How AI-native 6G networks will boost enterprise operations

While the transition from 4G to 5G was mainly about quicker speeds and less delay, AI-native 6G networks will be totally different.

Converging telecoms and AI is set to improve operational efficiency, risk management, and the user experience itself. The groundwork being laid by major players like Samsung is a clear signal: businesses must start planning for a network that acts less like a utility and more like an intelligent partner.

So, what is the business case for AI-native 6G networks? It boils down to autonomous efficiency and creating new services. The aim is to leapfrog marginal performance gains to unlock entirely new forms of value.

JinGuk Jeong, who is in charge of the Advanced Communications Research Center at Samsung Electronics, said: “The fusion of AI and telecommunications will deliver two core benefits—innovation in user experience and greater network efficiency through automation.”

In practice, this means networks that learn and optimise themselves. An enterprise could see resources autonomously reallocated to critical applications during peak demand, or power consumption managed intelligently across infrastructure to meet sustainability targets. It could finally enable reliable, widespread augmented and extended reality (AR/XR) services for frontline workers in logistics or manufacturing—applications that current networks just cannot truly support at scale.

Samsung is conducting research on embedding AI across every layer of the network. Jeong was quick to make clear that this is what’s important for truly AI-native 6G networks to work.

“AI-native doesn’t mean applying AI to specific equipment or functions—it means embedding AI technologies throughout the entire process, from design to operation,” he explained. “For example, in the physical layer (L1), AI reduces noise in radio signals, while in the data link layer (L2), it efficiently allocates network resources for each user.”

The biggest problem here isn’t the tech itself, but how complex everything is. No single vendor can deliver AI-native 6G network stacks alone. Successful rollouts will hinge on an “open innovation” strategy, mirroring the co-dependent ecosystems that leaders already navigate in the cloud. It needs deep teamwork between telcos, universities, and the chipmakers that power enterprise AI like NVIDIA, Intel, and Qualcomm.

What’s important is that this is all moving from labs to actual testing. Jeong said that “AI-RAN has moved beyond general simulations and lab-based testing and can now be validated in real-world network environments—allowing global telecom operators to directly experience its benefits. This will be a key driver in accelerating global standardisation discussions.”

This convergence of AI and 6G presents implications for technology leaders. The most pressing is that connectivity must be woven into the core AI strategy. Future business applications, especially those leveraging generative AI or industrial IoT, will depend on AI-native 6G networks that are as intelligent as the data centres and cloud platforms (think AWS, Google Vertex AI, or Microsoft Azure) they connect to.

Vendor and partner management roadmaps also need to expand; the most innovative services will likely emerge from collaborations spanning telecom operators, cloud providers, and hardware manufacturers. Beyond that, leaders must look past immediate performance metrics.

The era of AI-native 6G networks will not just be faster; it will be predictive, automated, and adaptive. The real task for executives is to start mapping that new potential to their own digital transformation goals.

See also: Telecom operators link AI goals to cloud spend

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Tags: 6g, ai, artificial intelligence, automation, connectivity, Enterprise, infrastructure, networks, samsung