India is at a turning point where AI can become its next big growth engine, if it invests in skills at scale, sovereign models, and strong digital infrastructure
India is at a turning point. The country that once became the world’s IT back office now has the chance to become a global AI innovation hub. In conversation with CIO&Leader, Sachin Tayal, Managing Director and founding member at Protiviti India, says India is moving toward an “AI-first” approach, supported by government missions, policy incentives, and fast-growing Global Capability Centres (GCCs).
India moved straight from no laptops to smartphones. We will move straight into AI as well,” ~ Sachin Tayal
But this opportunity is not automatic. It depends on how well India prepares its people, builds infrastructure, and creates trusted AI systems.
Skills Will Matter More Than Tools
AI tools are increasing fast. But tools alone do not create value. What matters is whether people know how to use them. Kayal points out that demand for AI skills is rising across banking, healthcare, manufacturing, and services.
India’s advantage lies in its people. To turn this into an edge, AI training must begin early in schools, continue in colleges, and extend to the existing workforce. Reskilling cannot be optional, even for senior professionals. Everyone must learn how AI works, how to apply it, and how to question it.
Countries that build skills faster than they build tools will lead in AI.
Bridging the Digital Divide
AI should not benefit only a small group of urban professionals. Kayal stresses that AI education must reach the working class, the services sector, and even farming communities.
India has a history of leapfrogging technology. It skipped PCs and adopted smartphones at scale. The same can happen with AI. People may not go through long digital phases. They may move directly to AI-powered services in health, finance, agriculture, and governance. The next wave of AI users will come from inclusion, not elite tech circles.
Why India Needs Its Own AI Models
Most global AI models carry Western context and bias. Kayal says India must invest in “Bharat models” trained on Indian languages, data, and cultural realities.
India’s diversity makes this harder, but also more important. With dozens of languages and deep cultural variety, building inclusive AI is a national responsibility. State-led AI hubs, policy incentives, and funding for Indian AI research are key to avoiding dependence on foreign models.
AI sovereignty will become as important as data sovereignty.
Data Centres and GPUs: The Backbone of AI
AI runs on compute. Tax incentives for data centres until 2047 and India’s growing data generation give the country an opportunity to keep data and AI infrastructure within its borders.
This reduces dependence on undersea cables, improves compliance, and strengthens India’s control over how its data is used. But it also raises sustainability questions. Data centres consume energy, and AI growth must be balanced with environmental responsibility. Ning Compute will decide who controls the AI value chain.
Job Fears Are Real, But Not the Full Story
AI will disrupt some jobs, especially low-end, repetitive roles like basic BPO work. But Kayal puts this in perspective. Technology has always removed some roles and created new ones. Typewriters disappeared. Digital jobs emerged. will create demand for prompt engineers, model trainers, AI risk specialists, cybersecurity experts, and domain leaders who can guide AI use. Short-term stock market dips do not reflect long-term structural change. Low-value tasks will shrink. High-trust roles will grow.
People, Planet, Purpose: How Enterprises Must Respond
Protiviti’s approach to India reflects how enterprises must adapt. AI is being embedded across audit, cyber, legal, finance, SAP, consulting, and risk. Everyone is being trained on AI tools.
At the same time, firms must take responsibility for data privacy, DPDP compliance, cybersecurity, AI model risk, and sustainability. AI adoption without governance creates risk. AI adoption with trust creates value.
AI-first companies will be governance-first companies.
Why Humans Will Still Matter
The fear that AI will eliminate white-collar work is understandable but misplaced. As AI grows, so does the need for human judgement, ethics, trust, and oversight.
People will be needed to:
- Decide how AI is used
- Set boundaries and guardrails
- Review outcomes
- Protect privacy and security
- Ensure fairness and accountability
The future of work is not about racing AI. It is about working with it responsibly.