'Digital sovereignty is now an industry necessity, not a regulatory checkbox': Rishi Aurora

Bengaluru: AI agents don’t fail in isolation; they fail inside complex systems. In an interview with DH's Uma Kannan, IBM Consulting India & South Asia Managing Partner Rishi Aurora says digital sovereignty is emerging as a source of strategic strength for India.

Edited excerpts:

Is India Inc past the AI 'hype cycle,' and what separates real transformation from expensive experimentation today?

India Inc is moving beyond AI hype — but the real inflection point now is agentic AI. The question is no longer whether enterprises can deploy models, but whether they can trust AI systems to take decisions, trigger actions, and operate with accountability at scale. We are seeing that banks, financial service providers, telecom operators and manufacturers that invested early in data discipline and governance are already moving from assistive copilots to agentic systems — automating credit decisions, network operations, shop floor optimisation, and so on. Others remain stuck at the pilot stage. This gap is reflected in IBM’s Enterprise in 2030 report; while 79% of executives expect AI-driven revenue impact, only 24% know where it will come from. As AI becomes more autonomous, digital sovereignty is now an industry necessity, not a regulatory checkbox. Embedding governance, accountability and control where the data resides. That’s what ultimately turns AI from promise into performance. Through our own client zero approach, IBM has reimagined over 70 workflows using AI and automation, unlocking $4.5 billion in productivity gains, which have been reinvested in R&D, new technologies, and go-to-market capabilities.

As agentic AI scales, what risks are Indian enterprises most worried about and which ones are they underestimating?

The big challenge for Indian enterprises isn’t AI itself — it’s organisational readiness. Legacy processes still weigh down many enterprises, along with accumulated technical debt, fragmented data and a shortage of skills needed to scale AI responsibly. As AI becomes agentic, governance gaps surface quickly. Explainability, accountability and oversight cannot be retrofitted; they need to be built into workflows from the start. Scaling GenAI isn’t about solving one issue at a time — it requires redesigning workflows, modernising core systems, strengthening data foundations and preparing the workforce in parallel. Miss any one of these, and pilots struggle to translate into value. Further, while enterprises are focusing on ensuring privacy and compliance, owing to regulatory requirements such as the DPDP Act, integration risks are often underestimated. AI agents don’t fail in isolation; they fail inside complex systems. In sectors like banking, a single poorly-governed autonomous decision can cascade rapidly. The real risk isn’t autonomy, but autonomy without transparency, lineage and human oversight.

Which industries in India are pulling ahead with AI at scale? What hard lessons are emerging from these early, large-scale AI deployments?

BFSI and manufacturing have a clear lead, but India’s Global Capability Centres (GCCs) are increasingly shaping how AI scales at the enterprise level. Banks have moved past pilots, embedding AI into core functions like credit, risk and compliance with strong governance and human in the loop controls. Manufacturing is pushing agentic AI onto the shop floor, driving real-time optimisation and productivity gains. GCCs play an integral role in taking these proven AI models and scaling them globally. Many are acting as AI control towers; standardising platforms, strengthening data foundations and stress-testing governance before solutions are rolled out globally. Given that our nation hosts over 2,100 GCCs, India is uniquely-positioned to lead the way globally.

How is the onset of digital sovereignty changing the way Indian enterprises design technology, manage data, and position themselves in a more fragmented global digital economy?

Digital sovereignty is emerging as a source of strategic strength for India. As our nation scales its AI ambitions over the next decade, control over data, models, and digital public infrastructure shall become the foundation for trust, resilience and long-term competitiveness. What is rapidly changing is the enterprise mindset. Sovereignty is no longer seen as a compliance requirement, but as a core design principle. In sectors like banking, telecom, energy and healthcare, where data is both critical and sensitive, enterprises are rethinking architecture to keep control without compromising on pace. This is driving the adoption of hybrid cloud models that seamlessly blend public, private and sovereign environments. Across industries, leaders are focusing on three things to achieve digital sovereignty: designing for it from day one, strengthening data governance so AI runs where the data lives, and moving beyond isolated use cases to rewire entire workflows. Together, these shifts are reshaping how Indian enterprises compete in a fragmented global digital economy.

What role do consulting firms like IBM play in helping Indian enterprises balance speed, scale, and sovereignty in their AI journey?

Enterprises today expect consulting partners to co-innovate, co-own outcomes, and stay through execution. As organisations grow more AI-mature, they want partners who can help redesign how work happens, stay close through execution, and scale AI with speed while retaining control. By bringing together IBM’s consulting depth, enterprise-grade technology platforms, and a strong partner ecosystem, we help clients move beyond experimentation and turn AI into a sustained, proprietary advantage. As AI becomes critical to how enterprises operate and scale, credibility becomes equally important. Through our client zero approach — using our own operations as a proving ground — we offer clients a practical blueprint for scaling AI responsibly, not just theory.