Data Privacy and Protection Day 2026: Seven Ideas to Celebrate and Make it Count
January 28 marks Data Privacy Day, and this year's theme cuts straight to the heart of a growing tension in European business: "You have the power to take charge of your data." The message is directed at individuals, but the implications for companies are significant.
The European Data Protection Board has made transparency obligations an enforcement focus for 2026. This means the vague privacy policies and buried consent options that many businesses have relied on are now under the microscope. Regulators aren't just asking whether you comply with GDPR. They're asking whether your customers can actually understand and exercise their rights.
For companies processing personal data, and that's essentially every European business, this shift demands action. The good news? Making data management genuinely accessible to customers isn't just about avoiding fines. It creates trust, reduces support overhead, and positions your business as one that respects the people it serves.
What the EDPB's Transparency Focus Means in Practice
When the EDPB identifies a theme for coordinated enforcement, it signals that supervisory authorities across the EU will prioritize this area during enforcement actions and investigations. For 2026, transparency isn't a suggestion. It's a target.
Under GDPR Articles 12 to 14, companies must provide information about data processing in a "concise, transparent, intelligible and easily accessible form, using clear and plain language." Most businesses, technically, meet this requirement by publishing privacy policies. But technical compliance and genuine transparency are not the same thing.
Data Protection Authorities will examine whether your privacy communications are actually understandable to the average person. They'll assess whether data subject access requests can be submitted and fulfilled without friction. They'll evaluate whether your AI systems, which often process personal data in ways customers don't expect, are clearly explained.
A 47-page legal document that ticks every GDPR box but requires a law degree to interpret will not satisfy this standard. Neither will a simple privacy policy if your AI chatbot is making decisions about customers without their informed awareness.
The AI Transparency Challenge
Even if AI is not directly interwoven within the scope of new transparency obligations, the timing of this enforcement focus is not coincidental. The whole ecosystem is becoming more complex as new technologies grow. AI systems are now embedded across European businesses, from customer service to fraud detection algorithms to personalization engines. Each of these systems processes personal data, often in ways that surprise the people whose data is being used.
Consider a simple example: a customer contacts your support team, and an AI system analyses their message to route it appropriately. This seems harmless, but the AI might also assess sentiment, predict churn risk, or flag the customer for different treatment based on their history. None of this is inherently problematic, but customers deserve to know it's happening.
The EU AI Act, now entering enforcement, adds another layer. AI systems require specific transparency measures, and systems must inform users when they're interacting with AI rather than humans. Companies that haven't audited their AI usage for transparency requirements are facing a compliance gap that regulators may notice even though this does not an obligation yet.
German businesses face particular scrutiny here. The BSI and BaFin have both signaled increased attention to algorithmic transparency, especially in financial services. If your company operates in Germany and uses AI to process customer data, transparency documentation should already be a priority.
Seven Practical Steps to Build Genuine Transparency
Meeting the EDPB's transparency standards requires more than policy updates. It demands operational changes that make data management genuinely accessible. Here are specific actions that create real impact.
Create a Privacy Dashboard That Actually Works
The most effective way to empower customers is giving them direct control. A self-service privacy dashboard should allow individuals to see what data you hold about them, correct inaccuracies, download their information, and request deletion, all without contacting support.
Many companies have built privacy centers that technically exist but are nearly impossible to find or use. Your dashboard should be accessible within two clicks from your main navigation. It should use plain language, not legal terminology. It should complete most requests automatically, without requiring manual review for standard operations.
One practical benchmark: if a customer wants to download all their personal data, can they complete this in under three minutes? If not, your process needs simplification.
Map and Document Your AI Data Processing
Before you can be transparent about AI, you need to understand it yourself. Most companies have deployed AI tools without systematic documentation of what personal data they access, how they process it, and what decisions they influence.
Conduct a complete inventory of AI systems that touch personal data. For each system, document the specific data inputs, the processing logic (at a level customers can understand), the outputs and decisions, and any automated decision-making that affects individuals.
This exercise often reveals surprises. Marketing teams may have implemented AI tools that access customer data without IT's knowledge. Third-party integrations may include AI components with unclear data practices. You cannot be transparent about processing you haven't mapped.
Rewrite Your Privacy Policy for Actual Humans
Privacy policies typically fail transparency tests for a simple reason: they're often written to satisfy lawyers, not inform customers. A policy that protects you legally but confuses customers will not satisfy the EDPB's requirements.
Consider restructuring your privacy documentation into a layered approach. Create a one-page summary that covers the essential points in 500 words or fewer, using language a 14-year-old could understand. Follow this with a more detailed explanation for those who want specifics. Reserve the comprehensive legal document for reference.
For each type of data processing, answer these questions in plain language: What data do we collect? Why do we need it? Who sees it? How long do we keep it? What can you do about it?
Test your privacy communications with actual customers. If they cannot accurately describe your data practices after reading your policy, the policy has failed its purpose.
Build Transparency Into AI Interactions
Every time a customer interacts with an AI system, they should understand that AI is involved and how it affects their experience. This doesn't require complex technical explanations. Simple, clear notifications work best.
When an AI chatbot handles initial customer service, it should introduce itself as an AI assistant and explain how to reach a human if preferred. When AI personalizes product recommendations, a small note explaining "These suggestions are based on your browsing history" builds understanding without interrupting the experience.
For automated decisions that significantly affect customers, such as credit decisions, fraud flags, or service eligibility, provide a meaningful explanation of the factors considered. GDPR Article 22 requires this for purely automated decisions, but good practice extends this to any AI-influenced decision with material impact.
Make Data Subject Requests Frictionless
The right to access, correct, or delete personal data is meaningless if exercising it requires a legal battle. Yet many companies have made these requests unnecessarily difficult, whether through obscure submission forms, excessive identity verification, or slow response times.
Streamline your process by accepting requests through multiple channels including email, web form, and in-app. Verify identity through methods customers already use, such as account login, rather than demanding passport copies for routine requests. Acknowledge requests immediately with a clear timeline. Automate fulfilment for standard cases, reserving manual review for complex situations.
Track your metrics here. If your average response time for data subject requests exceeds two weeks, or if you require back-and-forth communication to complete most requests, there's room for improvement.
Communicate Proactively About Changes
Transparency isn't just about responding to questions. It means proactively informing customers when something significant changes about how you use their data.
Develop a communication framework that triggers notifications when you add new AI systems that process personal data, when you share data with new third parties, when your retention periods change, or when you begin using data for purposes beyond what customers originally expected.
These notifications should be clear and specific. Rather than announcing "We've updated our privacy policy," explain what actually changed and why it matters. This approach builds trust and reduces the surprise factor that often leads to complaints and regulatory attention.
Train Your Team on Transparency
Your customer-facing staff are often the first point of contact when someone has questions about their data. If they cannot answer basic privacy questions confidently and accurately, your transparency efforts fall short.
Develop accessible training materials that cover what personal data your company collects and why, how customers can access and control their data, what your AI systems do and how to explain them, and how to handle data subject requests properly.
This training doesn't require making everyone a GDPR expert. Focus on equipping staff to answer common questions and escalate complex ones appropriately. A support agent who can clearly explain how to download personal data creates better outcomes than one who transfers every privacy question to legal.
The Business Case Beyond Compliance
Meeting transparency requirements isn't just about avoiding fines, though the potential penalties make compliance a clear priority. Companies that genuinely embrace transparency often discover unexpected benefits that truly impact their bottom line such higher customer retention and advocacy.
Support costs decrease when customers can manage their own data without assistance. Trust increases when people understand how their information is used. Competitive differentiation emerges in markets where privacy concerns influence buying decisions.
For B2B companies, transparency capabilities increasingly appear in vendor assessments. Enterprise customers want to know that their employees' and customers' data is handled properly. Demonstrating mature privacy practices can accelerate sales cycles and expand market access.
The companies that will thrive under increased regulatory scrutiny are those that view transparency as an opportunity rather than a burden. When customers feel in control of their data, they engage more confidently. When regulators see genuine effort toward transparency, they focus their attention elsewhere.
Start Now, Not Later
The EDPB's focus on transparency for 2026 means that companies without clear programs already face increased risk. Audits and investigations launched this year will examine current practices, not future plans.
Begin with an honest assessment of your current transparency posture. Can customers easily understand what data you hold? Can they access and control it without friction? Do they know how AI affects their experience? If the answer to any of these questions is no, prioritization is required.
Kertos helps European companies build compliance programs that include robust transparency measures, from AI inventories to privacy dashboards to data subject request automation. Our platform makes it practical to achieve genuine transparency, not just technical compliance.
Take the first step today. Request a free assessment of your transparency readiness and see exactly where your program stands against EDPB expectations.
