Praveen Arora, Vice President-IoT at Tata Communications, explains how enterprises can turn connected data into business value through edge intelligence, AI, secure connectivity and increasingly autonomous industrial operations.
Enterprise IoT is evolving from connecting devices to enabling intelligent, predictive and increasingly autonomous operations. As enterprises scale deployments across manufacturing, utilities, mobility and infrastructure, the focus is shifting towards integrating connectivity, edge computing, AI and security into a unified operational framework.
The challenge is no longer connectivity alone. Large-scale deployments must balance real-time responsiveness with network efficiency, protect thousands of connected endpoints, and translate operational data into measurable returns. Edge computing and Private 5G are enabling time-sensitive processing closer to machines and assets, while cloud infrastructure supports broader analytics and AI model training. At the same time, the growing convergence of IoT with generative AI and agentic systems raises questions about automation, accountability and human oversight in safety-critical environments.
In this conversation, Praveen Arora, Vice President-IoT at Tata Communications, discusses how enterprises can turn connected data into business value, balance edge and cloud workloads, strengthen security across connected environments, and prepare for AI-led industrial operations while retaining human oversight of critical decisions.
CIO&Leader: Enterprise IoT in India has shifted from isolated pilots to mission-critical deployments. What are the primary macro trends driving large-scale adoption across Indian and global enterprises today?
Praveen Arora: Over the last few years, enterprise IoT has evolved from isolated pilot projects into a core pillar of digital transformation. Organisations are moving away from siloed deployments and adopting integrated platforms that connect people, assets, machines, and operations into a single digital ecosystem. By combining sensors, connectivity, cloud, edge computing, and analytics, enterprises can convert large volumes of operational data into real-time insights and measurable business outcomes. We are also seeing strong momentum around seamless and global connectivity, with technologies such as eSIM and Remote SIM Provisioning (RSP) making it easier to deploy, manage, and scale connected devices across multiple geographies and networks. Adoption is accelerating in use cases where the business value is well proven. Large-scale deployments in areas such as connected vehicles, smart manufacturing, asset tracking, worker safety, and AI-powered video analytics are demonstrating tangible benefits through improved operational visibility, lower costs, better safety outcomes, and higher efficiency, resulting in IoT being increasingly viewed not as a technology initiative, but as a strategic business enabler
Another key trend is the convergence of IoT with AI and edge intelligence. Enterprises are increasingly processing data closer to the source, enabling real-time decision-making, predictive maintenance, and operational optimisation while reducing bandwidth and cloud processing costs.
CIO&Leader: Tata Communications provides cross-border fabric across connectivity, cloud, and edge. How does your global network infrastructure differentiate Tata Communications’ IoT proposition from standalone system integrators or telco providers?
Praveen Arora: At Tata Communications, our differentiation lies in our ability to bring together an integrated digital fabric—connecting devices, networks, applications, edge infrastructure, and operational intelligence into a unified ecosystem. Rather than taking a one-size-fits-all approach, we combine LPWAN and Private 5G to address the full spectrum of industrial and utility connectivity requirements.
For large-scale deployments such as smart metering, smart utilities, and smart cities, our LPWAN capabilities provide long-range, low-power, and cost-effective connectivity that can scale across vast geographies. Our LPWAN infrastructure supports some of the world’s largest smart utility deployments and is designed to connect millions of devices efficiently without placing unnecessary load on cellular networks.
For enterprise and industrial environments, our Private 5G solutions extend this digital fabric to the edge, delivering ultra-low latency, high bandwidth, deterministic performance, and secure on-premises connectivity. This makes them ideal for mission-critical applications such as machine vision, video analytics, robotics, autonomous operations, and connected worker solutions.
What sets Tata Communications apart from standalone system integrators or traditional connectivity providers is that we go beyond connectivity. We bring together the Interaction fabric, network fabric, edge intelligence, and operational platforms into a single managed environment. This enables customers to deploy, secure, monitor, and scale connected operations through one partner, rather than coordinating multiple vendors across the technology stack.
Our objective is not simply to connect devices, but to connect data, intelligence, and operational workflows to deliver measurable business outcomes at scale.
CIO&Leader: How has the conversation around IoT monetisation shifted in the C-suite—are enterprise leaders primarily prioritising operational cost reduction (preventive maintenance, energy management) or net-new revenue streams enabled by connected products?
Praveen Arora: The conversation has shifted from “How do I connect assets?” to “What business value does connectivity create?”
Today, operational outcomes remain the primary driver of IoT investments. Predictive maintenance, energy optimisation, asset utilisation, and worker safety continue to deliver the fastest and most measurable ROI.
The conversation has shifted from ‘How do I connect assets?’ to ‘What business value does connectivity create?’
However, as connected ecosystems mature, enterprises are increasingly exploring new revenue opportunities. In connected vehicles, for example, OEMs are evaluating data monetisation models around infotainment, usage-based services, and ecosystem partnerships.
The common thread is that enterprises first establish operational value and then leverage connected data, services, and ecosystems to create new revenue streams and business models
CIO&Leader: As ultra-low-latency applications grow, how is Tata Communications architecting the handoff between edge compute (processing data near the asset) and central cloud systems?
Praveen Arora: It is not edge versus cloud, but a balanced architecture designed to optimise network load and ensure rapid response times on the line.
Real-time, low-latency decisions such as computer vision running multiple safety and productivity use cases can happen locally at the edge, close to the camera or asset. At the same time, training AI models requires learning at scale, which is supported via the cloud.
It is not edge versus cloud, but a balanced architecture designed to optimise network load and ensure rapid response times on the line.
Private 5G is the connectivity layer that makes this handoff seamless. It links cameras, sensors, autonomous machines and connected worker devices to on-premises edge compute with ultra-low latency, high bandwidth and deterministic reliability, so real-time decisions are made locally without depending on the public internet. Because the network is dedicated and secure, high- volume video streams stay within the plant, and only the relevant events and frames travel onward to the cloud over Tata Communications’ network backbone. This keeps the load on the wide-area network low while giving the cloud the data it needs for model training and enterprise integration.
Private 5G ensures each workload takes the right path, whether it is processed at the edge or sent to the cloud, all managed end-to-end through a single operational view. When an incident occurs, edge devices capture the event locally and send only the relevant data or frames to the cloud for longer-term storage, analysis and enterprise integration. This approach balances workloads, optimises data flows and enables faster responses on the production line.
CIO&Leader: IoT deployments often generate massive volumes of unstructured or semi-structured telemetry data. How do you help enterprises ingest, clean, and pipe that stream to data lakes or AI models without bandwidth bottlenecks?
Praveen Arora: IoT deployments generate data from thousands of sensors, connected-worker devices, and operational systems. Our approach is to create an integrated IoT environment where intelligence can be applied at the edge to identify deviations and relevant events locally, ensuring that only the required data is transmitted to central platforms.
Depending on the use case, we leverage Private 5G for high-volume workloads such as video and machine vision, and LPWAN for low-power sensor deployments. We also collect insights from the connectivity layer, including network QoS data, and correlate it with operational and OEM data to drive business and operational efficiency. This edge-cloud approach helps optimise data flows, supports AI/ML-driven insights, and ensures that the right data reaches the right system at the right time, rather than moving every piece of data across the network.
CIO&Leader: Connecting thousands of unmanaged endpoints significantly broadens an enterprise’s attack surface. How do you address device-level vulnerability, mutual authentication, and zero-trust security from the edge device through the network core?
Praveen Arora: As enterprises connect thousands of devices, security can no longer be treated as a perimeter challenge. Our approach is to embed security across every layer of the IoT ecosystem—from the edge device and connectivity layer to the platform, applications, and data. We leverage secure device identities, certificate-based authentication, encryption, continuous monitoring, and anomaly detection to help protect connected environments end to end.
For global deployments, Tata Communications MOVE provides a regulatory-compliant connectivity framework that supports data privacy requirements and local data storage regulations across markets. The end-to-end data path is further secured through solutions such as IoT Safe, enabling secure communication channels between devices, networks, and applications.
Our goal is to provide an end-to-end, zero-trust security framework where devices, networks, applications, and data are continuously authenticated, encrypted, monitored and protected, enabling enterprises to scale IoT deployments securely and confidently.
CIO&Leader: How is the convergence of IoT and Generative AI/Agentic systems transforming industrial automation—are we moving from simple threshold alerting to autonomous machines that diagnose and resolve telemetry anomalies independently?
Praveen Arora: The convergence of IoT and Generative AI is accelerating the shift from simple threshold-based alerts to intelligent, predictive operations. Instead of reacting to alarms after an issue occurs, organisations can now analyse data from machines, sensors, video systems, and connected workers to detect patterns, identify potential risks early, and take preventive action before disruptions happen. Today, the biggest value of AI lies in enhancing human decision-making. For example, machine and vibration data can be used for predictive maintenance, computer vision can improve quality inspection and safety compliance, and multiple data sources can be combined to identify risks that would otherwise be difficult to detect. This enables faster, more informed responses and improves both operational efficiency and worker safety. As Generative AI and agentic systems continue to mature, they will increasingly be able to coordinate actions across multiple systems, recommend corrective measures, and automate routine operational workflows. However, in industrial environments, especially where safety and business continuity are critical, human oversight will remain essential. So, the evolution is not simply toward fully autonomous machines. It is toward intelligent systems that can understand context, predict issues, recommend actions, and in some cases automate responses, while keeping humans in control of critical decisions. The end goal is safer, more efficient, and more resilient industrial operations.
The end goal is safer, more efficient, and more resilient industrial operations.
CIO&Leader: Looking across the next 24 to 36 months, what are your major investment priorities for Tata Communications’ IoT portfolio regarding platform capabilities, partner ecosystems, and new market expansion?
Praveen Arora: Over the next 24-36 months, our primary investment priority is to transform Tata Communications’ IoT portfolio from a set of individual solutions into a unified, intelligence-led industrial operating platform that connects people, assets, facilities, utilities, and operations through a common digital fabric. The focus is not simply on adding more connected devices, but on helping enterprises move from connectivity and visibility to intelligence, prediction, and ultimately autonomous operations. From a platform capability perspective, we are investing in AI, Generative AI, machine learning, computer vision, digital twins, unified data fabrics, and edge intelligence to create a common operational layer across our portfolio. Whether it is worker safety, asset visibility, factory operations, utility management, or smart infrastructure, the objective is to bring data into a single intelligence layer that can deliver predictive insights, anomaly detection, operational recommendations, and automated decision-making. Ultimately, our vision is to build a portfolio that moves customers along the maturity curve from connected operations to intelligent operations, and finally to autonomous operations, while keeping people, safety, resilience, and sustainability at the heart of every transformation journey.