Seven GDPR principles you must know (and comply with)

The seven GDPR principles still form the backbone of data protection in 2025. They’re what regulators look at first, and what most companies struggle to apply consistently. As AI, automation, and cross-border data flows grow in 2025, adhering to these principles is more important than ever to avoid legal risks and build trust with customers.

The cost of getting them wrong keeps rising.  In May 2025, TikTok was fined €530 million for improperly transferring users’ personal data to China without implementing adequate protection as required by GDPR. 

Similarly, the Spanish data protection authority (AEPD) fined Orange Espagne €0.2 million for unlawful data processing, a violation of GDPR Article 6.

Both cases stemmed from a failure to follow the basics.

In this article, we’ll break down the seven GDPR principles you must know and comply with to ensure data security and privacy. We’ll also show you how platforms like Scrut help teams stay compliant day-to-day, by automating controls, tracking evidence, and keeping you audit-ready. 

What are the seven GDPR principles?

GDPR outlines seven key principles that define how personal data should be handled across the EU. These principles aren’t just theoretical. They’re the lens regulators use when evaluating compliance. Miss the mark, and fines can follow. 

1. Lawfulness, fairness, and transparency 

You must have a valid legal basis for processing personal data. If the legal basis doesn't meet any of the six conditions stated in Article 6 of the GDPR, you may be liable for fines, as seen in the case of Replika. The San Francisco-based startup paid €5.64 million for processing user data without a legal basis. 

Your legal basis is considered valid if it meets any one of the following six criteria:

• Consent: You’ve received clear, informed user consent for a specific purpose. This could be via a website form, app opt-in, or SaaS onboarding flow.
• Contractual: You need to process data to fulfil a contract. For example, shipping a product or provisioning a paid service requires you to collect and process customer personal data such as name, address, and other details.
• Legal obligations: You’re processing data to comply with a law (think tax reporting or payroll processing).
• Public interest: Data is processed as part of a task carried out in the public interest, often by public bodies or through public–private partnerships. The public interest must be genuine and backed by EU or member state law.

• Vital interest: You’re protecting someone’s life.
• Legitimate Interests:  Data is processed for the purposes of the legitimate interests pursued by the controller, except where overridden by the data subject's rights).

But it’s not just about legality. Fairness and transparency matter too.

Fairness means users should never be misled or kept in the dark. Transparency means explaining—upfront—why you're collecting data, how you’ll use it, and where it will be stored or shared.

2. Purpose limitation

This principle sets boundaries around data usage. It requires you to collect personal data for a specific, legitimate reason and not quietly repurpose it later for something else. For example, an e-commerce company collects customer data (name, email, phone number) to fulfill an order. Later, the marketing team starts using that data for promotions without asking for explicit consent.

That’s a violation. 

To stay compliant, define the purpose at the point of collection and communicate it clearly through your privacy notice. Monitor how teams use the data. If you want to use it for something new, you’ll need fresh consent.

There are a few exceptions under Article 89(1), where further use isn’t considered incompatible with the original purpose like:

• Archiving personal data for public interest.
• Scientific or historical research.
• Statistical purposes.

3. Data minimization

Only collect data that's relevant and necessary to your purpose. Whether you are a consumer brand or a B2B  company, ask: Do we really need this data to serve the user or meet our legal obligation? 

For example, when onboarding a consumer, collect only their name, email, and address, and avoid personal identifiers unless legally required. Collecting details for product demos from enterprise customers? Avoid gathering detailed company financials unless they are essential for customizing the product or pricing.

Following data minimization principles not only support GDPR compliance but also reduce your data liability footprint and simplify breach response planning. 

Less data means less risk.

4. Accuracy 

You’re responsible for keeping personal data accurate and current. For a B2B SaaS company, that means user profiles, billing contacts, and access roles should always reflect reality. 

Inaccurate records put you at compliance risks and also lead to poor user experience. Conduct periodic checks and audits to maintain the sanctity of data. 

Build in regular checks and audits to keep your data clean. Give users clear ways to flag or fix errors. In an enterprise setting, that could mean allowing authorized users to update corporate information with the right checks in place. 

For consumer businesses, it could be as simple as letting customers update their email, phone number, or address directly in their account dashboard.

5. Storage limitation

Don’t store personal data longer than is necessary for the purpose for which it was collected. For example, the  Financial Times has specified retention periods for different data types in its privacy policy.

Create a data retention policy to delete data that is well past its retention period. Delete data once it has served its purpose, or else you risk costly penalties and increased costs due to the storage space needed. 

Without this, you risk costly GDPR penalties and unnecessarily increase your data breach liability and exposure.

The only exception to this principle is if you’re archiving personal data in the public interest for scientific or historical research or statistical purposes in accordance with Article 89(1).

Put the right technical and organizational measures in place to protect the data subject’s rights and freedoms, as required under GDPR.

6. Integrity and confidentiality 

Protect data against unauthorized or unlawful processing and accidental loss or corruption. Set up technical safeguards, such as encryption, to prevent data damage. Leverage organizational measures, including access controls and regular audits, to prevent unauthorized access and processing. 

Match your security measures to the sensitivity, volume, and risk level of the data.

7. Accountability

Document data processing activities and conduct data protection impact assessments (DPIAs) to demonstrate compliance with GDPR. Conduct risk assessments and appoint a data protection officer (DPO) when necessary.

(Do note: A DPO is mandatory under Article 37 for public authorities. This is mainly for organizations whose core activities involve large-scale, regular monitoring of individuals or large-scale processing of special categories of data.)

Organize training on data security and privacy for your team to familiarize them with their obligations and remove ambiguity about roles and responsibilities. 

Simply claiming compliance is not enough; you must prove it through auditable evidence, ongoing monitoring, and proactive governance practices.

Pitfalls in enforcing the seven GDPR principles

Even with the best intentions, many organizations fall short when applying the GDPR’s seven principles. The missteps are often avoidable and avoiding them can protect you from costly fines and reputational damage.

1. Opaque privacy practices compromise transparency

Privacy notices are often hidden in obscure sections of websites. Users can't comprehend policies filled with legal jargon and are unable to understand what data is collected and how it's used, defeating the purpose of privacy notices. 

2. Overreliance on AI-driven data processing

Organizations are using AI in more business functions than in previous years, with 78% using AI in at least one function compared to 55% in 2023. As organizations increasingly adopt AI for personalization, profiling, and automation, they fail to ensure the lawfulness and fairness of such processing. Data subjects are unaware of how their data is used to train models, violating transparency and purpose limitation principles.

3. Inadequate consent mechanisms on emerging platforms

With the rise of new platforms such as voice assistants and wearables, many organizations struggle to obtain valid, informed consent. Consent interfaces on these platforms are either absent or too complex, leading to non-compliance with lawful basis requirements.

4. Outdated data retention policies for hybrid work and cloud

If you’ve moved to remote or hybrid work, you’ve likely adopted new collaboration tools and expanded your cloud storage. If your retention and deletion policies haven’t kept pace, you may be storing personal data in unmanaged tools, backups, and shadow IT, which is a breach of the storage limitation principle.

5. Repurposing data without user approval

Using customer data for something you never told them about like turning demographic data into targeted marketing violates purpose limitation and erodes trust. Always get fresh consent before repurposing data.

6. Collecting more data than needed

If you collect personal data you don’t need, just in case it’s useful later, you’re breaking data minimization rules, increasing storage costs, and creating more breach risk.

You can also run into trouble by letting inaccurate records pile up or skipping clear data retention schedules. Both put you at legal risk and make effective data management harder.

How Scrut helps you turn the seven GDPR principles into everyday practice

Scrut makes it easier to turn the seven GDPR principles into action and keep them that way. With over 1,400 pre-mapped controls across 50+ frameworks, the platform automates compliance workflows, centralizes evidence, and keeps you audit-ready without endless manual tracking.

Here’s how:

1. Ready-to-use templates and out-of-box frameworks

Scrut's GDPR compliance framework includes pre-mapped controls, policies, and workflows, accelerating implementation. It's 50 expert-vetted GDPR-compliant policies allow you to establish a robust data protection framework quickly. 

2. Automated compliance workflows and consent modules

From DSAR responses to policy updates and audit prep, Scrut automates critical GDPR processes so you don’t miss a step.

The tool automatically captures up to 80% of required evidence, giving you a 100% audit-ready view, with every piece of evidence mapped to its corresponding GDPR control. The evidence review planner flags upcoming and overdue items, so you can stay ahead of reviews and prevent any violations.

Consent modules record and update user preferences in real time, ensuring you handle data rights consistently and transparently.

3. Data mapping tools keep track of processing activities

The platform's automated data mapping tools scan and identify systems handling personal data across your organization. It helps you identify and categorize all data processing activities, ensuring each activity has a valid legal basis.

The tool helps you quickly locate and retrieve personal data, making DSAR responses within the 30-day window routine, not a scramble. Every request is tracked end-to-end with built-in audit trails.

4. Role-based task management

Scrut regulates data access by assigning GDPR-related tasks based on roles to restrict access to sensitive data. The platform sets deadlines, tracks progress, sends reminders, and manages accountability through audit logs. This reduces the risk of compliance gaps and ensures data security and privacy.

5. Real-time compliance dashboard

See your GDPR status at a glance: live risk scores, open DPIAs, policy progress, and remediation tasks. Custom alerts notify you of issues like expiring certificates or overdue consent renewals before they impact compliance.

With Scrut, every GDPR principle—from data minimization to purpose limitation to accountability—is reinforced through predefined controls, automation, and continuous monitoring.

You get real-time visibility, fewer manual processes, and a stronger privacy program.

Schedule a demo today to see how Scrut can help you maintain continuous compliance with GDPR. 

FAQs

What are the seven principles of GDPR?

The seven principles of GDPR are:

• Lawfulness, fairness, and transparency.
• Purpose limitation. 
• Data minimization.
• Accuracy.
• Storage limitation. 
• Integrity and confidentiality. 
• Accountability.

These principles form the foundation of GDPR and guide organizations on how to manage the personal data of EU  citizens. 

What is the accountability principle?

The principle requires organizations to take responsibility for complying with data protection rules and prove their compliance. It includes maintaining documentation, conducting assessments, training staff, and showing regulators that proper data handling practices are in place.

How do companies follow GDPR principles?

Companies follow GDPR principles by obtaining user consent, collecting only necessary data, securing information, and deleting data in accordance with their data retention policies. They limit data usage only for the stated purpose and demonstrate compliance through audits, impact assessments, and training.

Why is data minimization important?

Data minimization reduces privacy risks and limits exposure in case of breaches. By collecting only necessary information, organizations protect individuals' rights, lower storage costs, and simplify data management and security responsibilities.

What are the core GDPR compliance requirements?

Core GDPR compliance requirements include obtaining affirmative consent, ensuring data accuracy, and limiting data collection and retention. Ensure the security of data and provide users with the right to access and delete data. Document processing activities and demonstrate accountability through policies, assessments, and regular staff training.