The first case in which an employee won roughly $17,000 from her company after being replaced by artificial intelligence is not an isolated incident but a warning sign for every business. As neural networks are deployed ever more widely across HR and customer service, the number of legal claims grows with them. To avoid ending up as the defendant and to protect your business from multi-million-dollar payouts, you need to understand the new legal risks that arise when AI is used to manage people.
In the eyes of the law, automation through AI is not in itself a valid ground for dismissal. A court assesses whether the formal procedure was followed, not the technical reason for the changes.
Case No. 1: how a court reinstated an employee of Company X
The most high-profile precedent to date is the story of a category procurement manager at Company X. Under a 'lean production' optimisation programme, most of her responsibilities were handed over to a neural network. The employee was given a choice: either move to a two-hour working day with a corresponding pay cut, or resign. After she refused the new terms, her employment contract was terminated, and she took the matter to court.
The outcome was disappointing for the company. The court ruled entirely in the claimant's favour. The judges found that the change in working conditions was merely a screen concealing what was in fact a redundancy. The employer had breached the procedure on several counts.
Employees must be notified personally and in writing of an upcoming redundancy at least 2 months in advance.
In a redundancy, employees must be offered all suitable vacancies available within the company.
It relied on a change-of-terms dismissal, when it should have used the redundancy procedure with payment of all severance entitlements.
The company was ordered to reinstate the employee, pay her wages for the entire period of enforced absence (from July 2024 to February 2025), and compensate her for moral damages and legal costs. The total payout came to roughly seventeen thousand dollars.
In the eyes of the law, automation through AI is not in itself a valid ground for dismissal. A court first assesses whether the formal procedure was followed, not the technical reason for the changes.
Other legal risks that cannot be ignored
The Company X case is only the tip of the iceberg. When deploying AI in HR and customer processes, businesses face at least three further groups of risks.
Discrimination and 'dirty' data
Algorithms learn from a company's historical data, which already contains bias. If leadership roles were filled by men for decades, the AI will 'learn' to downgrade women's CVs. An affected employee can sue for discrimination, and the company will have to prove the fairness and objectivity of its 'black box' - which is practically impossible.
Data breaches and violations of data protection law
Any AI system that processes the personal data of employees or customers falls under data protection law such as the GDPR. By transferring your employees' data to a foreign neural network, you risk a real fine from the data protection authority, as this may amount to a cross-border data transfer without proper consent.
Opacity of decisions
If you cannot clearly explain to a court or a regulator why your neural network rejected a candidate or made a decision, you automatically create every precondition for a ruling against you.
| Consequences → Likelihood ↓ | Low | Medium | High |
|---|---|---|---|
| High | Opacity of AI decisions | Breach of the dismissal procedure | Cross-border transfer of personal data (data protection) |
| Medium | Customer complaints about the bot | Discrimination from 'dirty' data | Reinstatement lawsuit |
| Low | Technical model failure | Reputational noise in the media | Collective employee lawsuit |
Recommendations: how to integrate AI into your business safely
The point is not to ban the technology but to set it up correctly. For a neural network to work for you rather than against you in court, follow five rules.
This is the golden rule. The final decision on hiring, dismissal or a major bonus must always be made by a person. Use AI only as an assistant that prepares analysis and recommendations.
Develop and approve, by company order, a document that clearly sets out: which tasks AI is used for, which data it processes, and which security measures apply. This is your 'defence map' for regulators.
There is no perfect algorithm, but it is your duty to take reasonable steps to identify and minimise discriminatory factors. Document the results of every such audit.
If AI takes over part of a role's functions, do not try to dismiss the person 'by mutual agreement' or 'voluntarily' under pressure. Run the redundancy procedure honestly, observing notice periods, offering vacancies and paying compensation.
Check whether your employees' data is transferred abroad when using a given AI service, and whether there is a lawful basis for it under data protection law.
| Do (protects you in court) | Don't (creates litigation risk) |
|---|---|
| Leave the final decision to a human | Let the AI automatically reject and dismiss people |
| Run a redundancy under labour law with severance payments | Disguise a redundancy as a 'change of working conditions' |
| Notify personally and in writing two months in advance | Present a fait accompli or pressure a 'voluntary' resignation |
| Store data domestically and obtain consent under data protection law | Pour personal data into a foreign neural network without a legal basis |
| Document the algorithm's bias audit | Use a 'black box' whose decisions cannot be explained |
Tailored support from the consulting firm G-Invest
Deploying AI into people management and customer service is not just a technical challenge but a complex legal and strategic one. The consulting firm G-Invest offers end-to-end support to turn technology into an asset rather than a source of risk:
- Audit of current HR processes - we identify the bottlenecks where using AI could lead to lawsuits and fines.
- Development of a robust AI Policy - we draft an internal document tailored to your business that protects you.
- Legal review of contracts with AI and software vendors for compliance with data protection law.
Deploy AI without legal risk
G-Invest will build a step-by-step plan for integrating AI into HR and customer service - innovative and legally sound: a process audit, an AI Policy and a contract review for data protection compliance.
Frequently asked questions
Can you legally dismiss an employee simply because their functions have fully passed to a neural network?
No, you cannot. There is no direct ground of 'dismissal due to AI deployment' in labour law. When functions are automated, the employer must run a redundancy procedure with all the guarantees owed to the employee. A decision made solely by AI will have no legal force in court.
What penalties apply for discrimination when using AI in HR?
Discrimination in employment carries administrative liability. Fines for officers typically run from about $110 to $170, and for companies from about $550 to $1,100. The real cost, however, lies in the reputational damage and possible reinstatement claims with compensation, as in the case described in this article.
Do I need the employee's consent to process their data using AI?
Yes, in most cases. Under data protection law, processing personal data (which a neural network does) requires the data subject's consent, except in a narrow set of situations (for example, to perform the employment contract). The company's internal policy must clearly state which AI tools are used, which data is processed and for what purpose.
What actions will protect the company from litigation when deploying AI in HR processes?
The main protection is a 'human in the loop' and solid documentation. Adopt an AI Policy, run regular bias audits of your algorithms, and record that the final decision on hiring, dismissal or bonuses is made by a person on the basis of the AI's recommendation, not by the AI itself. And never try to replace a redundancy with a dismissal 'by mutual agreement' or 'due to a change in working conditions'.
What should a company do if it has already been sued over a decision made with AI?
Do not try to defend the automated decision as such. Your main line of defence is to prove that a human made the decision and that the AI was only a supporting tool. Provide all evidence of human oversight, documents on the algorithm audit, and proof that procedures were followed.