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Selection Lab and the EU AI Act: deployer compliance explained

Overview: Selection Lab and the EU AI Act for recruitment assessments

The EU AI Act entered into force on 1 August 2024 and became fully applicable on 2 August 2026. For organizations using AI-powered recruitment assessments, this creates a concrete compliance structure with obligations distributed across two distinct roles. The provider (the company that develops and places the AI system on the market) and the deployer (the organization that uses the AI system in its own context, such as a hiring process). For the wider picture, see the EU AI Act explained for recruitment.

This page exists to clarify precisely how that responsibility split works when you use Selection Lab as your recruitment assessment platform. It maps what Selection Lab supplies as the provider of AI-enabled assessment tools against what your organization, as the deployer, is responsible for managing and demonstrating under applicable EU AI Act obligations.

One important note before proceeding. This page is not legal advice. The compliance scope that applies to any specific deployment depends on your organization's use case, jurisdiction, and the risk classification you assign to your recruitment assessment workflow. Your legal, DPO, and compliance teams should confirm the applicable obligations for your configuration.

What Selection Lab provides as the AI system provider

As the provider of the assessment platform, Selection Lab's obligations cluster around system design, transparency documentation, and the contractual and technical controls that enable deployers to operate the system appropriately. Below is a summary of what Selection Lab delivers.

Privacy controls and data residency

All personal data processed within the platform is stored in Frankfurt, in accordance with GDPR requirements. Selection Lab is fully GDPR compliant and maintains clear data processing agreements with all sub-processors. For each processing purpose, consent is requested from candidates, and defined retention periods are in place. Candidates see their results before being asked again for consent before those results are shared with the hiring organization.

Selection Lab also applies privacy-by-design at the conversation layer. Local large language models are used to remove all personal information from SmartChat conversations before any processing occurs, reducing the risk of unintended personal data exposure.

Instructions for use and transparency documentation (Article 13)

Article 13 of the EU AI Act requires providers of high-risk AI systems to supply deployers with sufficient information to operate the system in compliance with applicable obligations. This includes clear instructions for use, information about the system's purpose and limitations, and guidance on human oversight.

Selection Lab provides documentation covering how the platform works, its intended use in selection workflows, the boundaries of the system's outputs, and how results should be interpreted by hiring teams. This documentation forms the basis of your organization's own transparency flows toward candidates and HR stakeholders.

Processor agreements and contractual controls

A Data Processing Agreement (DPA) is established with every customer as part of onboarding. This agreement documents the categories of personal data processed, the purposes of processing, sub-processor arrangements, data retention and deletion commitments, and security obligations. For organizations subject to EU AI Act obligations, this DPA also supports your ability to demonstrate processor-level accountability.

Platform capabilities and ATS integration

Selection Lab's platform covers the full selection funnel. Pre-screening, role match, interview preparation, and evaluation. The SmartChat module responds within 10 seconds and is accessible via WhatsApp or webchat, with results feeding directly into your ATS workflow. Native ATS integrations are supported, and implementation typically takes 2 to 10 weeks from contract signature to go-live.

After go-live, Selection Lab runs adoption checks every two weeks during the initial phase, followed by quarterly strategic reviews and ongoing support and training. This cadence is designed to help your teams use the system correctly and within the bounds documented in the instructions for use.

Compliance evidence pack: what to request during onboarding

The following documentation categories are available to customers and should be requested during your onboarding process.

  • Data Processing Agreement (DPA) / processor agreement
  • Data residency and security overview (Frankfurt, GDPR controls)
  • Consent and retention statement per processing purpose
  • Instructions for use documentation package
  • Integration documentation for ATS workflows
  • Logging and record-access details (specifics confirmed during implementation)

If you have a DPO, legal team, or external compliance advisor involved in your procurement, request this evidence pack at the start of your implementation engagement.

What deployers remain responsible for

Selection Lab provides the vendor-side building blocks, but deployers carry a defined set of obligations that cannot be delegated to the platform provider. The following sections identify those obligations and their EU AI Act article anchors.

Risk classification and use-case governance

Before deploying any AI system in a recruitment context, your organization must determine the applicable EU AI Act risk category for your specific use case. Recruitment and selection AI systems that make or meaningfully inform decisions about access to employment may qualify as high-risk systems under Annex III of the Act. If high-risk classification applies, a full set of obligations under Chapter III applies to both provider and deployer.

Documenting your risk classification decision, the use-case scope, and the governance structure under which the system operates is your organization's responsibility. Selection Lab can provide supporting documentation to inform this assessment, but the classification itself must be owned and signed off by your team.

Human oversight assignment and operational procedures (Article 14)

Article 14 requires that high-risk AI systems be designed so that natural persons can effectively oversee operation and intervene when necessary. Selection Lab designs its platform with this in mind, but the deployer must implement the human oversight structures in practice.

This means three things.

  • Assigning named oversight roles (for example, a senior HR professional or hiring manager) who are trained to interpret assessment outputs and exercise judgment
  • Establishing procedures for when and how a human reviewer can override or escalate a system-informed recommendation
  • Ensuring that the individuals assigned to oversight have the competence and access needed to intervene effectively during live recruitment cycles

This is an organizational process obligation. It cannot be satisfied by platform features alone.

Transparency toward candidates and HR teams (Article 13)

While Selection Lab provides the instructions for use and the consent flow at the platform level, your organization must operationalize transparency in your own recruitment communications. Candidates must be informed that AI systems are being used in the selection process, what data is collected, how it is used, and what their rights are.

Your HR communications, candidate-facing materials, career site disclosures, and internal HR policy documents all need to reflect the system's use in a way that satisfies the transparency expectations under Article 13 and any relevant national implementation measures.

Logging and retention under your control (Articles 19 and 26)

Article 19 of the EU AI Act establishes logging requirements for high-risk AI systems. Article 26 requires deployers to keep automatically generated logs to the extent those logs are under their control, and to retain them for a minimum of six months.

Selection Lab provides logging and record-keeping capabilities within the platform. The specifics of log access, export format, and retention configuration are confirmed during implementation. However, your organization must establish the operational procedures to do the following.

  • Retrieve and retain logs for the required period
  • Store those logs in a location under your control
  • Maintain monitoring and incident-response procedures tied to what the logs capture

Do not assume that logs held within the platform automatically satisfy this requirement. Your compliance team should confirm that your log retention procedures meet the Article 26 obligations for your specific deployment configuration.

Final decision-making governance

The hiring decision remains entirely with your organization. Selection Lab's platform produces assessment outputs and recommendations that inform your recruitment process, but the system does not make hiring decisions autonomously. Your organization must document the following.

  • The decision policy that governs how assessment outputs are used by hiring managers
  • The conditions under which a recommendation can be overridden
  • The governance structure for reviewing system outputs over time and detecting any drift or adverse impact

This documentation is essential for audit readiness and for demonstrating that human judgment remains accountable in the final selection outcome.

How Selection Lab supports your compliance workflow

The compliance obligations described above require organizational action, but Selection Lab structures its implementation and support model to help you get there efficiently.

Compliance enablement checklist for deployers

Use the following checklist as a starting point when operationalizing your EU AI Act obligations for recruitment assessments.

  1. Risk classification. Confirm with your legal/DPO team whether your recruitment assessment use case qualifies as high-risk under EU AI Act Annex III
  2. Oversight roles. Assign named human oversight owners with defined responsibilities and escalation procedures
  3. Decision policy. Document how assessment outputs are used in hiring decisions and under what conditions outputs can be overridden
  4. System configuration. Configure the platform strictly within the intended use described in Selection Lab's instructions for use documentation
  5. Candidate transparency. Update candidate-facing communications to reflect AI system use, data collection, and candidate rights
  6. Log retention. Establish procedures to retrieve, retain, and store automatically generated logs for at least six months under your control
  7. Monitoring and governance. Schedule periodic reviews (aligned with Selection Lab's quarterly strategic review cadence where possible) to assess system performance, bias risk, and compliance posture
  8. Evidence file. Maintain a compliance evidence file that includes the DPA, instructions for use, risk classification decision, oversight assignment, and log retention records

Documentation Selection Lab makes available

During implementation, the following documentation categories can be provided to support your internal compliance file.

  • Processor agreement / DPA
  • Data residency and security overview
  • Consent and retention framework documentation
  • Instructions for use package (covering system purpose, output interpretation, and oversight guidance)
  • ATS integration documentation
  • Logging and record-access details (confirmed at implementation stage)

Where Selection Lab's documentation does not cover a specific technical detail you need for your compliance file, such as log export format or tamper-evidence controls, raise those questions during your implementation kickoff. The technical and customer success teams can confirm specifics or escalate to the appropriate internal owner.

Request a compliance walkthrough

If you need a structured walkthrough of vendor and deployer responsibilities for your specific recruitment assessment configuration, Selection Lab offers a dedicated compliance engagement. This is particularly relevant for organizations with a DPO, legal team, or external compliance advisor involved in their EU AI Act readiness program.

To prepare for a compliance walkthrough, it helps to have the following information available.

  • A description of your recruitment assessment workflow (which roles, which stages, which assessment types)
  • Your target jurisdictions (EU Member States where candidates or hiring decisions are located)
  • Where in your pipeline the AI system outputs are used (ATS scoring, shortlisting, interview invitations, or other decision points)
  • Who in your organization will act as the human oversight owner
  • Whether you have completed an initial risk classification assessment

Based on this information, Selection Lab can deliver a responsibility matrix tailored to your configuration and a compliance evidence pack covering the vendor-side documentation described above.

Contact the Selection Lab team to schedule your compliance walkthrough or to request the documentation package for your onboarding.

Frequently asked questions

Is Selection Lab the provider or the deployer under the EU AI Act?

Selection Lab is the provider, the party that develops the assessment platform and places it on the market. Your organization is the deployer, the party that uses the system in its own hiring process. Each role carries its own obligations and neither can take over the other's.

Are recruitment assessments high-risk under the EU AI Act?

They can be. AI systems that make or meaningfully inform decisions about access to employment fall under Annex III. Whether your specific use case qualifies depends on how the outputs are used, and that classification is the deployer's responsibility to make, document and sign off, with input from legal and the DPO.

What does a deployer have to do under Article 26 of the EU AI Act?

Use the system according to the provider's instructions for use, assign competent human oversight, inform candidates that AI is used, and keep the automatically generated logs that are under your control for at least six months. Selection Lab supplies the documentation and logging capabilities; the procedures around them are yours.

Does Selection Lab make the hiring decision?

No. The platform produces assessment outputs and recommendations. The decision stays with your organization, and you need a documented decision policy that states how outputs are used, when a recommendation can be overridden and how outputs are reviewed over time.

Which documents can I request from Selection Lab for my compliance file?

The data processing agreement, a data residency and security overview, the consent and retention statement per processing purpose, the instructions for use package, ATS integration documentation, and logging and record-access details. Request them at the start of implementation, especially if a DPO or legal team is involved.

FAQ

Can game-based assessments promote diversity in the hiring process?

Yes, game-based assessments can support diversity by focusing on skills and behaviors rather than traditional criteria like résumés, which may contain unconscious biases. This gives candidates from diverse backgrounds a fairer chance to demonstrate their potential.

What is a game-based assessment?

A game-based assessment is a method that uses game mechanics to evaluate a candidate’s skills, competencies, and personality traits. While playing these games, candidates are assessed on aspects like problem-solving, cognitive ability, and behavior under pressure in an interactive way.

What are the advantages of game-based assessments?

Game-based assessments offer a more engaging and interactive experience for candidates, which can lead to a more positive perception of the hiring process—especially among certain groups. For employers, they provide deeper insights into both cognitive and behavioral traits, which traditional tests may miss. They also reduce the chance of socially desirable answers, as candidates tend to respond more authentically in a game environment.

How reliable are game-based assessments compared to traditional tests?

When well-designed, game-based assessments can be just as reliable—or even more reliable—than traditional tests. They assess a wide range of behaviors and cognitive abilities in a dynamic setting. However, the quality of these assessments varies greatly, so careful evaluation is essential.

How does a game-based assessment work?

Candidates participate in interactive games designed to measure specific skills and behaviors. Evaluation goes beyond just the final score—it also considers how the candidate makes decisions, handles challenges, and responds to different scenarios. These insights reveal underlying thought processes and behavioral patterns.

Are game-based assessments scientifically validated?

The main drawback is that many game-based assessments are relatively new and have not yet been extensively researched by independent academics. Providers often cite their own research, which is rarely externally validated. Without independent studies, the reliability of these assessments remains uncertain—something to keep in mind when selecting one.

How can game based assessments contribute to a better candidate experience

This can vary significantly by audience. The playful, interactive nature of game-based assessments can lower stress levels for some candidates compared to traditional tests. However, research shows that certain groups, especially those over 35, may find them more stressful. Men also tend to rate the experience more positively than women.

Can you practice game-based assessment?

You can familiarize yourself with the style of games used, but it’s difficult to "practice" for them in a traditional sense. These assessments are designed to measure natural reactions and authentic behavior, so repeated practice typically has less effect on performance than with traditional tests.

Will game-based assessments replace traditional tests in the future?

It’s likely that game-based assessments will become more common in hiring processes, but they probably won’t fully replace traditional tests. Both approaches have value and can complement each other depending on the role and the company’s needs.

How are the results of a game-based assessment analyzed?

Results are analyzed based on predefined criteria such as problem-solving ability, reaction time, and behavior under pressure. Advanced algorithms collect and interpret this data to provide a reliable, objective evaluation of a candidate’s strengths.

What kind of skills do game-based assessments measure?

They assess a wide range of abilities, including problem-solving, adaptability, decision-making under pressure, teamwork, and emotional intelligence. Depending on the design, they may also evaluate cognitive skills like memory, attention, and pattern recognition.

How long does a game-based assessment take?

Typically, these assessments last between 15 and 60 minutes, depending on the game’s complexity and the number of skills being tested. They’re usually shorter and more engaging than traditional assessments, making for a smoother candidate experience.

Are game-based assessments suitable for all roles?

They are especially effective for roles that require flexibility, creativity, problem-solving, and strong interpersonal skills. For highly technical or specialized roles, additional assessments may be needed to measure specific knowledge.

What’s the difference between a game-based and a gamified assessment?

A gamified assessment adds game-like elements (such as points or rewards) to a traditional test to increase engagement. A game-based assessment, on the other hand, is a standalone game designed specifically to evaluate certain competencies. The game itself is the primary evaluation tool, not just an enhancement.

FAQ

How can I improve my company’s retention rate?

The retention rate can be improved by investing in employee development and satisfaction. This includes offering training, career opportunities, and recognition for their contributions. A culture of open communication and attention to work-life balance can also contribute to higher retention. Additionally, offering competitive compensation and involving employees in decision-making can strengthen loyalty.

What are the benefits of growth opportunities for employee retention?

Growth opportunities can promote employee retention by giving staff a sense of direction and motivation. When they have the chance to learn and develop professionally within the company, they feel valued, which increases their loyalty. This can prevent them from leaving to seek better opportunities elsewhere. kunnen het behoud van personeel bevorderen door medewerkers een gevoel van richting en motivatie te geven. Wanneer zij de kans krijgen om te leren en zich professioneel te ontwikkelen binnen het bedrijf, voelen zij zich gewaardeerd, wat hun loyaliteit vergroot. Dit kan voorkomen dat ze vertrekken om elders betere kansen te zoeken.

What are the key factors that influence employee retention?

Key factors that influence employee retention include salary and benefits, opportunities for professional development, work-life balance, company culture, and the relationship with supervisors. Employees tend to stay longer when they feel valued, challenged, and supported in their work environment.

Why is employee retention so important for organizations?

Employee retention is important because it helps reduce recruitment and training costs for new employees, and it contributes to retaining knowledge and experience within the organization. High retention also ensures continuity within teams, leading to a more stable company culture, higher customer satisfaction, and improved business outcomes.

Which recruitment strategies help improve retention?

Recruitment strategies that can improve retention include identifying candidates who align with the company culture, using assessments to evaluate soft skills, and providing transparency about role expectations during the hiring process. Employees who feel connected to the organization and have clarity about their role are more likely to stay longer.

How can a good onboarding process contribute to higher retention?

An effective onboarding process can contribute to higher retention by helping new employees quickly adapt to their role, the company culture, and expectations. By providing support and clear information from the start, their engagement is increased, and the likelihood of them leaving early due to feelings of being overwhelmed or lacking guidance is reduced.

What is the role of company culture in retaining employees?

Company culture plays a crucial role in employee retention. When employees feel heard, valued, and connected to the values and norms of the company, they are more likely to stay. A positive culture that fosters collaboration, respect, and personal growth can significantly enhance employee motivation and satisfaction.

How can leadership and management style influence retention?

Leadership and management style have a significant impact on retention. Leaders who inspire, support, and coach their team can increase employee engagement and satisfaction. Offering autonomy and trust can lead to higher loyalty, while inefficient or negative management styles can contribute to dissatisfaction and increased employee turnover.

What is the importance of recognition and rewards for employee retention?

Recognition and rewards play an important role in employee retention by showing staff that their work is valued. This can increase their motivation and loyalty. In addition to financial rewards, compliments, promotions, and other forms of recognition can also contribute to satisfaction and retaining employees.

What role does work-life balance play in improving retention?

A balanced work-life balance plays an important role in increasing retention. By reducing stress and improving job satisfaction, employees are more likely to stay with the company. Initiatives such as flexible working hours, remote work options, and respect for personal time can contribute to this balance.

What does increasing retention mean within a company?

Increasing retention within a company means implementing strategies to keep employees with the organization for longer. This can be achieved by improving job satisfaction, offering growth opportunities, and fostering a positive and supportive company culture.

How do I measure the success of my retention strategy?

The success of a retention strategy can be measured by tracking retention rates and turnover rates, and by gaining insights from exit interviews. Additionally, employee satisfaction surveys and feedback from performance evaluations can provide valuable information about the effectiveness of the strategies applied.

What are the costs of a low retention rate?

A low retention rate can bring significant costs, such as increased expenses for recruiting and training new employees. Furthermore, the loss of experienced staff can lead to lower productivity, reduced knowledge transfer, and a negative impact on company culture.

How can I increase employee engagement?

To increase employee engagement, involve them in decision-making processes, regularly ask for their feedback, and recognize their contributions. Offering development opportunities and maintaining transparent communication can also contribute to greater engagement.

How can technology help improve employee retention?

Technology can be a tool for improving employee retention by facilitating communication, feedback, and development. By using online platforms for training, recognition, and evaluation, companies can create a more engaged and satisfied workforce.

FAQ

How long does it take to complete the tool?

Less than 10 minutes. You’ll answer 30 guided questions and get a summary of what to look for in your next assessment platform.

Can this checklist help me compare assessment providers?

Yes. By clarifying what matters most to your team, it makes comparing providers' features, pricing, and strengths much easier and more strategic.

How can I use this checklist if I’m not doing a formal RFI?

It’s equally valuable for internal evaluations, exploring new tools, or improving your current hiring process even if you’re not issuing an RFI or RFQ.

What should I look for in a modern assessment tool?

Prioritize platforms with user-friendly design, mobile compatibility, strong analytics, ATS integrations, and inclusive features like neurodiversity support.

What types of assessments should I consider in 2025?

Leading tools combine cognitive testing, situational judgment tests (SJTs), behavior assessments, and predictive AI to evaluate candidates more holistically.

Who should use an assessment checklist?

HR professionals, hiring managers, and procurement teams evaluating pre-selection solutions, especially those comparing AI-powered or compliance-driven assessment platforms.

How does this checklist help with RFIs and RFQs for assessments?

The checklist helps you define your exact requirements so you can confidently draft or respond to Requests for Information (RFI) or Requests for Quotation (RFQ) for assessment tools.

What is an assessment tool in hiring?

An assessment tool evaluates candidates’ skills, behaviors, and fit during the recruitment process. It helps improve hiring decisions and streamline pre-selection.

Game-based assessment packs

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Selection Lab and the EU AI Act: deployer compliance explained

Learn how Selection Lab supports deployers with vendor-side compliance building blocks and what EU AI Act obligations your organization must manage for recruitment assessments.
Joeri Everaers
COO
Read time: Approx

Overview: Selection Lab and the EU AI Act for recruitment assessments

The EU AI Act entered into force on 1 August 2024 and became fully applicable on 2 August 2026. For organizations using AI-powered recruitment assessments, this creates a concrete compliance structure with obligations distributed across two distinct roles. The provider (the company that develops and places the AI system on the market) and the deployer (the organization that uses the AI system in its own context, such as a hiring process). For the wider picture, see the EU AI Act explained for recruitment.

This page exists to clarify precisely how that responsibility split works when you use Selection Lab as your recruitment assessment platform. It maps what Selection Lab supplies as the provider of AI-enabled assessment tools against what your organization, as the deployer, is responsible for managing and demonstrating under applicable EU AI Act obligations.

One important note before proceeding. This page is not legal advice. The compliance scope that applies to any specific deployment depends on your organization's use case, jurisdiction, and the risk classification you assign to your recruitment assessment workflow. Your legal, DPO, and compliance teams should confirm the applicable obligations for your configuration.

What Selection Lab provides as the AI system provider

As the provider of the assessment platform, Selection Lab's obligations cluster around system design, transparency documentation, and the contractual and technical controls that enable deployers to operate the system appropriately. Below is a summary of what Selection Lab delivers.

Privacy controls and data residency

All personal data processed within the platform is stored in Frankfurt, in accordance with GDPR requirements. Selection Lab is fully GDPR compliant and maintains clear data processing agreements with all sub-processors. For each processing purpose, consent is requested from candidates, and defined retention periods are in place. Candidates see their results before being asked again for consent before those results are shared with the hiring organization.

Selection Lab also applies privacy-by-design at the conversation layer. Local large language models are used to remove all personal information from SmartChat conversations before any processing occurs, reducing the risk of unintended personal data exposure.

Instructions for use and transparency documentation (Article 13)

Article 13 of the EU AI Act requires providers of high-risk AI systems to supply deployers with sufficient information to operate the system in compliance with applicable obligations. This includes clear instructions for use, information about the system's purpose and limitations, and guidance on human oversight.

Selection Lab provides documentation covering how the platform works, its intended use in selection workflows, the boundaries of the system's outputs, and how results should be interpreted by hiring teams. This documentation forms the basis of your organization's own transparency flows toward candidates and HR stakeholders.

Processor agreements and contractual controls

A Data Processing Agreement (DPA) is established with every customer as part of onboarding. This agreement documents the categories of personal data processed, the purposes of processing, sub-processor arrangements, data retention and deletion commitments, and security obligations. For organizations subject to EU AI Act obligations, this DPA also supports your ability to demonstrate processor-level accountability.

Platform capabilities and ATS integration

Selection Lab's platform covers the full selection funnel. Pre-screening, role match, interview preparation, and evaluation. The SmartChat module responds within 10 seconds and is accessible via WhatsApp or webchat, with results feeding directly into your ATS workflow. Native ATS integrations are supported, and implementation typically takes 2 to 10 weeks from contract signature to go-live.

After go-live, Selection Lab runs adoption checks every two weeks during the initial phase, followed by quarterly strategic reviews and ongoing support and training. This cadence is designed to help your teams use the system correctly and within the bounds documented in the instructions for use.

Compliance evidence pack: what to request during onboarding

The following documentation categories are available to customers and should be requested during your onboarding process.

  • Data Processing Agreement (DPA) / processor agreement
  • Data residency and security overview (Frankfurt, GDPR controls)
  • Consent and retention statement per processing purpose
  • Instructions for use documentation package
  • Integration documentation for ATS workflows
  • Logging and record-access details (specifics confirmed during implementation)

If you have a DPO, legal team, or external compliance advisor involved in your procurement, request this evidence pack at the start of your implementation engagement.

What deployers remain responsible for

Selection Lab provides the vendor-side building blocks, but deployers carry a defined set of obligations that cannot be delegated to the platform provider. The following sections identify those obligations and their EU AI Act article anchors.

Risk classification and use-case governance

Before deploying any AI system in a recruitment context, your organization must determine the applicable EU AI Act risk category for your specific use case. Recruitment and selection AI systems that make or meaningfully inform decisions about access to employment may qualify as high-risk systems under Annex III of the Act. If high-risk classification applies, a full set of obligations under Chapter III applies to both provider and deployer.

Documenting your risk classification decision, the use-case scope, and the governance structure under which the system operates is your organization's responsibility. Selection Lab can provide supporting documentation to inform this assessment, but the classification itself must be owned and signed off by your team.

Human oversight assignment and operational procedures (Article 14)

Article 14 requires that high-risk AI systems be designed so that natural persons can effectively oversee operation and intervene when necessary. Selection Lab designs its platform with this in mind, but the deployer must implement the human oversight structures in practice.

This means three things.

  • Assigning named oversight roles (for example, a senior HR professional or hiring manager) who are trained to interpret assessment outputs and exercise judgment
  • Establishing procedures for when and how a human reviewer can override or escalate a system-informed recommendation
  • Ensuring that the individuals assigned to oversight have the competence and access needed to intervene effectively during live recruitment cycles

This is an organizational process obligation. It cannot be satisfied by platform features alone.

Transparency toward candidates and HR teams (Article 13)

While Selection Lab provides the instructions for use and the consent flow at the platform level, your organization must operationalize transparency in your own recruitment communications. Candidates must be informed that AI systems are being used in the selection process, what data is collected, how it is used, and what their rights are.

Your HR communications, candidate-facing materials, career site disclosures, and internal HR policy documents all need to reflect the system's use in a way that satisfies the transparency expectations under Article 13 and any relevant national implementation measures.

Logging and retention under your control (Articles 19 and 26)

Article 19 of the EU AI Act establishes logging requirements for high-risk AI systems. Article 26 requires deployers to keep automatically generated logs to the extent those logs are under their control, and to retain them for a minimum of six months.

Selection Lab provides logging and record-keeping capabilities within the platform. The specifics of log access, export format, and retention configuration are confirmed during implementation. However, your organization must establish the operational procedures to do the following.

  • Retrieve and retain logs for the required period
  • Store those logs in a location under your control
  • Maintain monitoring and incident-response procedures tied to what the logs capture

Do not assume that logs held within the platform automatically satisfy this requirement. Your compliance team should confirm that your log retention procedures meet the Article 26 obligations for your specific deployment configuration.

Final decision-making governance

The hiring decision remains entirely with your organization. Selection Lab's platform produces assessment outputs and recommendations that inform your recruitment process, but the system does not make hiring decisions autonomously. Your organization must document the following.

  • The decision policy that governs how assessment outputs are used by hiring managers
  • The conditions under which a recommendation can be overridden
  • The governance structure for reviewing system outputs over time and detecting any drift or adverse impact

This documentation is essential for audit readiness and for demonstrating that human judgment remains accountable in the final selection outcome.

How Selection Lab supports your compliance workflow

The compliance obligations described above require organizational action, but Selection Lab structures its implementation and support model to help you get there efficiently.

Compliance enablement checklist for deployers

Use the following checklist as a starting point when operationalizing your EU AI Act obligations for recruitment assessments.

  1. Risk classification. Confirm with your legal/DPO team whether your recruitment assessment use case qualifies as high-risk under EU AI Act Annex III
  2. Oversight roles. Assign named human oversight owners with defined responsibilities and escalation procedures
  3. Decision policy. Document how assessment outputs are used in hiring decisions and under what conditions outputs can be overridden
  4. System configuration. Configure the platform strictly within the intended use described in Selection Lab's instructions for use documentation
  5. Candidate transparency. Update candidate-facing communications to reflect AI system use, data collection, and candidate rights
  6. Log retention. Establish procedures to retrieve, retain, and store automatically generated logs for at least six months under your control
  7. Monitoring and governance. Schedule periodic reviews (aligned with Selection Lab's quarterly strategic review cadence where possible) to assess system performance, bias risk, and compliance posture
  8. Evidence file. Maintain a compliance evidence file that includes the DPA, instructions for use, risk classification decision, oversight assignment, and log retention records

Documentation Selection Lab makes available

During implementation, the following documentation categories can be provided to support your internal compliance file.

  • Processor agreement / DPA
  • Data residency and security overview
  • Consent and retention framework documentation
  • Instructions for use package (covering system purpose, output interpretation, and oversight guidance)
  • ATS integration documentation
  • Logging and record-access details (confirmed at implementation stage)

Where Selection Lab's documentation does not cover a specific technical detail you need for your compliance file, such as log export format or tamper-evidence controls, raise those questions during your implementation kickoff. The technical and customer success teams can confirm specifics or escalate to the appropriate internal owner.

Request a compliance walkthrough

If you need a structured walkthrough of vendor and deployer responsibilities for your specific recruitment assessment configuration, Selection Lab offers a dedicated compliance engagement. This is particularly relevant for organizations with a DPO, legal team, or external compliance advisor involved in their EU AI Act readiness program.

To prepare for a compliance walkthrough, it helps to have the following information available.

  • A description of your recruitment assessment workflow (which roles, which stages, which assessment types)
  • Your target jurisdictions (EU Member States where candidates or hiring decisions are located)
  • Where in your pipeline the AI system outputs are used (ATS scoring, shortlisting, interview invitations, or other decision points)
  • Who in your organization will act as the human oversight owner
  • Whether you have completed an initial risk classification assessment

Based on this information, Selection Lab can deliver a responsibility matrix tailored to your configuration and a compliance evidence pack covering the vendor-side documentation described above.

Contact the Selection Lab team to schedule your compliance walkthrough or to request the documentation package for your onboarding.

Frequently asked questions

Is Selection Lab the provider or the deployer under the EU AI Act?

Selection Lab is the provider, the party that develops the assessment platform and places it on the market. Your organization is the deployer, the party that uses the system in its own hiring process. Each role carries its own obligations and neither can take over the other's.

Are recruitment assessments high-risk under the EU AI Act?

They can be. AI systems that make or meaningfully inform decisions about access to employment fall under Annex III. Whether your specific use case qualifies depends on how the outputs are used, and that classification is the deployer's responsibility to make, document and sign off, with input from legal and the DPO.

What does a deployer have to do under Article 26 of the EU AI Act?

Use the system according to the provider's instructions for use, assign competent human oversight, inform candidates that AI is used, and keep the automatically generated logs that are under your control for at least six months. Selection Lab supplies the documentation and logging capabilities; the procedures around them are yours.

Does Selection Lab make the hiring decision?

No. The platform produces assessment outputs and recommendations. The decision stays with your organization, and you need a documented decision policy that states how outputs are used, when a recommendation can be overridden and how outputs are reviewed over time.

Which documents can I request from Selection Lab for my compliance file?

The data processing agreement, a data residency and security overview, the consent and retention statement per processing purpose, the instructions for use package, ATS integration documentation, and logging and record-access details. Request them at the start of implementation, especially if a DPO or legal team is involved.