AI Licensing Marketplace Dominance Concerns

1. Introduction

Artificial Intelligence (AI) is increasingly being used for recruitment, employee evaluation, payroll administration, performance monitoring, disciplinary decisions, workforce planning, leave management and termination recommendations. This raises an important legal question: Can an employer completely replace a human HR manager with AI?

There is generally no universal rule declaring that the use of AI in HR is illegal. However, replacing HR managers does not eliminate the employer's legal responsibilities. Employment discrimination, privacy, labour rights, procedural fairness, contractual obligations and statutory compliance continue to apply even when an employment decision is made through an algorithm.

The legal issue is therefore not simply whether AI can perform HR functions, but whether the AI-driven system makes lawful, transparent, reviewable and non-discriminatory decisions.

The EU AI Act specifically treats AI systems used for recruitment, candidate evaluation, promotion, termination, task allocation and worker monitoring as high-risk systems because they can significantly affect workers' rights and career prospects.

2. Meaning of Replacing HR Managers With AI

AI replacement of HR managers may take several forms:

AI recruitment: screening CVs and ranking applicants.

AI interviewing: analysing video, speech or written responses.

AI performance management: calculating employee performance scores.

AI disciplinary systems: identifying alleged misconduct.

AI termination recommendations: identifying employees for dismissal or redundancy.

AI workforce allocation: assigning shifts, duties or projects.

AI payroll and benefits administration.

AI employee monitoring: analysing attendance, productivity or behaviour.

There is a significant legal difference between AI assisting an HR manager and AI independently making a final employment decision.

3. Is Complete Replacement of an HR Manager Legally Permissible?

AI can potentially perform many administrative HR functions. However, complete automation becomes legally problematic when the system independently determines a person's employment rights without adequate safeguards.

For example, an employer may use AI to:

shortlist candidates;

calculate payroll;

identify training requirements;

organise employee records; or

identify potential compliance problems.

These functions are generally different from allowing an algorithm alone to:

reject every applicant;

dismiss an employee;

determine misconduct;

deny promotion;

impose disciplinary penalties; or

determine employment status.

The more serious the legal consequence, the stronger the argument for meaningful human oversight, procedural safeguards and an opportunity for review.

4. Employer Cannot Escape Liability by Blaming AI

A central principle is that an employer generally cannot avoid employment-law responsibility merely because a decision was generated by software.

If an employer delegates recruitment or disciplinary authority to an AI system, the employer must still comply with applicable employment legislation.

This is particularly important in discrimination cases. An employer cannot necessarily argue:

"The computer made the decision, therefore nobody is responsible."

The legal responsibility may remain with the employer and, depending upon the jurisdiction and circumstances, may also extend to the AI developer or vendor.

5. AI and Employment Discrimination

AI may reproduce discriminatory patterns contained in historical employment data.

For example, if an employer historically hired more men for managerial positions, an AI system trained on that historical data could learn patterns that disadvantage female candidates.

Similar risks may arise concerning:

race;

sex;

age;

disability;

religion;

nationality;

pregnancy;

language;

ethnicity; and

other legally protected characteristics.

The important question is therefore whether the automated system produces an unlawful discriminatory effect, regardless of whether discrimination was deliberately programmed.

6. AI and Human Oversight

Human oversight is one of the most important safeguards.

An effective system should provide:

human review of significant decisions;

authority to override an AI recommendation;

reasons for adverse employment decisions;

mechanisms for correcting inaccurate data;

regular bias testing;

audit records;

employee/applicant complaints procedures; and

accountability for the final decision.

Under the EU AI Act, employment-related high-risk AI systems are subject to specific regulatory requirements, including human oversight. The Act recognises the risks of AI systems used for recruitment, promotion, termination, task allocation and worker monitoring.

7. Privacy and Employee Data

Replacing HR managers with AI normally requires extensive processing of personal information.

AI systems may process:

CVs;

attendance records;

performance data;

emails;

productivity information;

biometric information;

communications;

location information;

behavioural data; and

disciplinary records.

Such processing may trigger data-protection and constitutional privacy obligations.

The Indian Supreme Court's jurisprudence on privacy is particularly relevant. In Justice K.S. Puttaswamy (Retd.) v Union of India, the Court recognised privacy as a constitutionally protected right under Article 21. The judgment also discussed the risks created by technological profiling and automated processing of personal information.

Therefore, replacing HR personnel with AI does not create a legal licence for unlimited employee surveillance.

8. Procedural Fairness

An employee facing dismissal or serious disciplinary action may require procedural safeguards under applicable labour law, employment contracts, standing orders, collective agreements or principles of natural justice.

An AI system may identify an employee as a "high-risk" or "low-performance" worker, but an automated score should not automatically be treated as conclusive proof of misconduct.

The employee may need an opportunity to:

know the allegation;

challenge inaccurate information;

provide an explanation;

submit evidence;

receive a fair inquiry where required; and

challenge the final decision.

Consequently, AI may assist an HR investigation, but automation should not automatically eliminate legally required procedures.

9. AI and Employment Status

AI-controlled workplaces may also create questions concerning who is actually exercising managerial control.

The principle is illustrated by Uber BV v Aslam [2021] UKSC 5. The UK Supreme Court examined the practical reality of a work relationship rather than simply accepting the contractual description. Uber's technological platform exercised significant control over drivers, and the Court held that the drivers were "workers" for the purposes of relevant employment legislation.

The case was not about replacing HR managers, but it demonstrates an important principle for AI-driven workplaces:

Technological control can have legal consequences.

An employer cannot necessarily avoid employment obligations merely because decisions are implemented through an application or algorithm.

10. Important Case Laws

Case 1: Mobley v. Workday, Inc.

Court: U.S. District Court, Northern District of California
Case No.: 23-cv-00770-RFL

This is one of the most important emerging cases concerning AI and employment.

The plaintiff alleged that Workday's AI-based applicant-screening technology discriminated against applicants based on race, age and disability.

In July 2024, the court allowed significant claims to proceed, including allegations that employers delegated traditional hiring functions to Workday's algorithmic tools. The court recognised the possibility that an AI provider could potentially face liability under theories involving employment agency or agency relationships.

In May 2025, the court also granted preliminary collective certification concerning the age-discrimination claim.

Legal principle:
Delegating hiring functions to AI does not necessarily remove discrimination-law liability.

Case 2: Uber BV v Aslam [2021] UKSC 5

The UK Supreme Court considered whether Uber drivers were workers despite Uber's contractual description of them as independent contractors.

The Court examined the practical reality of Uber's technology and the control exercised through the platform and concluded that the drivers were workers for relevant statutory purposes.

Relevance to AI-HR:
A business cannot necessarily avoid legal obligations merely because management functions are performed through technology rather than a human manager.

Case 3: Justice K.S. Puttaswamy (Retd.) v Union of India

Court: Supreme Court of India

The Supreme Court recognised privacy as a constitutionally protected right under Article 21. The judgment addressed technological surveillance, profiling and processing of personal information and recognised that technological systems can create serious privacy concerns.

Relevance to AI-HR:
AI-based employee monitoring and profiling must be considered alongside privacy and personal-data protections.

Case 4: State v. Loomis, 2016 WI 68

Court: Supreme Court of Wisconsin, United States

The case concerned the use of the COMPAS algorithm in criminal sentencing rather than employment. The court considered whether an algorithmic risk assessment could be used in decision-making while recognising concerns concerning transparency and the limitations of proprietary algorithms.

Relevance to AI-HR:
Where an algorithm materially influences a person's legal interests, questions of transparency, accuracy and human decision-making become important.

Case 5: NJCM et al. v. State of the Netherlands (SyRI), ECLI:NL:RBDHA:2020:865

Court: District Court of The Hague

The Dutch court examined SyRI, an algorithmic system used to identify potential social-security fraud. The Court held that the system's legal framework violated Article 8 of the European Convention on Human Rights because the interference with privacy was insufficiently justified and the system was insufficiently transparent and verifiable.

Relevance to AI-HR:
Large-scale algorithmic profiling requires adequate transparency, proportionality and safeguards.

Case 6: OQ v Land Hessen and SCHUFA, Case C-634/21

Court: Court of Justice of the European Union
Decision: 7 December 2023

The case concerned automated scoring under Article 22 of the GDPR. The Court considered circumstances in which automated establishment of a probability score could amount to automated decision-making producing significant effects.

Although the dispute concerned credit scoring rather than employment, the reasoning is highly relevant to automated HR scoring systems because it demonstrates the legal importance of automated decisions that materially affect individuals.

Relevance to AI-HR:
AI-generated scores can become legally significant when they effectively determine an individual's access to important opportunities.

11. AI Replacing HR Managers and Natural Justice

Where an AI system recommends dismissal, disciplinary action or another serious employment consequence, the employer should consider whether the applicable law requires a fair procedure.

The major concerns include:

A. Right to be heard

The employee should have an opportunity to respond where the applicable law requires it.

B. Right to challenge evidence

Employees should be able to contest incorrect data or algorithmic conclusions.

C. Impartial decision-making

An automated system should not be designed so that a predetermined outcome is inevitable.

D. Reasoned decisions

The organisation should be able to explain the basis of significant employment decisions.

E. Human review

Serious employment consequences should ordinarily receive meaningful human scrutiny where required by applicable law.

12. AI and Termination of Employment

The replacement of an HR manager becomes particularly sensitive when AI determines termination.

For example, an AI system might calculate:

"Employee performance score = 42/100 → termination recommended."

Such a system may create legal problems if:

the data are inaccurate;

the scoring methodology is discriminatory;

the employee cannot challenge the score;

contractual disciplinary procedures are ignored;

statutory termination requirements are violated; or

the AI recommendation is automatically treated as the final decision.

Therefore, an AI-generated termination recommendation should not automatically be treated as legally sufficient evidence for dismissal.

13. AI and Collective Labour Rights

Replacing HR managers can also affect:

trade-union consultation;

collective bargaining;

worker representation;

grievance procedures;

disciplinary processes;

redundancy consultation; and

employee welfare.

Where labour legislation requires consultation with employees or unions, an employer cannot necessarily satisfy that requirement merely by allowing an AI system to communicate with workers.

Human participation may remain legally necessary.

14. Vendor Liability

AI HR systems are frequently supplied by third-party technology companies.

This creates a three-party legal structure:

Employer → AI Vendor → Employee/Applicant

Potential liability may arise from:

discriminatory algorithm design;

negligent software development;

inaccurate data processing;

unlawful surveillance;

breach of privacy;

failure to conduct appropriate testing; or

unlawful employment decisions made using the software.

The Mobley v. Workday litigation is particularly significant because it raises questions about whether an AI vendor can itself be treated as an employment-related actor or agent when its software performs functions traditionally carried out by employers.

15. Legal Requirements for Lawful AI-Based HR Management

An employer seeking to replace or substantially reduce human HR involvement should establish:

AI governance policy

Human oversight mechanism

Anti-discrimination testing

Data-protection compliance

Algorithmic impact assessment

Audit and record-keeping system

Employee grievance mechanism

Human appeal process

Cybersecurity controls

Vendor accountability clauses

Regular accuracy testing

Documentation of important employment decisions

16. Advantages of AI in HR

AI can provide legitimate operational benefits, including:

faster recruitment;

reduced administrative costs;

automated payroll;

consistent processing;

workforce analytics;

identification of training needs;

improved record management; and

faster employee-service responses.

However, efficiency does not by itself establish legality.

17. Major Legal Risks

18. Legal Position

The legality of replacing HR managers with AI depends heavily upon jurisdiction, the particular HR function, the applicable employment legislation, the nature of the decision and the degree of human oversight.

There is a significant legal distinction between:

AI as an HR assistant

and

AI as the final HR decision-maker.

Administrative automation is generally easier to justify than fully automated decisions involving dismissal, discrimination, disciplinary punishment, promotion or other fundamental employment interests.

The emerging case law demonstrates that courts are increasingly examining the actual effect of algorithmic systems, rather than simply accepting the argument that "the computer made the decision."

19. Conclusion

AI can legally perform many HR functions, but AI does not automatically acquire the legal authority of an HR manager merely because an employer delegates HR tasks to software.

Employment obligations continue to apply when decisions are automated. Employers must consider equality and non-discrimination law, privacy and data protection, contractual obligations, procedural fairness, labour relations and applicable statutory requirements.

The developing litigation, particularly Mobley v. Workday, demonstrates that AI-based employment systems may themselves become the subject of discrimination litigation.

The broader principles found in Puttaswamy, Uber BV v Aslam, State v Loomis, the SyRI case and OQ v Land Hessen/SCHUFA indicate that technological decision-making does not place employment decisions outside ordinary legal scrutiny.

Therefore, the legally safer model is generally AI-assisted HR management with meaningful human accountability, rather than an entirely unreviewable automated HR system. The precise requirements, however, depend on the governing jurisdiction and the particular employment decision.