Vladislav Zaimov is a distinguished authority in the field of telecommunications infrastructure, specifically recognized for his deep proficiency in enterprise network architecture and the critical management of risks within vulnerable network environments. As we navigate the complex landscape of 2026, Zaimov’s insights have become essential for understanding the convergence of legacy systems and the next generation of intelligent, software-defined infrastructure. Our conversation centers on the seismic shift within the industry as mobile operators move toward highly automated, vendor-independent frameworks to solve the mounting pressures of operational costs and energy demands.
This discussion explores the transition from traditional self-organizing networks to more advanced Service Management and Orchestration (SMO) and RAN Intelligent Controller (RIC) platforms. We examine the financial realities of the radio access network, which remains the most expensive component of modern infrastructure, and how automation levels are progressing toward high-impact autonomy by the end of the decade. Zaimov also touches upon the specific success stories of global operators who are already seeing significant energy savings, as well as the emerging technical interfaces that allow for real-time network control at an unprecedented scale.
The radio access network is notoriously expensive and resource-heavy; how is this current financial and environmental pressure driving the immediate need for automation?
The Radio Access Network is the most significant burden on any mobile operator’s balance sheet, currently accounting for over 60% of the total cost of ownership. When you look at the operational side, the numbers are even more staggering, with the RAN responsible for between 70% and 80% of a mobile network’s total energy consumption. In a world where sustainability is no longer optional, these figures represent a massive opportunity because even a modest improvement in efficiency yields a huge environmental and financial payoff. By implementing sophisticated AI and machine learning algorithms for automated management, operators aren’t just chasing a trend; they are fighting to keep their nationwide footprints sustainable and profitable. It’s a high-stakes environment where saving a few percentage points in energy can translate into millions of dollars in annual cost savings.
As we move further into 2026, why are we seeing such a massive shift away from legacy self-organizing networks toward SMO and RIC-based platforms?
The limitations of legacy self-organizing networks, or SON, have become a major bottleneck for operators who need to scale quickly and manage multi-vendor environments. Traditional SON solutions often struggle with interoperability and the latency requirements of modern 5G and future 6G deployments, which is why we’re seeing a 40% compound annual growth rate in spending on SMO and RIC platforms through 2030. Operators like AT&T, Verizon, and Vodafone are moving toward these standards-based components because they offer a level of programmability that legacy systems simply can’t match. By using centrally coordinated rApps hosted on the SMO and Non-RT RIC layers, these companies can automate thousands of cell sites regardless of which vendor provided the hardware. This shift is the backbone of the “vendor swap-out” projects we’re seeing globally, allowing for a much more flexible and hybrid RAN architecture.
Could you share some concrete examples of how these automation technologies are performing in the real world right now?
We have seen some incredible results from greenfield operators, particularly with Rakuten Mobile, which has deployed a nationwide RIC across a footprint of 350,000 cells. This deployment is a technical marvel because it integrates components from ten different radio unit and distributed unit vendors, proving that multi-vendor interoperability is a reality. In their live network, they have already achieved a 20% reduction in energy consumption per cell using closed-loop applications. Following their successful lab trials, they are now pushing those boundaries even further, aiming for a 25% reduction through the use of more advanced AI and machine learning models. Seeing these numbers move from a controlled lab environment into a massive, live network gives the entire industry the confidence that these automation goals are actually within reach.
We often hear about different levels of autonomy in networking; what does the roadmap look like for reaching a “highly autonomous” state by the end of the decade?
The journey toward a fully autonomous network is segmented into levels, and while Level 5, or total autonomy, is still a very distant dream, many operators are laser-focused on reaching Level 4 by 2030. At Level 4, we’re looking at highly autonomous operations that can handle high-impact scenarios like traffic optimization, fault management, and service assurance without constant human intervention. This is particularly vital for special event management, where network demand can spike unpredictably and requires real-time adjustments. The pursuit of this level of autonomy is what’s driving the adoption of Open RAN automation, as it provides the scalability and low-latency control needed for such complex tasks. It’s about moving from a reactive posture to a proactive, self-healing network that can anticipate issues before they affect the end-user.
What technical barriers still exist for real-time control, and how are new interfaces like E3 helping to overcome them?
One of the biggest hurdles has been the reluctance of hardware vendors to expose the necessary interfaces for third-party control, which has slowed the adoption of xApps and the Near-RT RIC. However, there is a lot of excitement around the recently proposed edge-enhanced exposure interface, known as E3. This standardized mechanism is a game-changer because it allows dApps to interface directly with baseband nodes for control at timescales below 10 milliseconds. This level of speed is essential for tasks like interference cancellation, spectrum sharing, and geolocation in current 5G and upcoming 6G deployments. By breaking down these silos, the industry is creating a path for lower-layer performance optimization that was previously impossible in a closed, proprietary system.
What is your forecast for the Open RAN automation market over the next few years?
The trajectory for Open RAN automation is incredibly aggressive, with annual investments projected to exceed $660 million by the end of 2030. We are seeing a steady 40% growth rate for SMO, RIC, and the various application ecosystems like rApps and xApps, which is significantly higher than the 9% growth we see in the broader, traditional automation market. This tells us that the industry is firmly committed to this modernization wave, prioritizing vendor-independent approaches that offer more control. While traditional SON solutions will likely coexist with these new platforms for a while because they are so deeply integrated into daily operations, the shift is undeniable. As brownfield operators continue their mid-cycle 5G modernizations, the dominance of programmable, AI-driven automation will become the standard for the entire telecommunications landscape.
