Employment

AI systems intended to be used as an automated job matching and ranking tool

designed to assist internal and external recruiters in the recruitment and selection processes by analyzing and filtering candidates should be classified as high-risk. Such a system processes structured and unstructured data (e.g., CVs, skills, education, past placements, cognitive, social and emotional competencies) and compares it to job descriptions or historical hiring data to generate quantitative scores, rankings (e.g., ‘top 5 candidates’), and/or qualitative fit categories (e.g., ‘high fit,’ ‘low fit’). These outputs are used to shortlist candidates for internal and external recruiters, who retain discretion to review, override, or supplement algorithmic recommendations. However, the system’s rankings and scores serve as a primary input for decision-making. For example, it could lead to low ranking or exclusion of candidates of a certain gender or of candidates with disabilities. It therefore falls to be classified as high-risk pursuant to point 4(a) of Annex III.

AI system intended to be used for candidate or contractor sourcing across online platforms

A recruitment agency deploys an AI-enabled tool to search social media, professional sites or job boards, and its own CV databases. Recruiters input pre-defined criteria such as years of experience, technical skills, or educational background. The system processes unstructured and structured data, identifies matching profiles, and generates a shortlist of potential candidates or contractors who are natural persons.

This system falls within the use case of point 4(a) of Annex III, since it directly and meaningfully affects the recruitment and selection of natural persons by filtering and identifying candidates. None of the exceptions in Article 6(3) apply considering the tasks carried out by the AI system and its material influence on the outcome of decision-making.

AI system ranking self-employed service providers

An online platform designed to help consumers in finding a self-employed service provider to assist them with various tasks uses an AI-enabled job-matching tool that ranks service providers and determines which are presented to potential consumers.

This system falls within the use case of point 4(a) of Annex III since it directly and meaningfully affects selection of natural persons by filtering and ranking potential service providers. Because its output shapes access to future assignments and may have a decisive impact on the careers of self-employed persons, along with their livelihoods and rights, none of the exceptions in Article 6(3) apply.

AI-based vision monitoring system intended to be used for pilot recruitment

An AI-enabled system is intended to be used to assess the visual capacities of pilot candidates. Using cameras and sensors the system monitors relevant metrics (e.g., visual acuity and reaction speed) then evaluates whether candidates meet the thresholds required for passenger flights. These results directly determine candidates’ eligibility for certain roles. This system falls within the use case of point 4(a) of Annex III, since it is used in recruitment and selection to evaluate candidates’ suitability (i.e., in this case whether they are eligible to fly long-haul or short-haul flights). None of the derogations in Article 6(3) apply considering the nature of the tasks being carried out by the AI system and its material influence on the outcome of the decision-making. 

AI system intended to be used for scoring applicant answers in a recruitment process

An AI system is intended to be used to evaluate written or oral responses given by job applicants during an online assessment. The system assigns each applicant a numerical score based on linguistic and substantive criteria, then generates a ranking used to determine who is invited to the interview stage. This system falls within the use case of point 4(a) of Annex III, since it is used in recruitment and selection. The AI performs core evaluative functions and meaningfully impacts the substance of the recruitment and selection. None of the exceptions in Article 6(3) AI Act apply, in particular, considering the fact that the AI system will materially influence the decision-making.

AI system intended to be used to support apprenticeship recruitment at a commercial firm

A firm uses an AI system to support the recruitment of apprentices. The system is applied to manage and process applications for apprenticeship positions, potentially by screening CVs, matching applicants to roles, or generating shortlists based on pre-defined criteria such as qualifications or age. Although apprenticeships include training elements, the AI is used within the context of hiring for a formal employment relationship and therefore falls within the use case of point 4(a) of Annex III. None of the exceptions in Article 6(3) AI Act apply considering the nature of the tasks being carried out by the AI system.

AI system intended to be used to place targeted job advertisements to specific users on social media

The system collects and analyses a wide range of data navigation patterns and user characteristics. Advertisers provide targeting criteria, such as age, educational and professional background, or sector, and the system identifies and prioritises potential audiences. The system goes beyond merely matching requirements such as whether the candidate possesses certain professional accreditations or their geographical location. Since the system determines access to employment opportunities through targeted advertising, it falls within the use case of point 4(a) of Annex. Since the system’s functioning can materially affect which candidates are able to learn about job vacancies, thereby influencing their ability to pursue employment, it cannot benefit from the exceptions in Article 6(3) AI Act.

AI system intended to be used by employment agencies to assign candidates to vacancies      

The system processes candidate data such as information in CVs, including skills, education history, and prior work experience. On the employer side, the system incorporates job requirements, occupational classifications, and labour market data. The system then generates recommendations by ranking candidates for specific vacancies or by suggesting suitable job postings to jobseekers. These outputs are used by caseworkers in the agency, who may rely heavily on the system to manage large volumes of applications. Since the system evaluates candidates in the context of recruitment and access to employment opportunities, it falls within the use case of point 4(a) of Annex III. Since the system’s recommendations have a direct bearing on which candidates are referred to employers and which vacancies are presented to jobseekers, it cannot benefit from the exceptions in Article 6(3) AI Act.

AI system intended to be used to perform background checks on job applicants during recruitment

The system aggregates and analyses multiple types of data. Standard inputs include official records, such as education and professional certifications, employment history, social network history, and credit or financial data, where legally permissible. The system also incorporates open-source and online information. Employers or recruiters receive outputs in the form of composite risk scores, categories such as ‘low,” ‘medium,” or ‘high risk,” or specific alerts highlighting potential issues (e.g., unexplained employment gaps, flagged financial liabilities, or controversial online activity). 

These outputs can be used as filters in high-volume hiring, where candidates flagged as ‘high risk” may be deprioritized or excluded before a caseworker reviews their file. While human review is formally part of the process, in practice the system’s output heavily influences which candidates advance in the recruitment process, hence materially influencing the outcome of the recruitment process. Since the system materially influences career prospects and is used in the scope of recruitment, it falls within the use case of point 4(a) of Annex III. Since the system performs profiling, it cannot benefit from the exceptions in Article 6(3) AI Act. 

AI system intended to be used exclusively to identify non-inclusive or discriminatory wording in ad descriptions

The system’s identification logic is based on patterns and terms defined and reviewed by human experts, and the system flags potentially problematic phrases. At first glance, the system operates within the broad employment domain, but the job ad screening tool is not intended to be used for the recruitment or selection of natural persons and therefore falls outside the use case of point 4(a) of Annex III.

AI system intended to be used for employer brand advertisements to present the company as an attractive place to work

The advertisements highlight aspects, such as workplace culture, employee benefits, or career development opportunities, but are not tied to any specific job opening and are non-discriminatory. The system may optimise the placement of ads to reach broader or more suitable audiences, using metrics, such as website traffic, engagement rates, or general demographics. However, the system is limited to employer branding advertisements and does not concern specific job vacancies, and therefore falls outside the use case of point 4(a) of Annex III.

AI system intended to be used for employer reputation monitoring

A company uses an AI system to scan online platforms and social media for comments or reviews mentioning the employer, with the purpose of tracking the organisation’s reputation as a workplace and identifying general trends in how the company is perceived by potential applicants. No analysis or tracking of specific comments or specific users (which are anonymized at collection) are undertaken.Although the AI system is linked to recruitment more broadly, since employer reputation may affect how attractive the company appears to jobseekers, it is not intended to be used for the direct recruitment or selection of natural persons and therefore falls outside the use case of point 4(a) of Annex III.

AI system intended to be used for employee onboarding support

The system provides personalized information about company policies, training schedules, and answers common questions during their onboarding process. Since the system supports internal HR operations after hiring and does not influence the recruitment or selection of natural persons or affect in any manner their access to work, the system does not fall within the use case of point 4(a) of Annex III. The system may fall within the use case of point 4(b) of Annex III, if it affects the terms of the work-related relationship or feeds into performance evaluations or monitors workers.

AI system intended to be used for assisting candidates in tailoring their CV to specific open positions

The AI system analyses the candidate’s CV along with the description of the open position provided by the candidate. Based on these elements, the AI tool recommends changes to the CV of the candidate with the aim of increasing the likelihood of selection for an interview. These recommendations are exclusively shared with the candidate. While the AI system may indirectly impact the success of the candidate in obtaining the desired position, its use is initiated and managed by the candidate, outside of the potential employer’s control and occurs outside of the recruitment and selection process. It therefore falls outside the use case of point 4(a) of Annex III.

AI system intended to be used for assisting candidates in finding the best available position 

The system is used by candidates to analyse both job vacancies and information provided by the candidate covering their skills, experience, and professional expectations. Based on these elements, the system ranks job vacancies and recommends the most suitable positions for the candidate. These recommendations are exclusively shared with the candidate. While the AI system may indirectly impact the success of the candidate in obtaining the desired position, its use is initiated and managed by the candidate, outside of the potential employer’s control and occurs outside of the recruitment and selection process. It therefore falls outside the use case of point 4(a) of Annex III.

AI system intended to be used for scheduling interviews

The system is used to automate the coordination of interview appointments with job applicants. The system operates by integrating with the company’s calendar tools and the availability preferences provided by each candidate. It proposes interview time slots based on mutual availability and logistical constraints, such as time zone differences or maximum daily meetings per recruiter. It also sends reminders to recruiters and candidates a few days before the interview reminding them of the date, time and location of the interview. The system includes a function allowing candidates to indicate specific accessibility needs, such as requests for sign language interpretation, extended interview duration, or alternative formats for communication. These preferences are then automatically incorporated into the scheduling process to ensure the appropriate arrangements are made. While the scheduling system operates in the recruitment context, it does not perform any function that contributes to the selection of candidates. Since  the system’s purpose is purely logistical and it does not initiate nor influence employment-related assessments, it falls within the exception  for narrow procedural tasks listed in in Article 6(3)(a) AI Act. 

AI system intended to be used to check human patterns in hiring

The AI system is used to audit past hiring decisions by analysing anonymized recruitment data, including CV scores, interview notes, and hiring outcomes. The system employs statistical modelling to detect potential biases or inconsistencies. It does not participate in ongoing recruitment or influence current candidate evaluations, nor does it assess or make decisions based on identified or identifiable recruiters’ or applicants’ personal characteristics. Its role is purely retrospective based on anonymized information and for already completed human assessments. Although it falls within the use case of point 4(a) of Annex III, the system benefits from the exception listed in Article 6(3)(c) AI Act for AI systems intended to detect decision-making patterns or deviations from prior decision-making patterns without replacing or influencing previously completed human assessments.

A retail/logistics company deploys an AI-enabled scheduler to assign shifts, rest periods and on-call windows

Inputs provided to the AI system include, among others, behavioural/performance signals (punctuality, non-show history, acceptance/decline rates for offered shifts, customer/manager ratings). The optimiser ranks workers for each slot and auto-allocates shifts, allocating the highest performing workers to the most important shifts. Workers ranked lower receive less important and possibly fewer shifts, lower variable pay, and less predictable patterns. The optimiser also downgrades priority if a worker declines ‘priority offers”.

The AI system will evaluate the performance and behaviour of workers and assign tasks based on this evaluation and, as such, falls within the scope of point 4(b) of Annex III. Use of this AI system will affect workers’ remuneration, their access to priority tasks and possibly progression. As such, the system cannot benefit from the exceptions in Article 6(3) AI Act.

An online tutoring platform deploys an AI system to manage self-employed teacher accounts 

Inputs include student satisfaction ratings, lesson completion rates, and punctuality logs from the videoconferencing system. The system aggregates these into a ‘tutor performance score.” If the score falls below 4/5 for three consecutive weeks, the system automatically suspends the tutor’s account for a month. If low ratings persist for another review period, the account is permanently deactivated. The practical effect is that tutors can no longer accept lessons, which ends their work relationship with the platform. The system’s effect is the functional termination of the work relationship. The term ‘termination’ used in point 4(b) of Annex III is to be understood in substantive terms, covering any decision that deprives workers of continued engagement.

AI system for workload allocation among associates in a law firm

The system ingests data on billing hours, turnaround times on prior assignments, responsiveness to emails, and voluntary participation in firm activities (e.g. training, client development). These behavioural inputs are aggregated into a score, which serves as a basis for the allocation of client matters. Since the system allocates tasks based on the individual behaviour of associates, materially affecting both present work conditions and long-term career trajectories, it falls within the use case of point 4(b) of Annex III. 

AI system for pricing and pay determination in platform work

A ride-hailing platform deploys an AI system to dynamically set driver compensation. Inputs include real-time demand, driver acceptance rates, passenger ratings, and average completion times. The system calculates per-ride fares and adjusts individual drivers’ pay multipliers. For example, drivers with consistently lower passenger ratings or slower completion times receive a reduced pay coefficient, while highly rated drivers earn bonuses. These adjustments are made automatically and applied in real time, directly affecting income. Human oversight exists formally, but in practice pay levels are determined exclusively by the algorithm and appeals rarely alter outcomes.Since remuneration decisions fall within the terms of a work-related relationship, the system falls within the use case of point 4(b) of Annex III.

AI system intended to be used for assignment of civil servants to posts

A public administration uses an AI system to allocate successful candidates (e.g. teachers or doctors) to specific posts after they have passed a competition exam. The system takes into account test scores, geographical preferences, availability of vacancies, and seniority. It generates final assignment lists that determine which candidate goes to which post. Appeals are possible, but in practice the AI system’s allocation output is decisive, as administrative services rely on the system to finalise placements. Since the system is used for the allocation of roles in the public sector, directly and meaningfully determining working conditions and career paths of civil servants, it falls within the use case of point 4(b) of Annex III.

AI system for tracking delivery operations

A courier and shipping company uses an AI system to track shipping data and detect potential mistakes in labelling or issues with distribution. The system assesses the content of labels, monitors parcels in transit and detects potential deviations between the expected and actual route taken by the parcel in transit to its destination. If the AI system detects deviations, it will inform only the employee in charge. The employee in charge will then adopt the necessary procedures for correction (if any are needed). As the system’s purpose is ensuring smooth workflow operations and contractual compliance, supporting workers in their tasks rather than evaluating workers’ performance, the monitoring activity is incidental and falls outside the use case of point 4(b) of Annex III.

AI system for training performance evaluation

A company uses an AI system to assess employees’ progress in voluntary training modules by analyzing quiz results and course completion data. The system only provides feedback and learning recommendations to the employee to support individual development. Its function is limited to measuring learning outcomes within a training context, not to appraising job performance, determining promotions, or shaping managerial decisions.

AI system for office space optimization

A company uses an AI-enabled booking tool to optimise desk allocation in a hybrid workplace by matching employee reservations with available desks or meeting rooms. While the system organises physical workplace resources, it does not allocate tasks, determine promotions, evaluate workers, or affect employment rights.

AI system for corporate travel planning

A company uses an AI application to optimise business travel arrangements, suggesting cost-effective flights, hotels, and itineraries for employees required to attend meetings or conferences. The AI application’s suggestions do not prevent the employee from making alternative choices or even fully manually booking as long as it does not breach objective rules of company policy (e.g., maximum prices). The system supports logistics and budgeting, but does not determine the distribution of work, performance evaluations, career progression or termination decisions.

AI system suggesting delivery areas to platform couriers

A food delivery platform deploys an AI system that recommends geographic areas where demand is expected to be higher, based on factors such as weather, past orders, and real-time traffic data. Couriers receive notifications such as ‘high demand expected in Area X between 1-2 pm’ but they are free to ignore the suggestions. There are no penalties for declining recommendations, no specific registry of couriers that accepted or rejected the recommendation, and the system does not reduce their access to future tasks. The recommendation tool provides only optional, non-binding supporting information and does not represent task allocation on the basis of individual behaviour.

AI system compiling performance records for reporting

A manufacturing company uses an AI system to automatically collect from the company’s timekeeping application and organize employee monthly attendance records into structured reports and dashboards that the AI system sends to managers at a fixed date. The system does not monitor employees’ attendance, generate performance scores, make recommendations, or flag employees, it merely consolidates existing information that was entered by employees in the timekeeping application. Managers continue to perform qualitative evaluations independently. Although the system operates in employment monitoring and falls under the use case of point 4(b) of Annex III, it does not engage in monitoring nor does it make evaluative judgments and falls under the exception for AI systems intended to perform a preparatory task listed in Article 6(3)(d) AI Act.

AI system refining human-drafted promotion evaluations

A consultancy firm uses an AI-enabled writing assistant to refine managers’ promotion reports after the evaluations are fully completed. Managers decide on recommendations, draft justifications, and assign ratings based on company criteria before the AI system improves language clarity, ensures consistency with corporate style, and flags potentially biased wording. At the end of the process, the manager is required by internal policy to double-check the revised evaluations. The system does not change outcomes, scores, or create new content; its role is supportive. Although the system relates to promotion decisions, it does not influence decision-making and falls within the exception for AI systems intended to improve the result of a previously completed human activity listed in Article 6(3)(b) AI Act.