The new Digital Personal Data Protection (DPDP) Act, 2023, has got operational teeth through the DPDP Rules. They may transform the digital data economy into a regulated market. They signal the start of a new infrastructure cycle. Broad obligations will become actionable workflows for firms handling personal data. In doing so, they promise to open a market for privacy-technology start-ups while raising a new friction for India’s Artificial Intelligence (AI) ambitions.
The DPDP Rules give the digital economy a sharper set of guardrails, which include clearer consent mandates, data minimisation, strict breach-notification obligations, and penalties (up to Rs 250 crore for major failures). For businesses, they shift privacy from a compliance checkbox to an operational cost. For tech start-ups, it implies a sizable runway. The Government has given an 18-month transition window but is in talks to compress the period for the larger firms.
Incidents of data breach and misuse are mounting. According to an IBM report (2025), the average organisational cost of a data breach in India is Rs 220 million ($2.7 million), up 13 per cent from the previous year. A state-wise projection of identity-theft and data-breach incidents estimates 8,500 such cases by 2025, with Karnataka expecting 2,500 incidents. In a telling example, a cloud server holding 2.73 lakh bank-transaction records was exposed via unsecured access. In the fintech realm, nearly a quarter of the firms surveyed reported losses over $1 million from cyber incidents in the past three years. These are symptoms of a digital economy lacking architectural controls, and the DPDP Rules will rectify them.
Not all the industries face the urgency. Those that collect large volumes of sensitive data, track behaviour in real time, or process minors’ information have red flags in business models. Financial services, insurers, and fintech top the list. Such firms process vast troves of KYCs, transactions, and demographic and behavioural data. Not to mention the passwords. Under the new rules, each step of data collection, processing, storage, and deletion must be justified. The shift is less about legal theory and more about systems overhaul.
Healthcare, diagnostics, and tele-medicine are crucial. Medical records are among the most sensitive categories of personal data, and multiple studies show that Indian health-tech firms lag in privacy compliance. The rules force them into new protocols around consent, secondary use of data, and retention limits.
Next comes ed-tech and gaming where data about minors introduces extra layers of complexity. The rules require verified parental consent, and impose stronger safeguards for child-data processing. E-commerce, D2C brands, and retail, which were previously exempt from heavy scrutiny, will find themselves in an unfamiliar terrain as CRM databases, behavioural profiles, and personalised marketing will need to be re-architected. Even mobility, logistics, and ride-hailing track location, and biometric or identity data. They face elevated compliance burdens. The sharper liability means each of these verticals becomes a natural buyer for privacy stacks.
A news report reported the size of India’s data-protection market at $5.34 billion in 2024, and is expected to rise to $27.77 billion in the future. The global data-privacy software market stands at $3.84 billion, and is projected to reach $45.13 billion by 2032. Few regulatory cycles have unlocked such a wide, multidimensional technology market. GST did. UPI did. The DPDP law and rules may follow the same trajectory in data governance.
What makes this moment distinct is that compliance is no longer a back-office activity but an operational requirement. Sectors that handle sensitive data will need automated consent logs, deletion engines, and breach-response systems. Platforms that handle minors will require parental-consent workflows, and age-verification modules. A privacy-tech ecosystem will emerge because thousands of companies will no longer be able to function without it.
The timing is fascinating. This is the time when the start-up ecosystem is accelerating. As of mid-2025, the number of recognised start-ups in India surpassed 180,000. With state policies supporting such firms, the infrastructure around founding and scaling young firms is strengthening. Privacy-tech may become the next frontier of enterprise SaaS, following HR, fintech infra, and cloud-native stacks.
This means cohorts of founders, venture funds, and incubators will chase regulation-led markets. Beyond compliance tech, the Rules open adjacent opportunities. Synthetic-data startups will find fertile ground now that raw data collection is constrained. Businesses may rethink models heavy on behavioural tracking, and shift toward “data-light” or “privacy-disciplined” growth engines. Programmatic-advertising may face CPM inflation or reduced retargeting pools. Brands may migrate to first-party or zero-party data strategies.
Indian cloud and data-centre providers may be the beneficiaries as enterprises prefer domestic storage, encryption frameworks, and audit-compliant infrastructure. Talent markets will tighten. Certified privacy officers, data-governance leads, and audit specialists will command premium salaries. This may result in boosting start-ups that create lightweight, low-cost compliance tools for small firms, and enable the former to scale up the way Tally, Zoho, and Razorpay did.
India added over 350 megawatts of new data-centre capacity between 2022 and 2024. With DPDP enforcement, enterprise cloud migration may accelerate. Local sovereign-cloud architectures may receive fresh interest as firms seek lower-risk environments. There may be a revaluation of business models. Start-ups built on aggressive data capture or cross-app tracking will not enjoy the same growth. Investors often begin pricing regulatory risk into valuations. Data-light or privacy-disciplined models may command premiums. This can reshape the Indian start-up landscape over the next five years.
The rise of privacy-tech does not occur in a vacuum. It intersects with AI ambitions. Studies suggest that 20-30 per cent of model-training cost arises from data cleaning and preparation. With more stringent consent, and deletion obligations the costs will rise. Model retraining cycles may lengthen as users opt out, or request purging of data. Sectors that depend on behaviour-rich data may feel the slowdown. Yet history suggests that the pause may not be permanent. In Europe, firms adopted synthetic data, federated learning, and privacy-preserving machine learning. India may follow the same path. If this happens, the friction can become the catalyst for a more sophisticated AI ecosystem built on cleaner, more trustworthy data.
India’s digital economy has expanded faster than its governance norms. The DPDP Rules begin to reverse this imbalance. They create a market where privacy is not an abstract right but an operational discipline. Start-ups that build the tools to operationalise it will shape the next decade of enterprise technology. The rise of privacy-tech is not just a side-story to DPDP, but the centre-piece.
