India’s AI shift - From capability to control

Over the past year in India, conversations with CIOs across industries tell a consistent story. AI has decisively moved beyond pilots and proofs of concept. The focus today is not whether AI works, but whether it delivers measurable returns while operating within clear boundaries of trust, governance, and accountability. As Indian enterprises look ahead to 2026, success will depend on treating AI not as a technology experiment, but as a system that is engineered for scale, responsibility, and real business outcomes.

From experimentation to trusted execution

The CIO Playbook makes one reality unmistakably clear. While AI spending in India is accelerating, adoption remains measured, with nearly half of organisations still in evaluation or planning stages. This is not hesitation. It reflects a sharper understanding of risk, ROI, and long-term impact. Indian CIOs are increasingly clear that AI must be grounded in enterprise-grade data, aligned to defined outcomes, and explainable in its decisions. Trust is no longer an abstract concept. It is operational.

In regulated sectors such as banking, healthcare, and public services, explainability and data integrity are becoming non-negotiable. Leaders want AI systems that can justify recommendations, respect privacy, and stand up to regulatory scrutiny. In India’s context, where scale and diversity amplify both opportunity and risk, trusted AI is the only viable path forward.

Hybrid AI as the architecture of choice

One of the strongest signals from the CIO Playbook is India’s clear alignment with hybrid and on-premise AI architectures. Nearly two-thirds of organisations are choosing this model, driven by data sovereignty requirements, latency sensitivity, cost control, and resilience. This is a pragmatic decision, not a conservative one.

AI workloads in India are increasingly spanning centralised data centres, edge environments, and public cloud platforms within the same workflow. Training may occur in core infrastructure, while inference takes place closer to where the data is generated. This distributed approach allows organisations to scale AI responsibly without overspending or compromising control. For Indian enterprises operating at a massive scale, hybrid AI is not optional. It is foundational.

Power, sustainability, and the reality of scale

AI growth brings with it a hard constraint that CIOs can no longer ignore: power. Energy availability and efficiency are emerging as strategic considerations in AI planning. Sustainability in India is no longer limited to corporate commitments. It is directly linked to the ability to expand AI initiatives over time.

Denser systems, advanced cooling technologies, and right-sized infrastructure are enabling organizations to extract more performance per watt. At the same time, moving inference closer to the edge reduces data movement, lowers latency, and cuts energy consumption. Enterprises that embed sustainability into their AI infrastructure decisions today will be better positioned to scale tomorrow without disruption.

Governance as a business priority, not a checkbox

Perhaps the most critical insight from the CIO Playbook is the growing gap between awareness and action on AI governance. Governance, risk, and compliance now rank as the top priority for CIOs in the region, yet full implementation remains limited. In India, fewer than one in five organizations report having fully enforced enterprise AI GRC frameworks.

This gap represents both a risk and an opportunity. Responsible AI cannot be retrofitted. It must be designed into systems from the outset, through clear governance models, ethical frameworks, human oversight, and strong data protection. Organizations that move early on governance will not only reduce risk but also accelerate adoption by building confidence among boards, regulators, employees, and customers.

Putting people at the centre of AI adoption

AI’s real impact in India will come from how widely it can be applied across roles and functions. Natural language interfaces, agentic AI, and more intuitive tools are lowering the barrier to participation. Domain experts in manufacturing, healthcare, retail, and logistics can now shape AI-driven workflows without being AI specialists.

The leadership challenge is clear. CIOs must create environments where people can use AI confidently and responsibly. That means investing in skills, building a culture of accountability, and partnering where internal capabilities need to scale faster. As India moves toward 2026, AI is no longer a standalone initiative or a future bet. It is becoming integral to how organisations operate, compete, and grow. The leaders will be those who build AI systems that are trusted by design, hybrid by default, sustainable at scale, and governed with intent, always keeping human judgment at the core of the transformation.

Sumir Bhatia

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Sumir Bhatia is the President of Asia Pacific, ISG at Lenovo.