Sumir Bhatia ,President, Asia Pacific, Lenovo ISG is at the helm of one of the most pivotal shifts in enterprise technology, building AI-ready, secure, and scalable infrastructure for a digitally transforming region. With over three decades of leadership across global tech giants, Sumir’s approach blends technical depth, business foresight, and a relentless focus on customer-centric innovation.
From championing “Smart Normal” as a mindset to operationalizing AI across highly regulated sectors, Sumir is driving Lenovo’s mission to deliver smarter technology from pocket to data center. In this exclusive interview, he explores the unique demands of India’s AI surge, the road from readiness to enterprise-scale deployments, and how Lenovo is positioning India at the center of the global AI infrastructure supply chain. With sharp insights on compliance, talent, governance, and sustainability, Sumir charts a bold vision for enterprises navigating the next wave of intelligent transformation across Asia Pacific.
With 51% of Indian enterprises planning to ramp up AI initiatives, how is Lenovo tailoring its infrastructure strategy to deliver ROI-driven, scalable solutions that align with India’s unique digital transformation goals?
Ans. Lenovo is sharply focused on delivering infrastructure that’s not only scalable but outcome-driven. Lenovo is enabling this shift by helping organizations move from siloed AI deployments to scalable, production-grade solutions. Our end-to-end portfolio - from AI-ready devices, servers, hybrid cloud, and services - ensures our customers have the flexibility to build and deploy AI where it creates the most value, and deliver performance, data control, and compliance, especially in regulated sectors such as BFSI and healthcare.
What makes India unique is the diversity of its digital landscape. That’s why we’re investing in local innovation through our India-based R&D lab, solution testing capabilities, and ecosystem collaborations. We ensure our offerings are not just global in scale but also tuned to local business environments and IT requirements.
With India emerging as the most GenAI-ready market in APAC, what are the biggest roadblocks you foresee in moving from readiness to real, scalable enterprise outcomes? What does an ideal AI-ready infrastructure look like for APAC enterprises today?
Ans. Moving from intent to impact requires more than just enthusiasm - it demands trusted infrastructure, data maturity, and responsible deployment frameworks. One of the major roadblocks is the gap between experimentation and enterprise-grade scaling, driven by data quality issues, legacy integration, and talent. As per our recent CIO Playbook 2025, only 7% of Indian enterprises have systematically adopted AI across the organization. Many organizations are piloting GenAI use cases, but to operationalize them, they need infrastructure that is robust, secure, and ready to support real, complex workloads. This includes everything from high-performance servers and efficient cooling to the ability to deploy flexibly, whether on-prem, at the edge, or via hybrid cloud.
The ideal AI-ready infrastructure combines performance with simplicity - systems that can run intensive AI models, are scalable, cost-effective, and easy to manage. Lenovo is supporting this shift through a comprehensive portfolio from AI-optimized infrastructure to Everything-as-a-Service (XaaS) delivery via Lenovo TruScale. Our work with more than fifty independent software vendors and institutions across India is helping organizations deploy AI with confidence, scale intelligently, and align with business outcomes.
As AI adoption deepens, especially in regulated sectors like BFSI and healthcare, how should enterprises navigate the rising complexity of compliance, governance, and data sovereignty in the region?
Ans. Improving regulatory compliance ranks as the top business priority for enterprises in Asia Pacific. This underscores the need for governance models that are embedded across the AI lifecycle. Enterprises must implement robust data frameworks, ensure model explainability, and maintain human oversight in critical processes. In India, however, only 19% of CIOs report fully implemented enterprise AI governance, risk, and compliance (GRC) policies, highlighting a significant readiness gap. Hybrid AI environments play a vital role by supporting localized control and regulatory alignment. Rather than seeing compliance as a barrier, forward-looking enterprises treat it as a design principle, one that paves the way for a sustainable, secure, and scalable AI deployment.
As AI systems evolve from assistive tools to increasingly autonomous agents, how do you envision the balance between AI autonomy and human oversight, especially in terms of governance models and safeguards for enterprise-scale deployments?
Ans. As AI transitions from supporting roles to autonomous decision-making, enterprises must go beyond performance metrics to design AI. It’s no longer about what AI can do, but what it should do, how it does it, and do it responsibly.
At Lenovo, we believe autonomy and human oversight should not compete - they must coexist. AI systems should be governed by transparency, accountability, and control, with clear policies for auditability, traceability, and human intervention.
To lead this effort globally, Lenovo has established a Responsible AI Committee, a cross-disciplinary body tasked with setting governance standards, reviewing ethical implications, and ensuring that our AI solutions are designed and deployed responsibly across markets. This committee brings together leaders from legal, technical, security, privacy, product, and strategy teams to oversee Lenovo’s commitment to fairness, transparency, inclusiveness, and human oversight in AI. Whether through policy-driven access, explainable models, or real-time override capabilities, trust must be architected, not assumed, into enterprise AI deployments.
Given the surge in AI and edge computing, where do you see the next big talent and upskilling gaps in APAC, and how should governments and enterprises prepare?
Ans. The rapid adoption of AI and edge computing across APAC is outpacing the current talent pipeline. Key gaps are emerging in areas like data engineering, edge infrastructure management, GenAI operations, and AI governance.
Beyond technical expertise, there is also growing demand for professionals who can apply AI ethically and contextually across regulated industries. To address this, governments are scaling national skilling initiatives, investing in industry-academia collaboration, and creating certification programs focused on AI and digital infrastructure. As part of this collaborative approach, Lenovo, along with Motorola and MBF, has partnered with the National Institute of Engineering (NIE) in Mysuru to launch the Alpha Lab that provides hands-on, AI-driven learning environments for students and researchers, aiming to build future-ready AI talent in India.
Enterprises must step up by developing in-house talent, leveraging AI service partners wisely, and embedding AI learning into core business functions. At Lenovo, we’re working closely with customers and ecosystem partners to drive this transformation from both ends, capability building and infrastructure readiness
Lenovo’s AI server manufacturing in India and the new R&D hub in Bengaluru signals a strong strategic commitment. What were the key drivers behind this move, and how do you see it shaping India’s role in global AI supply chains?
Ans. Our investment in local server manufacturing and the Infrastructure R&D lab in Bengaluru is part of a long-term vision, one that aligns with India’s growing role as a global digital and AI hub.
India offers a unique trifecta: a fast-evolving AI economy, an expanding pool of skilled talent, and a favorable policy environment for innovation and ‘Make in India’ initiatives. Local production of AI-optimized infrastructure is a step toward improving operational agility and aligning more closely with regional needs, while supporting broader supply chain goals.
The Bengaluru lab adds a vital R&D layer, driving innovation in thermal design, power optimization, system architecture, and platform engineering. Together, these investments are positioning India as both a consumer and contributor to global infrastructure advancement.
From your vantage point, how is Lenovo enabling enterprises across APAC to move beyond pilot AI projects toward full-stack, secure, and sustainable AI ecosystems? What governance models or safeguards do you believe are critical as enterprises scale AI across sectors?
Ans. Across APAC, enterprises are evolving from siloed AI pilots to enterprise-wide, production-grade deployments. Lenovo is enabling this shift by offering a full-stack AI ecosystem of optimized edge devices, high-performance servers, deployment services, and industry-validated solutions.
With Lenovo AI Fast Start, we help customers identify high-impact use cases, validate them quickly, and scale with purpose. We’re equally focused on building systems that are secure, explainable, and policy-compliant from day one.
Governance plays a critical role in this journey. Whether it’s ensuring data lineage, embedding ethical safeguards, or enabling real-time human oversight, we treat responsible AI as a core design principle. As enterprises scale AI, these safeguards are not optional; they are essential to ensure trust, continuity, and long-term success.