The Data Security Council of India and PrivaSapien have jointly released a new industry report outlining how enterprises can operationalise India’s Digital Personal Data Protection (DPDP) Act through privacy engineering and privacy-enhancing technologies (PETs) as organisations prepare for stricter compliance and AI governance requirements.
The report, titled Operationalising DPDP and Privacy by Design through PETs, was unveiled at FINSEC 2026 in Mumbai and focuses on embedding privacy safeguards directly into enterprise systems, workflows, and data architectures rather than treating compliance as a standalone legal or governance function.
The release comes at a time when Indian enterprises are accelerating AI adoption while simultaneously preparing for the DPDP Act’s full enforcement timeline, which introduces significant accountability requirements and penalties for non-compliance. The report notes that organisations remain divided between traditional governance, risk and compliance (GRC) approaches and the need for technical safeguards mandated under DPDP.
According to the report, traditional methods such as manual DPIAs, consent collection frameworks, and cookie management systems alone are insufficient to address the operational risks associated with AI-led data processing environments. Instead, the report argues that data protection must be engineered into systems before data processing begins.
From a technology standpoint, the report positions privacy engineering as an emerging discipline that combines cybersecurity, architecture design, cryptography, anonymisation, consent management, and AI governance into a unified operational framework.
The paper proposes a four-stage implementation model spanning lawful purpose definition, consent governance, privacy threat modelling, data protection impact assessments, and technical enforcement mechanisms using Privacy Enhancing Technologies.
The report highlights several PET categories, including mathematical anonymisation, differential privacy, homomorphic encryption, synthetic data generation, private set intersection, and zero-knowledge proofs. These technologies are increasingly being evaluated across sectors including BFSI, healthcare, telecom, and AI-driven digital platforms where large-scale personal data processing is expanding rapidly.
A major theme of the report is the distinction between cybersecurity and privacy engineering. While cybersecurity focuses on protecting data at rest and in transit, privacy engineering governs how legitimately accessed data is processed, minimised, anonymised, shared, and retained within enterprise systems.
The report argues that organisations may remain technically secure while still failing privacy compliance obligations if underlying systems are unable to demonstrate lawful processing, consent traceability, data minimisation, and purpose-bound usage across AI and analytics workflows.
According to Abilash Soundararajan, CEO and Co-Founder of PrivaSapien, the DPDP framework places unprecedented emphasis on technical safeguards as a core compliance requirement. He noted that India’s evolving digital infrastructure initiatives, including DEPA, the JAM trinity, and UPI, will increasingly rely on privacy-enhancing technologies to unlock data responsibly while protecting citizens from harm.
Vinayak Godse, CEO, DSCI stated that organisations adopting privacy-enhancing technologies are moving beyond baseline compliance towards embedding privacy directly into the architecture of digital systems, while also strengthening stakeholder trust and enabling responsible innovation.
The report further recommends that India’s future regulatory and enforcement frameworks formally recognise verifiable deployment of PETs as a mitigating factor during compliance proceedings. It also calls for privacy engineering to be formalised as a dedicated technical discipline across academic and enterprise ecosystems to address India’s growing implementation capacity gap.
The release reflects a broader shift across India’s enterprise technology landscape, where organisations are increasingly integrating AI governance, data protection, privacy engineering, cybersecurity, and responsible innovation frameworks as part of long-term digital transformation and regulatory readiness strategies.