FUTURE OF HYBRID AI INFRASTRUCTURE

The Data Centre Conclave 2025, organized by Nexgen Conferences Pvt. Ltd. on 11 July 2025 at the Holiday Inn in Mumbai, their flagship event, brought together industry leaders, innovators, and professionals from the data center and digital infrastructure ecosystem. This conclave served as a premier platform to explore cutting-edge advancements, discuss pressing challenges, and uncover emerging opportunities in the ever-evolving world of data centers.

The event covered a wide range of topics, including technologies such as 5G, edge computing, and artificial intelligence, as well as sustainable energy solutions and robust security frameworks. Participants gained unparalleled insights and forward-thinking strategies to navigate the future of digital infrastructure. The Data Centre Conclave 2025 was an invaluable opportunity for attendees to network with industry peers, engage in thought-provoking discussions, and stay informed about the latest trends in data center technology and innovation.

Data centers serve as the foundation of our digital world, providing the essential infrastructure for businesses, telecom providers, cloud services, and enterprises to efficiently store, process, and manage vast amounts of data. As technology continues to advance at a rapid pace, modern data centers must adapt to accommodate the increasing demands of emerging technologies such as artificial intelligence (AI), 5G networks, the Internet of Things (IoT), and edge computing.

To keep up with these advancements, organizations are transitioning towards scalable, high-performance data center infrastructures that offer robust security, improved energy efficiency, and automation capabilities. Furthermore, the growing prevalence of hybrid and multi-cloud environments necessitates seamless integration, low latency, and real-time processing to support mission-critical business operations and next-generation applications.

As the digital landscape continues to evolve, data centers must remain agile, embracing innovation to provide the necessary backbone for a world that heavily relies on the constant exchange and processing of information. By staying at the forefront of technological advancements, data centers can ensure that they meet the ever-changing needs of businesses and consumers alike.

Mombasawala Mohamedsaed, as General Manager of New Technologies Initiatives at Keysight Technologies, is recognized for leading industry discussions on revolutionizing AI infrastructure at key technology events in India, including the Data Centre Conclave 2025 in Mumbai and other recent high-profile gatherings. At these forums, Keysight’s leadership—including Mohamedsaed—has focused on next-generation strategies to modernize data center and AI infrastructure, highlighting several foundational technology shifts.

This slide outlines key points about global AI investment and competition:

Scale of Investment: AI development represents a massive economic commitment, with projections showing AI-related spending could reach 2.5-4% of U.S. GDP and 1.5-2.5% of GDP in other leading AI nations. This puts AI investment on par with major infrastructure or defense spending.

Hardware-Driven Growth: The immediate focus is on physical infrastructure – 80% of generative AI spending in 2025 will go toward hardware like specialized chips, servers, and data centers rather than software development. This reflects the massive computational requirements for training and running advanced AI systems.

Global Competition: The framing as a “quest for dominance” and “race” suggests this isn’t just about technological advancement, but about strategic positioning. Nations and companies are viewing AI capabilities as critical for economic competitiveness and potentially national security.

The key insight is that AI development requires unprecedented capital investment in physical infrastructure, making it as much an industrial and economic challenge as a technological one. The scale suggests AI is being treated as a foundational technology that could reshape entire economies.

AI has the potential to add an impressive $967 billion by 2035 and $450-500 billion to India’s GDP by 2025, accounting for approximately 10% of the country’s $5 trillion GDP target. It’s clear that AI technology will play a crucial role in driving India’s economic growth and development in the coming years.

The transition from graphics rendering to AI computing represents one of the most successful examples of hardware repurposing in computing history, fundamentally enabling modern AI capabilities.

Unlike CPUs which excel at sequential tasks, GPUs were designed to handle thousands of simultaneous calculations for rendering graphics. This parallel processing capability perfectly matches the computational needs of AI algorithms, particularly neural networks that perform massive matrix operations simultaneously.

Modern data centers require more scalable and modular infrastructure, with compute fabrics and chiplet-based designs enabling ultra-high throughput and flexibility for AI workloads.

There is planned a massive scale-up in AI computational infrastructure, showing how the demand for larger AI models is driving exponential growth in hardware requirements:

This build-out represents more than just buying more GPUs. It requires:

Specialized data centers with enormous power and cooling capacityAdvanced networking equipment to handle unprecedented data throughput

Sophisticated orchestration software to manage distributed training across thousands of processorsp

New standards for interconnect technologies as existing networking hardware reaches its limits.

The progression suggests that AI development is pushing the boundaries of what’s technically feasible in distributed computing infrastructure, requiring innovations in networking, power delivery, and thermal management at datacenter scale.

This slide reveals the hierarchical complexity of AI infrastructure networking, showing how different scales require fundamentally different technological approaches.The infrastructure complexity explains why AI development requires such massive capital investment and why networking technology advancement is critical to AI progress.

Mohamed Saed highlighted the importance of energy-efficient designs, cooling innovations (such as liquid cooling), and smarter resource allocation to meet the exponential growth in AI-driven operations and maintain operational sustainability.

This slide reveals the operational complexity of running AI infrastructure at scale, highlighting the distinct requirements for training versus inference workloads.

The architecture reveals why AI companies need two distinct network infrastructures. Training clusters optimize for maximum throughput and perfect reliability among GPUs, while inference networks optimize for user experience and data security. This dual-infrastructure requirement significantly increases the complexity and cost of AI operations.

The hypervisor layer shown suggests these systems must also support multiple simultaneous workloads, adding another layer of orchestration complexity to an already sophisticated networking challenge.

This reading list provides a comprehensive framework for understanding AI’s transformative impact across multiple dimensions. Together, these books span the technical (Suleyman), geopolitical (Kissinger et al.), and anthropological (Harari) dimensions of AI transformation. This reading list suggests that understanding AI requires more than technical knowledge—it demands appreciation for historical context, power dynamics, and long-term societal implications. The selection indicates this presentation is targeting leaders who need to understand AI’s broader strategic implications beyond just the infrastructure and technical capabilities discussed in the earlier slides.

Gaurav Ranade presented on Strategy & Security in Data centres, highlighting India generates 20% of the world’s data but has only ~3% of global data center capacity. This creates a massive imbalance where the country producing one-fifth of global digital information lacks the infrastructure to process, store, and analyze it domestically.

This gap means India is heavily dependent on foreign data centers for processing its own data, creating potential security, sovereignty, and economic concerns. Data generated in India likely gets processed in other countries’ facilities, giving those nations potential access to sensitive information and economic value.

India has achieved ~950 MW of data center capacity as of early/mid-2024, surpassing other major APAC markets like Singapore, Japan, and Australia. This suggests aggressive recent investment and expansion, but it’s still insufficient relative to the country’s data generation.

Ranade focused on how evolving architectures, emerging threats, and real-world use cases are reshaping the design, operation, and protection of data centre ecosystems. Key points included the impact of the explosion of AI workloads, edge computing, and compliance-driven mandates requiring security to be integrated early in strategy and design rather than as an afterthought.

Ranade covered critical elements such as power and cooling, segmentation, workload isolation, and sovereign data governance. Ranade emphasized that strategy must intertwine with design to ensure secure and resilient data centres, addressing the challenges enterprises face in a highly connected, threat-prone environment.

Rather than retrofitting existing facilities for AI workloads, future data centers will be purpose-built from the ground up for machine learning and AI processing. This means optimized cooling systems for high-density GPU clusters, specialized networking architectures for the massive data flows AI requires, and power infrastructure designed for the extreme energy demands of AI training and inference.

Data centers will increasingly operate themselves using AI-driven management systems. This includes automated resource allocation, predictive maintenance, self-healing network configurations, and intelligent workload distribution. Given the complexity revealed in earlier slides about multi-layer networking and infrastructure, autonomous operations become essential for managing systems too complex for human oversight alone.

As quantum computing advances threaten current encryption methods, data centers must transition to quantum-resistant security protocols. This is particularly critical for AI systems processing sensitive data and for protecting the valuable AI models and training data that represent massive investments. The timeline is urgent since quantum threats could materialize within the next decade.

This slide outlines a comprehensive ecosystem approach to building resilient AI and data center infrastructure, recognizing that no single entity can address all the complex challenges involved:

Role of MSSPs and System Integrators: Managed Security Service Providers and system integrators serve as the orchestrating layer, bringing together disparate technologies and services into cohesive, operational systems. Given the complexity shown in earlier slides about multi-layer networking and infrastructure requirements, these partners are essential for designing, implementing, and managing integrated AI infrastructure that actually works in practice.

Collaboration with Power/Utility Providers: AI data centers have unprecedented power demands – potentially requiring hundreds of megawatts for large training facilities. This necessitates deep partnerships with utilities for grid planning, dedicated power infrastructure, and potentially co-location strategies. The power requirements are so substantial they can affect regional grid stability and require long-term capacity planning.

Presentation by Amit Bhatt – Director data center services, On evolution of data centres at the data centre conclave 25 nexgen tech, highlighted on the Cycle trends in Data centres and why it happens.

The cyclical nature of data center architecture evolution through four fundamental tensions that drive periodic shifts in computing paradigms:

Latency vs. Centralization: The perpetual struggle between performance and efficiency. Centralized systems offer economies of scale and easier management, but as applications demand real-time responsiveness (like AI inference, autonomous vehicles, or AR/VR), the physical limits of data transmission force a move toward edge computing. This cycle repeats as new applications push latency requirements beyond what centralized systems can deliver.

Cost vs. Control: The economic pendulum swings between cloud adoption for scalability benefits and on-premises repatriation when costs become prohibitive or compliance requirements demand direct control. Organizations often discover that while cloud offers flexibility, sustained high-volume workloads can become more expensive than dedicated infrastructure, leading to “cloud repatriation” movements.

Innovation vs. Stability: Technology adoption follows a pattern where new paradigms (like serverless computing) repackage established concepts (event-driven programming) with modern tooling and improved implementation. This creates cycles where “revolutionary” technologies are actually evolutionary improvements on proven architectures, leading to periodic rediscovery of older approaches with better execution.

Security & Regulation: Data sovereignty laws and privacy regulations create geographic constraints that override pure technical optimization. GDPR, data localization requirements, and national security concerns force organizations to maintain local computing capacity regardless of cost or efficiency considerations, driving demand for regional data centers.

These cycles explain why data center strategies oscillate between centralized and distributed, cloud and on-premises, cutting-edge and proven technologies. Each swing addresses the limitations revealed by the previous approach, but creates new constraints that eventually drive the next cycle.

By 2030: Data centers will transition to high-density computing with 100+ kW racks powered by hybrid energy systems combining grid power, on-site renewables, hydrogen fuel cells, and battery storage. Infrastructure will shift to modular, prefabricated designs enabling rapid edge deployment, while liquid cooling and immersion systems handle extreme heat loads. AI-driven management systems will provide full-stack automation with self-healing capabilities, supported by multi-petabyte software-defined networks offering real-time routing and low-latency edge interconnects.

By 2040: Data centers will achieve complete autonomy through self-optimizing AI agents requiring zero human intervention, operating as self-sufficient modular pods adaptable to any environment or weather condition. Near-zero carbon operations will be maintained through nuclear microreactors, 100% renewable energy, and real-time grid load balancing. Quantum computing integration will revolutionize processing capabilities while quantum-secure photonic networks provide self-healing global connectivity, creating fully autonomous digital ecosystems that adapt and scale independently with optimal performance and sustainability.

The NexGen 2nd Annual Data Centre Conclave, held on July 11th, 2025, at the Holiday Inn in Mumbai, proved to be a resounding success. As the Gold Partner, Norden Communication played a pivotal role in bringing together key players from the data center and digital infrastructure industry. The event featured insightful discussions, presentations, and exhibitions that explored the latest advancements in sustainable, high-performance data center technologies. Norden’s participation underscored its commitment to driving innovation and fostering collaboration within the digital infrastructure space.

Norden stands out as a unique manufacturer and supplier of ELV and Optical Solutions, catering to various sectors such as telecommunications, buildings, utilities, surveillance systems, and Public Addressing Systems. Their tried-and-tested solutions employ cutting-edge technology to deliver high-quality products that meet the diverse needs of their clients across industries. Norden is committed to pushing boundaries and providing exceptional devices and solutions that excel in performance, reliability, and innovation.

At the Data Center Conclave in Mumbai, VIAVI Solutions showcased its latest portfolio of test, monitoring, and orchestration solutions for next-generation data centers. Key products on display included the OneAdvisor 800 with 400G Transport Module and the comprehensive range of field test solutions for fiber construction, maintenance, and high-speed network testing. VIAVI’s commitment to enabling sustainable, efficient, and scalable data centers was evident through its focus on solutions for fiber inspection, testing process automation, and end-to-end job management.

“India’s data center industry is experiencing significant growth due to accelerated digital data traffic and country’s expanding digital infrastructure. The exponential data growth is pushing data centers to be closer to their customers, resulting in more edge deployments, while also forcing data center operators to increase speed, security and efficiency at the same time as they minimize latency. Hyperscale data centers and the cutting-edge technologies accompanying them, are turning these unprecedented challenges into opportunities”, said Monojit Samaddar, Country Director, VIAVI.“

At the Data center conclave this year, VIAVI will showcase test solutions that provide multi-dimensional visibility, intelligence and insight needed to efficiently manage physical and virtual environments, in order to profitably deliver optimum service levels, transition to new technologies and launch innovative services, he added“.