As enterprises worldwide accelerate their transition from AI experimentation to large-scale execution, technology leaders across semiconductors, enterprise services, infrastructure, and storage are converging on a common theme: the future of AI will be defined by execution discipline, physical-world intelligence, resilient architectures, and foundational readiness. Senior executives speaking across domains highlight how 2025 marked a turning point, from pilots to governed, enterprise-wide adoption, while 2026 is set to deepen this shift with new computing paradigms, edge intelligence, and heightened expectations around security, reliability, and real-world impact.
The rise of Physical Intelligence and edge autonomy
According to Paul Golding, VP of Edge AI and Robotics at Analog Devices, AI is moving beyond language and vision models into the physical world. “The next frontier of AI will be Physical Intelligence. The scaling laws that powered the success of large language and vision models will continue through 2026 but will extend into models that learn from vibration, sound, magnetics, and motion (stubborn attributes of the physical world). I predict these physical reasoning models will migrate from the datacenter to the edge, powering a new type of fluid autonomy that thinks and acts locally, sensitive to local physics and without recourse to centralized servers. Such models will dynamically learn from novel situations, exposed to only a few examples of novel circumstance. Think of a mobile factory robot that can reason for itself and determine what to do when faced with an unexpected obstacle. We can expect to see an increase in hybrid ‘world models’ that blend mathematical and physical reasoning with data-driven sensor-fused dynamics, and systems that not only describe the world but participate in it and learn, as Richard Sutton says, from their own ‘experience.”
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From pilots to disciplined enterprise execution
Enterprise leaders note that AI conversations in India have matured significantly over the past year. Vikram Bhandari, CTIO at Riveron, observes that 2025 marked a decisive pivot toward measurable outcomes. “In 2025, India’s enterprise technology landscape shifted decisively from experimentation to execution. The conversations we’re having with C-suite leaders, especially CFOs and CTOs are now centered on tangible returns, measurable efficiency, and accelerating the move from pilots to full-scale adoption. Over the past year, companies have advanced automation, modernized financial and operational systems, and strengthened governance to meet rising regulatory standards and global competition. As we look ahead to 2026, this momentum will only intensify. Technology and finance leaders are beginning to treat AI as foundational infrastructure, supported by deeper investments in cloud, data platforms, and cybersecurity. The focus is evolving beyond automating individual tasks toward orchestrating intelligent, end-to-end operations, where decisions, controls, and compliance are embedded by design. The message from 2025 is clear: India is no longer testing digital transformation. The mandate for 2026 is equally clear – execute responsibly, securely, and with unwavering discipline to deliver lasting business impact.”
Balancing cloud agility with infrastructure strength
As enterprises scale AI and cloud-native services, infrastructure resilience remains a critical counterbalance. Ajay Sawant, Chairman & Managing Director at Orient Technologies, highlights the need for equilibrium between services-led transformation and core IT foundations. “As organisations prepare for 2026, enterprise technology is entering a period of accelerated evolution driven by cloud-first architectures, AI-powered automation, and the rapid build-out of digital public infrastructure. These shifts signal a clear move toward services-led transformation models that prioritise agility, resilience, and measurable business outcomes. At the same time, traditional IT infrastructure continues to play a foundational role, anchoring the stability and performance that large-scale digital environments demand. The year ahead will require technology partners to blend deep services expertise with robust infrastructure capabilities to support mission-critical, high-complexity programmes. Companies that can balance both dimensions will be best positioned to enable organisations as they navigate this next era of digital growth.”
AI scale collides with security and resilience imperatives
With scale comes complexity and risk. Tejesh Kodali, Group Chairman of Blue Cloud Softech Solutions Limited, points to rising expectations around trust and resilience. “2025 highlighted both the promise of AI and the mounting pressures felt across sectors from security and cybersecurity to healthcare and beyond. Over the past year, organisations across industries accelerated their adoption of AI for automation, decision intelligence, and operational efficiency, even as they navigated increasingly sophisticated, persistent, and unpredictable threats and disruptions. This dual trajectory has reshaped expectations for 2026, where AI will continue to drive scale, speed, and innovation across every digital ecosystem. As an industry-agnostic solutions provider, we see this shift impacting all sectors alike: the need for continuous intelligence, resilient architectures, and adaptive, self-learning systems is no longer limited to one domain. The path ahead is a transition from fragmented, reactive approaches to integrated, AI-powered frameworks that uphold trust, reliability, and long-term digital growth.”
The return of physics-led compute
At the hardware layer, new compute paradigms are emerging to address energy and latency constraints. Massimiliano Versace, VP of Emergent AI at Analog Devices, sees analog computing gaining renewed relevance. “Historically sidelined due to scalability and precision limitations, analog compute is reemerging in 2026 as digital architectures face energy, latency, and memory bottlenecks with no solution in sight. This is especially critical in edge environments where real-time responsiveness and power efficiency are a must. Analog AI compute uses the physics of the sensing and computing substrate to perform computation, transforming energy directly into AI inference. This is a different approach to AI compute vs. conventional digital processors, which separate sensing from computation. Analog AI collapses these layers into a unified framework where intelligence begins at the sensor itself. By the end of 2026 we’ll see initial deployments and adoption of this technology, particularly in robotics, wearables, and autonomous applications, where analog AI enables real-time responsiveness, smoother interactions, longer battery life, and more natural behavior in the devices they power.”
Fixing the fundamentals to unlock AI impact
Despite rising AI investments, leaders caution that transformation hinges on execution fundamentals. Dr. Mukesh Gandhi, Founder & CEO of Creative Synergies Group, emphasizes discipline over ambition. “AI adoption will continue to accelerate in 2026, yet meaningful transformation requires more than just investment in next-generation infrastructure. It demands a relentless focus on the fundamentals. As organizations attempt to move beyond pilots, many will be stalled by critical gaps in data integrity and specialized skills. To convert ambition into dependable value, leaders must resist the temptation of ‘big-bang’ projects and instead prioritize targeted, operational wins. The winners will be those who exercise the patience to fix these structural deficits, pairing disciplined execution with a modernized culture to bridge the divide between strategy and readiness.”
Storage emerges as a critical AI enabler
As AI workloads explode, storage is becoming a strategic priority. Subind Kumar, Vice President and Country Manager at Sandisk, notes unprecedented demand across enterprise and consumer segments. “2025 has been a landmark year for data storage, driven by an explosion in data from AI models, digital transformation and consumers. From cloud data centers deploying petabyte-scale flash storage solutions to consumers embracing Gen4 and Gen5 SSDs, the appetite for faster, high capacity and more reliable storage devices has never been higher. We saw enterprises in India and globally building AI-ready data lakes to glean faster insights from a large amount of data, while everyday users are demanding customized storage devices to meet their different needs. Our focus in 2026 will be on continuing to create innovative storage devices to meet the needs of our enterprise customers and consumers so they can focus on what they do best. We are committed to empowering every user, from enterprises to creators, with the right storage technology to unlock their data’s potential in the AI era.”
