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07 January 2026 Enabling AI-driven data center operations with IT/OT Convergence Fabrizio LandiniGlobal Data Center Segment Leader
Discover the benefits of IT/OT convergence, plus our roadmap for achieving it in your own data center operations.
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Long story short AI-driven operations demand seamless coordination between IT and OT systems. Converging these historically siloed domains unlocks new levels of efficiency, resilience, and intelligence – but success requires more than just technical integration. Why it matters As AI workloads grow exponentially, the gap between what data centers can deliver and what they’re being asked to deliver is widening. IT/OT convergence is the strategic foundation that enables operators to meet this challenge. The complete picture Data centers are no longer just rows of servers in climate-controlled rooms. They’re complex, dynamic ecosystems where digital workloads and physical infrastructure must operate in perfect harmony. Yet historically, these two domains – information technology (IT) and operational technology (OT) – have been managed separately, with different teams, different tools, and different priorities. This separation made sense in an earlier era. IT focused on compute, storage, and networking, which is the digital backbone of the data center. OT managed physical infrastructure, be that power distribution, cooling systems, or environmental controls. The two rarely needed to coordinate beyond basic capacity planning. But AI has changed everything. Modern AI workloads generate unprecedented thermal loads, require dynamic power allocation, and demand real-time optimization of cooling systems. When a large language model kicks off a training run, the entire data center must respond instantly, from power draw to cooling output to network bandwidth. This level of coordination is impossible when IT and OT operate in silos. IT/OT convergence addresses this challenge by creating a unified data and control plane that spans both domains. It enables operators to see the entire data center as a single, integrated system rather than a collection of disconnected components. The result: faster response times, better resource utilization, and the foundation for truly autonomous, AI-driven operations. The challenges holding convergence back Despite its clear benefits, IT/OT convergence remains elusive for many operators. The challenges are both technical and organizational. On the technical side, IT and OT systems speak different languages. IT networks run on standard protocols like Ethernet and TCP/IP. OT systems often use proprietary industrial protocols designed for specific equipment. Bridging this gap requires middleware, protocol translation, and careful integration work. There are also technical challenges associated with the IT and OT systems themselves. In particular, legacy systems on the OT side can be difficult to integrate with digital tools. For example, building management systems (BMS) can be a major stumbling block for data center operators. Some operators are still using older systems that aren’t known for their connectivity, or even proprietary protocols.
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Case study CPFL Energia Yet these challenges are surmountable. CPFL Energia in Brazil demonstrates what’s possible when IT/OT convergence is executed well. Managing power distribution to 9.1 million consumers across 12 Brazilian states, the organization implemented Hitachi infrastructure that unified its operational technology data.
But technical challenges pale in comparison to organizational ones. IT and OT teams often have fundamentally different cultures, priorities, and risk tolerances. IT teams move fast, embrace change, and prioritize flexibility. OT teams move deliberately, resist unnecessary change, and prioritize reliability above all else. Both approaches are valuable, but they can be difficult to reconcile. “Technical challenges pale in comparison to organizational ones.” Successful convergence requires building bridges between these cultures. This means creating cross-functional teams, establishing shared metrics, and developing a common language that both IT and OT professionals can speak. It also means investing in training so that IT professionals understand physical systems and OT professionals understand digital networks. A roadmap for IT/OT convergence So where do you start? Based on our experience working with data center operators worldwide, we recommend a phased approach. Phase 1:Establish data connectivity Before you can converge operations, you need unified visibility. This means connecting OT systems to a common data platform, standardizing data formats, and ensuring real-time data flow. Start with non-critical systems to build confidence and learn lessons before tackling mission-critical infrastructure. Phase 2:Create unified dashboards Once data is flowing, create visualization tools that give both IT and OT teams a single view of the data center. This breaks down information silos and makes interdependencies visible. Phase 3: Implement automated responses With unified visibility in place, you can start automating responses that span IT and OT domains. For example, when a high-power AI workload starts, automatically adjust cooling output and notify the power management system. Phase 4:Enable predictive operations The ultimate goal is using AI to predict issues before they occur and automatically optimize operations. This requires sophisticated analytics, machine learning models, and high-quality historical data – but the payoff is enormous. Throughout this journey, it’s essential to maintain security and reliability. Convergence doesn’t mean exposing critical systems to unnecessary risk. It means thoughtfully connecting them with appropriate safeguards. It’s also worth finding partners that put their money where their mouth is. Some providers will now co-invest with their partners to develop new solutions, merging the traditional role of technology vendors with investment vehicles that catalyze change. At Hitachi, we do this through our Strategic Social Innovation Business (SSIB) unit. The SSIB combines funding with systems that we use to drive change in the areas that matter most.
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Case study Southwest Power Pool Our partnership with Southwest Power Pool exemplifies this approach. This isn’t IT/OT convergence in theory – it’s operational technology (the power grid) and information technology (AI-driven analytics) working as one unified system to solve infrastructure bottlenecks that are preventing 2+ terawatts of generating capacity from reaching the grid.
Above all, it’s crucial that IT/OT convergence evangelists find better ways of demonstrating the true business value of this transformation. It’s not enough to point to siloed metrics, be that sustainability reporting or enhanced uptime. Data center operators need to leverage the unified data stream that this newfound connectivity affords them to better identify and demonstrate ROI across a range of subsystems and solutions. “Convergence doesn’t mean exposing critical systems to unnecessary risk. It means thoughtfully connecting them with appropriate safeguards.” What’s next? As AI workloads continue to grow, IT/OT convergence will move from competitive advantage to table stakes. The data center operators that thrive will be those that can seamlessly coordinate their digital and physical infrastructure, using AI to optimize both in real time. The question isn’t whether to pursue convergence, but how quickly you can get there – and whether you have the right partners, processes, and people in place to make it succeed.
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Own the conversation Ask the big question: Are we moving too fast toward autonomous operations, or not fast enough? At what point does removing humans from the loop become a risk rather than an optimization? Disrupt your feed: We talk about digital twins and AI-driven operations, but most data centers still struggle with basic integration between IT and OT systems. Are we building the future on unstable foundations? Drop this fact: The addressable market for IT/OT convergence is projected to surpass $1 trillion by 2027 with around 8.5% growth annually.
