AI and India: Translating readiness into success

Corporate boardrooms globally are confronted with the pivotal challenge of turning AI’s vast potential into real business impact. The answer to which lies in readiness, not limited to technology alone, but extends across people, processes and purpose. India, at the forefront of global AI readiness, has been leveraging scale, structure and speed to create its competitive edge. According to the Kyndryl People Readiness Report 2025, 97% of Indian enterprises have already adopted AI solutions, and 95% have implemented governance frameworks to ensure responsible AI deployment.

Additionally, 72% of India business leaders, with the realisation that an AI led transformation would demand specific skills, have been actively investing in internal upskilling. Thus, while many economies remain in the AI experimentation phase, India, with its execution-led approach is advancing toward enterprise-wide transformation

Scalable AI opportunity powered by India’s talent advantage

With the scale, versatility and economic flexibility available at disposal, Indian enterprises have been able to move quickly from experimental pilots using cross-functional AI teams to enterprise-wide deployment. Indian workforce’s strong analytical skills, quick learning and comfort with complexity, in addition to a culture of structured problem-solving and collaborative decision-making, is the perfect combination and build that can operationalise AI at scale in real-world business environments and shortens time to impact

But even with this advantage, scale doesn’t come automatically. Readiness must translate into real, coordinated execution.

The readiness-execution divide slowing down India’s AI ambitions

While India has a head start as per AI readiness metrics, maintaining that lead requires closing the gap between intent and implementation. Execution must become the priority through clearer accountability, cross-functional ownership, and a relentless focus on business impact.

A major hurdle lies in the disconnect between C-suite vision and on-ground execution. While leadership remains aligned on AI’s potential, frontline adoption is often uneven. Middle managers lack clarity on implementation priorities, operational teams face skill deficits, and performance metrics rarely reflect AI’s contribution to business value. This misalignment leads to fragmented efforts, where AI pilots fail to scale or deliver impact.

A shortage of practical expertise hinders large-scale AI adoption efforts. And this is evident even across India’s Ministries, Departments, and public sector organisations, while the intent to adopt AI is strong translating it into action is the challenge. The barriers that need to be broken are, ageing infrastructure, fragmented data systems, and uneven digital maturity. These issues slow down execution and limit the ability to scale AI meaningfully.

That said, the opportunity is substantial. In government departments, AI can improve citizen-facing services; whether through faster grievance resolution, multilingual communication platforms, or data-led planning for public programs. In public sector organisations across industries like banking, energy, and manufacturing, AI can automate routine processes, improve asset utilisation, strengthening risk and compliance.

We also need to evaluate AI’s scope not limited to achieving operational efficiency, but to advance broader national priorities. The conundrum lies in using AI to drive economic growth, create jobs, boost global competitiveness, and accelerate initiatives like Make in India. And for that shift to happen, we need to strategize on embedding AI into the core of how these entities operate.

Strategic partnerships will be key to making this happen, especially those that bring scale, platform depth, and the ability to build systems that are resilient and ready to grow.

Aligning people, processes, and platforms for AI success

Adoption doesn’t succeed on process redesign alone. Culture can often be a barrier to AI success. For AI adoption to succeed organisations should unify technology, processes and culture. Organisations need to integrate change management into the core of AI programs, starting with diagnostics, aligning incentives, and activating support at the team level, to stronger outcomes. Three layers determining AI adoption would be: individuals need confidence using AI in their roles; teams require new norms for collaboration and shared decision-making; and organisations must realign performance metrics and governance to sustain these shifts.

Equally critical is scaling applied skills. Upskilling through hands-on learning prepares teams for real-world AI deployment and optimization, while governance ensures agility and accountability.

Signs of this shift are already emerging. A small group of enterprises, also known as AI Pacesetters, are taking a structured, enterprise-wide approach to AI transformation, embedding AI across functions while addressing skills, ethics, and job impact transparently. Their efforts accelerate scaling, strengthen commitment, and deliver measurable business impact by aligning people, processes, and technology.

The business imperative for AI leadership

India’s AI readiness can drive global leadership, but success depends on effective execution. To stay ahead of international competitors, organisations must shift from pilot projects to structured implementation. Leadership commitment, investment in talent, and business process transformation are essential for this shift. Those making the transition will shape India’s AI-driven growth and set new global standards.

The article has been written by Anuj Vaid, Vice President, Strategic Business, Kyndryl India.

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