India’s privacy reality check: Rising stress, shrinking teams, and the AI imperative
India’s digital economy is growing at an unprecedented pace — powered by fintech, healthtech, e-commerce and AI-led platforms that thrive on data. Yet as organisations innovate, the people responsible for protecting personal data are increasingly stretched thin.
ISACA’s latest State of Privacy 2026 survey highlights that 55% of privacy professionals in India say their roles are more stressful today than five years ago. Shrinking teams, compliance complexity, and rapid AI adoption are compounding the pressure. As India transitions from intent to enforcement under the Digital Personal Data Protection (DPDP) Act, execution maturity is now the defining factor.
To better understand what these trends mean for Indian enterprises, we spoke to Chetan Anand, ISACA Global Mentor and Emerging Trends Working Group Member. “The statistics suggests a correlation between resources and on-the-job stress. The stress is attributed to the technology’s rapid evolution, compliance challenges, resource shortages and competing priorities. Organisations need to identify job roles to manage privacy compliance, equip their privacy professionals with the necessary training and certifications and prioritize privacy.”
Chetan says that DPDPA is exposing execution gaps as DPDPA has specific requirements. Since the DPDP rules were published in November 2025, many specific requirements are still new to Indian organisations and will take them some time to get a complete understanding of the privacy regulations.
“CISOs and DPOs should treat it as a risk perception problem, not a reassurance. Being confident does not reduce exposure; being wrong increases it. The correct posture under DPDP is not: ‘Will we have a breach?’ but ‘How quickly and confidently can we respond when one occurs?’”
Indian organisations are turning to AI because privacy complexity has outpaced human-only models; yet they are simultaneously uneasy because AI amplifies DPDP risk if governance does not evolve fast enough.
Over the next 12–24 months, organisations must treat AI systems handling personal data as regulated processing activities under DPDP, not neutral tools. DPOs and privacy teams must evolve into privacy engineering and AI governance roles. Explainability and auditability need to be built in before incidents occur.
Chetan recommends operationalising a DPDP-aligned data processing inventory with end-to-end consent and purpose traceability (‘policy-as-code’). He says, “This is the single highest-leverage move because it underpins every DPDP obligation and determines whether AI adoption reduces or multiplies risk. Make personal data processing visible, enforceable, and provable across humans, systems, and AI.”
As privacy budgets tighten even while AI adoption accelerates, many organisations face a dangerous imbalance between ambition and oversight. The challenge is no longer doing more with less — it is designing systems that reduce risk before scale magnifies it.
Opines Chetan, “The answer is not efficiency alone—it is selectivity, leverage, and architectural discipline. When resources shrink, unbounded AI is the real risk, not under-investment. It requires a shift from reactive oversight to preventive architecture. We need to shrink the AI risk surface before we shrink monitoring spend. We need to move from people-intensive monitoring to system-enforced controls. AI must be treated like critical infrastructure and not as a productivity tool.” However, this can only happen when trust is designed into systems, enforced by code, and overseen by humans only where judgment is required.
As DPDP enforcement deepens and AI adoption accelerates, India’s privacy landscape is entering an execution-driven era. For CIOs and CISOs, the mandate is clear: embed visibility, traceability, and governance into systems by design. Digital trust will be earned not by policy declarations, but by architectural resilience and operational proof.