AI Is Forcing a Reset in Enterprise Infrastructure—Here’s What Changes

As we all know, enterprise IT architecture has been on a long journey, from centralized data centers to hybrid and multicloud environments, and from monolithic applications to highly distributed digital services. What has changed in recent years is not just the pace of this evolution, but its underlying drivers. The rapid rise of AI workloads, the expansion of edge computing, and the growing force of data sovereignty regulations are no longer incremental trends; together, they are reshaping the foundations of enterprise infrastructure.

Enterprises today operate across a fragmented digital footprint spanning public clouds, private clouds, edge locations, and on-premises infrastructure. AI has intensified this fragmentation. Training workloads may be centralized in public or private cloud environments, while inference workloads increasingly need to be executed closer to users, primarily via edge locations, to meet latency expectations. At the same time, data pipelines now cross geographies and jurisdictions, each with distinct regulatory constraints governing how data can be processed and moved.

Digital experience expectations have also risen sharply. End users, whether customers or employees, expect real-time responsiveness, uninterrupted availability, and consistent security, regardless of where applications or data reside. This has pushed enterprises to rethink how compute, security, and connectivity work together as a single system rather than as independent silos.

However, most enterprise environments were not designed for this level of distribution or interdependence. Networking, security, and computing tools have traditionally been procured, deployed, and managed in silos, an approach that worked in more static architectures but is increasingly misaligned with AI-driven, edge-enabled operating models.

Against this backdrop, select service providers and platform vendors are attempting to redefine their roles, not merely as connectivity or security providers, but as enablers of an end-to-end digital fabric that can support modern enterprise demands. It is within this broader context that Tata Communications, at its exclusive analyst roundtable, held in Mumbai last week, made key portfolio announcements, framing them as foundational elements of what it calls a “digital continuum” for AI-era enterprises, anchored in a unified approach to connecting, protecting, and controlling the modern enterprise infrastructure.

AI, Sovereignty, and Tool Sprawl Are Stress-Testing Enterprise IT

However, several structural shifts have complicated this evolution and exposed gaps in existing enterprise architectures.

1. 1. AI has introduced an infrastructure discontinuity: Unlike traditional enterprise workloads, AI workloads are inherently distributed. Data may reside in one cloud, GPUs in another, and users across multiple geographies. Inference often needs to occur close to the user to meet experience expectations, while training workloads remain centralized. This creates new east–west traffic patterns across clouds and regions, dramatically increasing network complexity and cost sensitivity.
   2. Data sovereignty has become a network problem, not just a storage problem: Regulations such as GDPR in Europe, the US Clarifying Lawful Overseas Use of Data Act (CLOUD) Act, China’s Personal Information Protection Law (PIPL), and India’s Digital Personal Data Protection (DPDP) Act now impose constraints not only on where data is stored, but also on how data moves across borders. In an AI-driven world where data is constantly in motion, enterprises must enforce sovereignty at the network level to ensure traffic does not inadvertently traverse prohibited jurisdictions.
   3. The edge has emerged as both an opportunity and a risk: As more processing shifts closer to users, enterprises are expanding their digital perimeters. This expansion has dramatically increased the attack surface, particularly for DDoS attacks, API abuse, and bot-driven threats. More than half of internet traffic today is non-human, and attacks are becoming faster, more distributed, and increasingly AI-driven themselves.
   4. Enterprises are overwhelmed by operational complexity and tool sprawl: Most large organizations now operate dozens of infrastructure and security tools across networks, clouds, data centers, and endpoints. According to Avasant’s Cybersecurity Services 2023 Market Insights™ report, 67% of enterprise customers struggle with managing multiple point tools, leading to underutilization and overlapping use cases, while 85% face interoperability and integration challenges across third-party security tools used to monitor logs and events.

As infrastructure complexity grows beyond human-scale management, enterprises struggle with visibility gaps, delayed incident response, and rising operational costs.

Collectively, these complications are forcing enterprises to confront a hard truth: incremental optimization of individual tools is no longer sufficient. What is required is a more integrated approach that treats compute, security, and connectivity as inseparable elements of a single digital fabric.

These changes raise a fundamental question for enterprises and service providers alike:

How can organizations design and operate a digital infrastructure that is AI-ready, sovereignty-aware, secure by design, and operationally simple?

Tata Communications’ response to this question centers on a three-part framework—connect, protect, and control—implemented through three tightly linked platforms:

1. 1. IZO^TM+ Multi Cloud Network

As enterprises expand across multiple clouds, connectivity has become one of the most complex and cost-intensive aspects of cloud architecture. Native cloud networking models are inherently siloed, forcing enterprises to manage different constructs, security policies, and monitoring tools for each provider. This fragmentation slows deployment, increases operational risk, and makes it difficult to enforce consistent performance, security, and governance across environments.

To address this challenge, Rajat Gopal, vice president of Global Network Services at Tata Communications, introduced IZO™+ Multi Cloud Network, a software-defined networking overlay designed to simplify and unify connectivity across heterogeneous cloud estates. The platform abstracts cloud-specific networking complexities and enables intent-based provisioning through a centralized control plane, allowing enterprises to deploy and scale multicloud networks in minutes rather than weeks.

A core differentiator of IZO™+ is its emphasis on automation and visibility. Built-in autopilot capabilities support self-healing and resilient operations, while a single dashboard provides end-to-end insight into traffic flows, performance, and cloud networking costs across providers. Security is embedded into the fabric through consistent policy enforcement and segmentation, rather than added as a bolt-on.

1. 2. The Edge Distribution Platform

To address performance and security challenges at the edge, Vaibhav Dutta, vice president and global head of cybersecurity at Tata Communications, introduced the Edge Distribution Platform (EDP), a solution that consolidates multiple traditionally separate capabilities into a single, network-native platform.

EDP combines content delivery, web and API security, edge computing, and DDoS mitigation under a unified control plane. This integration is designed to eliminate the trade-off between performance and security that enterprises often face when layering multiple point solutions.

From a security standpoint, the platform addresses both volumetric and application-layer attacks, with mitigation SLAs that commit to rapid response times. From a performance perspective, it supports low-latency content delivery and edge-based processing, both of which are increasingly important for industries such as gaming, media, retail, and e-commerce.

Importantly, EDP is positioned as a product model rather than a pricing construct, avoiding complex feature gating that can leave critical protections inaccessible unless higher tiers are purchased. This reflects a broader shift toward simplicity and predictability in enterprise security consumption.

1. 3. ThreadSpan

The final pillar, control, is delivered through ThreadSpan™, Tata Communications’ unified observability, configurability, and automation platform.

Puneet Sethi, vice president and global head of product, ThreadSpan at Tata Communications, explained that the platform is designed to provide a single control layer across the enterprise digital fabric. ThreadSpan consolidates telemetry from networks, cloud environments, data centers, security tools, and user devices into a unified operational view, enabling teams to understand infrastructure health and performance end to end rather than in isolated silos.

Beyond visibility, ThreadSpan emphasizes actionable intelligence and automation. Using AI-assisted analytics and agent-based workflows, the platform correlates events across domains, identifies root causes, and automates remediation for a significant share of operational incidents. This helps enterprises reduce mean time to resolution, minimize manual intervention, and prevent recurring failures.

Conclusion: From Fragmentation to a Cohesive Digital Fabric

The enterprise technology landscape is entering a phase where fragmentation is no longer sustainable. AI-driven workloads, sovereign data flows, edge-centric architectures, and escalating cyber threats are converging to expose the limitations of siloed infrastructure and tool-centric strategies.

Tata Communications connect–protect–control framework reflects a broader industry shift toward platformized digital infrastructure, where compute, security, and connectivity are treated as interdependent capabilities rather than isolated domains. By grounding its approach in network ownership, software-driven abstraction, and unified control, the company is positioning itself beyond traditional connectivity toward becoming a foundational enabler of the AI-era digital continuum.

For enterprises, the implication is clear: success in the next phase of digital transformation will depend less on adding new tools and more on simplifying, integrating, and automating the digital fabric that underpins the business.

By Gaurav Dewan, Research Director and Pranidhan Atreya, Research Analyst