DPDP Establishes New Privacy Roles Transitioning from Policy to Code

BENGALURU: India’s push for data privacy is driving demand for a new category of technology professionals skilled in translating regulations into operational systems. As companies navigate complex data environments and the rapid adoption of artificial intelligence (AI), the need for expertise in implementing the Digital Personal Data Protection (DPDP) Act is becoming increasingly critical.

The Shift from Compliance to Technical Implementation

Traditionally, data privacy has been managed by legal, compliance, and cybersecurity teams. However, with the impending implementation of the DPDP Act, organizations are realizing that having policies on paper is insufficient. “The challenge is that organisations are moving from legal and advisory work to putting structured policies and controls in place,” said Sachin Salian, senior VP and global business and delivery head at Writer Information. This shift from regulatory compliance to technical compliance has created a shortage of professionals capable of engineering privacy controls into enterprise systems.

“There is definitely a supply gap,” noted Srinivas L, joint CEO and joint MD of 63SATS Cybertech. While many firms focus on advisory services, such as gap assessments and policy documentation, there is a scarcity of engineering talent. Companies face significant challenges when implementing requirements like allowing customers to withdraw consent. “You have built these networks for the last 15 or 20 years, and there is no consent mechanism built into that data,” Srinivas explained. Rebuilding complex data flows to accommodate consent withdrawal and data erasure is often necessary.

Legacy Systems Complicate Compliance

Demonstrating the effectiveness of privacy controls across systems is another hurdle for companies. “If tomorrow I ask whether you have deleted the data, you need to show the evidence,” Salian stated. While new tools for consent management, cookie management, and data mapping are emerging, the process remains complex. Legacy technology, including mainframes and COBOL-based databases, complicates compliance with modern consent and data lifecycle requirements.

AI’s Impact on Data Privacy

For Kapil Mahajan, global CITO of Allcargo Group, AI has fundamentally altered the privacy landscape. AI can analyze multiple legitimate data points to infer information that customers may not have explicitly provided. “The whole privacy question was, who can access this data? That, to me, shifted,” Mahajan remarked. He emphasized that the focus has now shifted to what organizations are permitted to infer from the data. “The architecture now has to evolve from protecting data to governing intelligence,” he added. “Just because technology can know something doesn’t mean an enterprise should know it.”

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