India’s Digital Personal Data Protection Act (DPDPA) may be rooted in domestic privacy reform, but its implications stretch far beyond national borders. As organizations around the world grapple with how to handle Indian personal data, the DPDPA’s approach to international data transfers, AI development, and cross-framework compliance takes center stage.
This article explores how the DPDPA compares with other major regulations like the GDPR and CCPA, and how it affects the practices of global businesses, especially those in the AI and technology sectors.
For a detailed breakdown of DPDPA’s domestic scope, lawful processing bases, and consent rules, start with our foundational article to India’s privacy law.
From cross-border data governance to cybersecurity readiness, the DPDPA establishes new expectations and new complexity for companies doing business in or with India.
India’s cross-border data transfer rules under DPDPA: Global impacts and compliance risks
As one of the most globally impactful provisions, India’s cross-border data transfer rules are especially important for multinational businesses. In a global economy cross-border flows are vital. The DPDPA allows foreign transfers of personal data by default, except to countries explicitly blacklisted by the government. This “negative list” approach contrasts with the EU’s adequacy/transfer mechanism model.
India’s strategy is pragmatic: any country lacking adequate data protection or posing security concerns may be restricted, but otherwise, transfers are permitted. In practice, until a blacklist is published, businesses may largely continue international data flows without complex compliance checks. The law does require that fiduciaries implement security measures before export and obtain appropriate consent and notices from data principals.
This regime will require companies to monitor government updates on restricted jurisdictions and document that the transferred data is protected.
However, conflicts remain: For instance, Indian financial regulators (RBI) impose strict localization on banking data. Reconciling sectoral mandates with the DPDPA’s more lenient transfer rules will be a compliance challenge. In any case, unlike strict GDPR-style export controls, the DPDPA avoids cumbersome adequacy applications or standard contracts, favoring a balance between trade and privacy.
For transfer purposes, the DPDPA’s reach is narrower than that of the GDPR. It does not apply extraterritorially to data processing that merely involves profiling or monitoring Indians (unless goods/services are offered).
As noted by privacy experts, offshore AI providers that do not actively market to India could legally scrape or profile Indian data subjects without falling under the DPDPA. This is a significant contrast with GDPR, which explicitly covers profiling of EU residents by non-EU companies.
In short, India’s law welcomes global data flows but carves out specific security-based exceptions via its blacklist mechanism. These cross-border provisions offer a sharp contrast with other data privacy frameworks around the world, especially the GDPR and CCPA.
Comparing DPDPA with GDPR and CCPA
India’s DPDPA shares many elements with other modern privacy laws, but also has distinct features. A high-level comparison with the EU’s GDPR and the US California Consumer Privacy Act (CCPA) highlights the contrasts:
Lawful basis:
Like the GDPR, the DPDPA requires a legal basis for data processing. However, where the GDPR permits six bases (including legitimate interests and contractual necessity), the DPDPA essentially limits firms to consent or narrowly defined “legitimate uses.”
By contrast, CCPA does not use consent-based processing; it is an opt-out regime for sales of data, and grants rights like deletion but does not prescribe a general processing basis.
Consent standard:
Both the DPDPA and GDPR require explicit, informed consent. India’s law mirrors the GDPR’s strict consent definition (“free, specific, informed”) and even envisages digital consent management infrastructure.
In contrast, the CCPA does not hinge on consent for most consumer uses (it bans “sales” unless consumers opt-out).
Data subject rights:
The DPDPA grants rights comparable to the GDPR’s access, correction, and deletion rights. Like GDPR, it mandates notice and allows data subjects to withdraw consent. It adds India-specific rights (grievance officer, nomination).
The CCPA provides somewhat different rights: access, deletion, and data portability (upon request), as well as the right to opt-out of data sale. The DPDPA does not currently recognize an opt-out of marketing or sale, since the concept of “sale” is not in the Act.
Data categories:
GDPR’s “special categories” (sensitive data) framework does not appear in DPDPA; all personal data is governed equally.
CCPA distinguishes “sensitive personal information” in some contexts, but again, only for specific opt-outs.
Processor obligations:
The GDPR and CCPA each impose certain duties directly on processors/service providers (GDPR’s Article 28 contract requirements, CCPA’s obligations for service providers under contract).
By contrast, the DPDPA imposes obligations only on data fiduciaries; processors are indirectly covered via mandatory contracts.
Cross-border transfers:
The GDPR restricts data exports outside the EU unless an adequate level of protection exists or safeguards (e.g., Standard Contractual Clauses) are used.
The DPDPA’s approach is more permissive: transfers are generally allowed unless the government blacklists the destination. In effect, India uses a negative list rather than an adequacy test.
CCPA imposes no restrictions on transferring personal data out of state or the country.
Breach notification:
GDPR requires notification of the authority within 72 hours if there is a high risk to individuals.
DPDPA requires notification of all breaches to the Board and individuals, but sets no fixed deadline or risk threshold.
CCPA has a broad notice requirement for security breaches under California’s civil code, though enforcement focuses on timely consumer notification.
Enforcement and fines:
Under GDPR, regulators can levy fines up to €20 million or 4% of global turnover.
The DPDPA caps fines at INR 500 million (~US$6 million) to INR 2.5 billion (~US$30 million), with adjustments for severity. The maximum is lower than
GDPR’s 4% in euro terms, but still significant relative to the Indian market.
CCPA fines are much smaller (generally $2,500-$7,500 per violation by default). Notably, unlike the CCPA (which allows statutory damages in case of certain breaches), the DPDPA does not create a private right of action for individuals. All DPDPA enforcement will flow through the government Board.
Businesses with GDPR compliance programs will find some familiar elements, but will need to fill specific gaps (e.g., implementing consent for many purposes where GDPR would use alternative bases).
As businesses examine the operational impact of the DPDPA, it’s clear that AI developers face some of the steepest challenges and opportunities.
DPDPA’s impact on AI development
India’s booming AI sector, projected to grow rapidly in the coming years, will feel the DPDPA’s effects acutely.
Consent-centric constraints:
Training many AI models requires large-scale personal data. Because DPDPA only allows processing of non-public personal data with consent or limited exceptions, datasets not explicitly consented to (for example, scraped proprietary user data) may be off-limits.
In practice, companies developing consumer AI may need to redesign data collection so that consent is gathered at the point of data generation, or rely on alternative methods (synthetic data, generative techniques from public sources).
Public data exemption:
Unlike many laws, the DPDPA exempts all personal data that has been made public by individuals (or required to be public). This means raw web content, social media profiles, or public directories, when legitimately public, fall outside the Act. AI developers can therefore harvest publicly available datasets without DPDPA consent obligations.
However, this exemption is not unqualified; if data was originally collected under a different context and later published, questions may arise. Moreover, companies must still respect other laws (e.g., copyright, platform terms of use) when scraping. In essence, the public-data exemption may facilitate open-data AI research, but legal caution is advised.
Research exemption:
The DPDPA’s exemption for research, archiving, and statistical purposes could promote AI R&D, provided clear ethical and technical standards are defined by the rule. If implemented broadly (e.g., covering university and private research), organizations could process sensitive data for model training without individual consent, subject to safeguards. This mirrors how the GDPR permits secondary research use under appropriate safeguards.
Without precise rules, however, institutions may err on the side of caution. Ultimately, a well-designed research exemption could help India build quality AI datasets, but it hinges on government guidance on permissible methods.
Extraterritorial limits:
The DPDPA’s limited territorial reach (only entities offering goods/services to Indians) creates a loophole; foreign AI providers not targeting India can potentially profile or process data on Indians outside the Act’s bounds.
In other words, an AI company based abroad, not actively marketing in India, might train its models on Indian citizens’ data without DPDPA oversight. This could give non-Indian firms an edge, while local companies must comply. If unintended, policymakers may need to address this.
Risk-based obligations (SDFs):
These obligations build on the DPDPA’s broader accountability framework introduced earlier. You can revisit how SDFs are defined and governed in the DPDPA’s core enforcement structure in India’s Digital Personal Data Protection Act (DPDPA) Key Principles, Consent Rules, and Organizational Readiness.
In the AI context, major tech platforms handling vast datasets, such as social networks or cloud AI providers, may be designated as Significant Data Fiduciaries (SDFs), triggering additional requirements like audits and DPIAs.
For example, a large social network or cloud AI provider handling vast personal data could be an SDF. They would then face stringent oversight and compliance costs.
While burdensome, this risk-based tiering is intended to ensure that the data-heavy players driving AI development do not skimp on safety or ethics.
Cybersecurity under DPDPA: New privacy compliance standards for Indian businesses
As the DPDPA raises the bar for privacy governance, it also implicitly calls for stronger cybersecurity. Data protection and cybersecurity go hand in hand, and organizations must meet both obligations to stay compliant and competitive.
The DPDPA reinforces this by demanding enhanced data security from fiduciaries. Every organization must adopt “appropriate technical and organizational measures” to secure data. This echoes and upgrades India’s earlier IT Act provisions, which had only imposed “reasonable security practices.”
In practice, companies will likely need to invest in stronger encryption, access controls, monitoring, and breach response capabilities. They must also ensure data privacy and security by design, which may involve tighter network defenses and regular security audits (such as a DPDPA audit).
Moreover, the Act’s breach notification regime will create synergies with cybersecurity standards. By aligning incident response processes with the law’s requirements, organizations can better coordinate between their IT security teams and legal/compliance teams. The DPDPA also implicitly endorses privacy-enhancing practices by excluding anonymized or public data from its scope.
While the sources here emphasize legal analysis, industry commentary suggests that the DPDPA will spur companies to view cybersecurity as an indispensable investment. Privacy-conscious Indian consumers and partners will increasingly expect robust cyber defenses. In short, complying with the DPDPA will largely mean “secure by default” data handling, strengthening India’s overall cyber resilience.
Charting a global compliance strategy under India’s DPDPA
From global data transfers to AI governance, the DPDPA marks a turning point in India’s privacy landscape, which demands strategic action from organizations worldwide. It establishes a consent-oriented, rights-based regime with familiar elements from the GDPR and other laws while introducing some specific features (consent managers, significant fiduciaries, a negative list for transfers). Its rollout will fundamentally change how organizations operating in India govern data.
Compliance will require collaboration between legal teams and technologists, updating contracts, reengineering consent flows, mapping data, and strengthening security. International companies must note that the DPDPA’s global reach means many US and EU businesses (even without an Indian presence) will fall under its scope if they handle data on Indians.
Compared to GDPR and CCPA, the DPDPA places greater emphasis on consent and state discretion, fewer exceptions for government, and a unique mix of flexibility (in transfers) and strictness (in processing grounds). As India’s regulators publish the rules and activate the Data Protection Board, more clarity will emerge on timelines and technical standards.
In the meantime, privacy, security, and legal professionals should treat the DPDPA as the new baseline for data governance in India. Embracing its principles, robust consent, respect for individual rights, and rigorous security, will not only ensure compliance but also build trust in India’s rapidly digitizing economy.
