in both, reflecting the fact that the industry has not settled on a single path.
For now, 3GPP is keeping both options open. Where AI ends up sitting in the core will shape network architecture and vendor influence for years.
Integrated sensing and communication
As AI makes the network more capable of making decisions and managing itself, sensing can give it more information about the physical environment around it. ISAC uses its existing wireless signals for both communication and sensing, allowing cellular infrastructure to detect and track objects without dedicated sensing equipment.
Recent trials are starting to show what it could look like in practice. For example, in July 2026, AT&T and Ericsson used existing 5G infrastructure outside the AT&T Stadium in Texas to detect, locate, and track multiple drones flying between 300 and 400 feet. The system used existing massive multiple-input/multiple-output radios, signal processing, and AI-enabled sensing rather than a separate radar system.
The demonstration is a useful proof point, but it is not yet a replacement for dedicated radar. It’s more likely a near-term role as an additional layer of sensing, particularly in places where cellular infrastructure is already widely deployed. Drone detection, perimeter security, industrial sites, ports, and logistics facilities are the likely first use cases.
The bigger test will be whether ISAC can move beyond controlled trials and demonstrate performance across different environments, weather conditions, distances, and object types. If ISAC can handle those conditions, it could give AI-driven networks another important input, allowing them to make decisions based on what is happening in the physical environment and inside the network.
What to watch
The next few years will show whether 6G can deliver on the larger idea that it is less about a faster connection and more about the network becoming an intelligence platform. The clearest checkpoints are on the standards calendar: Release 20 studies conclude in 2027, the architecture is due to be finalized in 2028, and the first normative 6G specs freeze in March 2029. This will determine the technical standards, but what operators do in practice comes down to whether AI, distributed computing, and sensing can create enough value to justify the cost and complexity of putting them deeper into the network.
This is what truly differentiates 6G from previous generations. The network is becoming part of the computing infrastructure and can process AI workloads closer to the source, make decisions about how network resources are used, and gather information about the physical environment. That moves 6G beyond the traditional role of connecting devices and toward a more intelligent network.
This is a follow-up to ABI Research’s 5G & 6G: Adoption, Technologies and Use Cases.
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