GDPR & AI Act 2026: How CRM solutions make data protection and AI fit

With the adoption of the AI Act in 2024, the European Union has created a uniform framework for the use of artificial intelligence. At the same time, the GDPR remains the central basis for handling personal data.

This increases the requirements for companies, especially in the interaction between data and AI. CRM solutions play a key role here: They bundle customer data, map processes and are increasingly becoming the basis for AI-supported applications.

For medium-sized companies in particular, a powerful CRM is crucial in order to implement regulatory requirements securely and at the same time exploit the potential of AI along the customer journey.

This article shows what CRM managers should look out for in 2026 and how they can future-proof their CRM.

What to expect in this article

GDPR - data protection remains central

The EU AI Act - AI in CRM gets clear rules

Consent management becomes strategic

Using AI features in CRM responsibly

Data minimization vs. Personalization pressure

Audit of existing CRM systems

Interfaces and third-party provider risks

Lifecycle management: Deletion concepts and data life cycle

Organizational and procedural measures

Checklist: 10 questions that CRM managers should ask themselves in 2026

Conclusion: Think of GDPR & the AI Act as working together

GDPR - data protection remains central

In 2026, the General Data Protection Regulation (GDPR) will remain the authoritative basis for the handling of personal data. Legally compliant processing is still essential, especially in the B2B environment, where business contact data is frequently used.

For CRM managers, this means in particular documenting consent properly, carefully weighing up legitimate interests and consistently implementing the principle of data minimization. These requirements have a direct impact on central CRM functions such as lead scoring, tracking and profiling.

At the same time, the requirements for transparency and traceability are increasing. Companies must be able to prove at any time, the legal basis for data processing and how corresponding processes are mapped in the CRM system.

Practical check: GDPR in CRM 2026

• Are consents documented completely and in an audit-proof manner?
• Are legitimate interests clearly justified and regularly reviewed?
• Have you ensured that only necessary data is collected and used?
• Are all data-related processes in your CRM documented in a traceable manner?

The EU AI Act - AI in CRM gets clear rules

With the AI Act, the European Union is creating binding guidelines for the use of artificial intelligence for the first time - including in CRM. Typical use cases such as lead scoring, sales forecasts or automated customer interactions are therefore increasingly subject to regulatory requirements.

The focus is on risk classifications, transparency obligations and extensive documentation requirements. Companies must clearly explain how AI systems make decisions and what data is used for this.

Requirements regarding the explainability of AI results and the possibility of human oversight are also particularly relevant for CRM managers. Automated decisions must not be non-transparent or uncontrollable.

Consent management becomes strategic

With increasing regulatory requirements, consent management is evolving from a mandatory operational task to a strategic success factor. Companies must not only obtain consent, but also manage it in a differentiated, transparent and systematic manner.

Granular consents are required that make it possible to clearly separate different purposes of use. At the same time, first-party data strategies are gaining in importance, as third-party cookies are increasingly losing relevance. The CRM becomes the central instance for managing and documenting all consents.

Established procedures such as double opt-in are also coming under greater scrutiny and should be reviewed with regard to user-friendliness and verifiability. Seamless documentation remains an ongoing task that must be properly anchored in the CRM from a technical and organizational perspective.

Using AI features in CRM responsibly

The use of AI in CRM opens up new potential, but also requires clear guidelines. Before introducing AI-supported functions, companies should carry out a structured risk analysis and evaluate the respective use cases.

In addition, company-wide AI governance is becoming increasingly important. It defines binding rules for the use, monitoring and further development of AI systems in CRM.

A key aspect of this is ensuring human oversight: Automated decisions must remain verifiable and, in case of doubt, be able to be corrected by humans. CRM managers should also critically examine their technology providers, for example with regard to compliance evidence and regulatory standards.

Data minimization vs. Personalization pressure

A central area of tension in CRM will also remain in 2026: While marketing and sales are increasingly relying on a personalized approach, legislators are demanding consistent data minimization.

For companies, this means consciously weighing up which data is actually necessary and how it can be used sensibly. The aim is to create relevance for the customer without collecting or storing unnecessary data.

This is where the principle of "privacy by design" comes in: Data protection is integrated into processes and systems from the outset instead of being added later. If implemented correctly, this can not only reduce regulatory risks, but also create trust and thus become a competitive advantage.

Audit of existing CRM systems

A structured look at the existing CRM system is the first step towards harmonizing regulatory requirements and AI use. Many companies are already using AI-supported functions - often without full transparency about how they work and what data they are based on.

CRM managers should therefore systematically record which AI modules are already in use and where data is automatically enriched or processed. Equally important is the complete documentation of all data flows both within CRM and across system boundaries.

Practical check: CRM audit

• Which AI-supported functions are currently in use?
• Where is data automatically enriched or changed?
• Are all data flows fully documented and traceable?

Interfaces and third-party provider risks

Modern CRM systems are rarely used in isolation. Instead, they are closely networked with other systems such as customer data platforms (CDP), marketing automation solutions and tracking tools. However, these interfaces also increase complexity and regulatory requirements.

Particular attention must be paid to international data transfers, especially to third countries such as the USA. Companies must ensure that all legal requirements are met and that suitable protective measures are in place.

In addition, existing data processing agreements should be regularly reviewed and updated to ensure transparency and legal certainty.

Lifecycle management: Deletion concepts and data life cycle

An often underestimated but central component of GDPR compliance is clearly defined lifecycle management for data. Companies must determine how long data may be stored and when it is to be deleted or archived.

Automated deletion routines help to implement these requirements efficiently and minimize risks. At the same time, there is tension between regulatory requirements and marketing and sales interests regarding using data for as long as possible.

A clearly documented data life cycle with traceable deletion periods and defined processes that are technically mapped in the CRM system is therefore crucial.

Organizational and procedural measures

In addition to technical and legal requirements, organizational framework conditions are becoming increasingly important. Companies need to define clear responsibilities, coordinate processes and prepare their employees specifically for dealing with AI and regulatory requirements.

A key issue here is role clarification: Who is responsible for the use of AI in CRM? In practice, it is clear that this responsibility cannot be isolated to a single function. Rather, close cooperation between marketing, IT and legal is required in order to take both innovation potential and regulatory requirements into account in a balanced manner.

At the same time, the need for targeted training measures is increasing. CRM teams must be enabled to understand AI-supported functions, recognize risks and use them responsibly. In addition, companies should define internal guidelines that clearly regulate the use of AI in campaigns and customer processes and provide guidance in day-to-day work.

Checklist: 10 questions that CRM managers should ask themselves in 2026

If a CRM function processes personal data and uses AI, the GDPR and AI Act must be checked and documented in parallel. The following questions will help you to critically examine your own status quo and identify key areas for action:

Conclusion: Think of GDPR & the AI Act as working together

As demanding as the regulatory requirements are, they also offer companies the opportunity to clearly differentiate themselves. Those who consistently implement data protection and the responsible use of AI create trust and strengthen long-term customer relationships.

Transparent communication plays a central role here. Companies that openly explain how they use AI and how they handle data, create orientation and security for customers. This can be a decisive competitive advantage, especially in the B2B environment.

A common mistake in practice is to consider the GDPR and the AI Act separately. In fact, both sets of regulations work in parallel and complement each other in many areas.

• The GDPR regulates the handling of personal data - from the legal basis and transparency to the rights of data subjects and data security.
• The AI Act focuses on the AI system itself - in particular on risk assessment, transparency, governance and human oversight.
• As soon as AI is used in CRM to process personal data, both sets of rules must be fully taken into account.

Companies that integrate this into their CRM strategy at an early stage benefit twice over: They reduce regulatory risks and at the same time create a resilient basis for the successful use of AI. This is precisely where the opportunity for sustainable success in digital competition lies.