As we mark Safer Internet Day in February 2026, the conversation has shifted dramatically from individual password hygiene to broader issues around responsible technology usage, such as the governance of Artificial Intelligence (AI). For large enterprises in India, the stakes have never been higher as regulations try to match the pace of progress in AI. With data as the foundation to AI usage, the expectation of many modern organizations is to operate as a data company, particularly if they have large amounts of consumer information on their hands.
SE Leader-India
Cloudera
The urgency is driven by a volatile threat landscape. An uptake in AI usage across business functions, and by extension, consumer data, expose the surface area vulnerable to cyber threats. According to Cyber Threat Report 2026, India recorded more than 265 million cyberattacks in 2025. This concentration of cyber threats targets the massive transaction volumes and sensitive personal information held by retailers and financial institutions. At the same time, although nearly two‑thirds of Indian organizations report having an AI governance framework in place, only 12% view these structures as mature enough to manage emerging risks effectively. This gap is further exacerbated by the fact that 70% of organizations struggle to access timely, high‑quality data as datasets grow more complex, distributed, and difficult to govern securely. Against this backdrop, organizations need to responsibly govern the data that fuels their growth while continuing to push the boundaries that give them a competitive advantage. Very often, these go hand in hand.
In this climate, a single breach does not just incur fines; it erodes the brand equity that businesses fight to build. For years, organizations relied on reactive security measures, “guard dogs”, that barked only after a threat appeared. However, in 2026, AI models continuously pull and generate data across on-premises centers, clouds, and the edge. Waiting for a problem to surface is no longer an option.
This is why Private AI has emerged as the critical framework for the modern enterprise. Private AI ensures that model inputs and outputs never leave the enterprise environment, bringing compute to the data rather than exposing data by moving it to the compute. This approach allows leaders to dismantle the “data privacy dilemma”, the false belief that they must choose between utilizing data for innovation or locking it down for compliance.
However, effective Private AI requires absolute visibility. According to Global Data Insights Survey 2025, 52% of Indian organizations previously admitted they did not know where their critical data resided. You cannot govern what you cannot see. To counter this, successful enterprises now utilize unified data platforms that provide end-to-end data lineage, tracking exactly where data originated, how it was transformed, and who accessed it.
As Generative AI agents become integral to workflows, we must also scrutinize the data feeding them. The most valuable data for tuning AI, support transcripts and transaction histories, is often the most sensitive.
Ultimately, security is a driver of value, and mission critical for an organization. As we navigate 2026, the companies that succeed will be those that implement proactive guardrails, ensuring their AI is private, governed, and secure by design.
Authored by Piyush Agarwal, SE Leader-India, Cloudera
