Across recruitment, performance management, promotion, and workforce analytics, Artificial intelligence (AI) systems are increasingly shaping who is hired, who advances, and how work is monitored and rewarded.
The EU Artificial Intelligence Act (EU AI Act), adopted in 2024, reflects a growing recognition that these systems can either support fair, consistent decision-making, or amplify existing inequalities at scale. From 2 August 2026, when the Regulation becomes generally applicable, organizations operating in or reporting in the EU face clear expectations for how AI is governed, deployed, and overseen in employment contexts.
For employers, the EU AI Act is not only a technology regulation. It is a people, fairness, and governance regulation.
What is the EU Artificial Intelligence Act?
The EU Artificial Intelligence Act is a comprehensive regulatory framework for artificial intelligence. Its central objective is to ensure that AI systems used within the EU are safe, trustworthy, and aligned with fundamental rights, including non-discrimination and equality.
The EU AI Act defines an AI system broadly as “‘a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments”.
Like the GDPR, the EU AI Act applies extraterritorially. Any organization deploying AI systems that affect individuals in the EU, regardless of where the organization or technology provider is based, must comply with its requirements.
Crucially, the EU AI Act adopts a risk-based approach. AI systems are classified according to the level of risk they pose to individuals and society. Those deemed “high-risk” are subject to the most stringent obligations.
Why AI used in employment is classified as high-risk
Under the EU AI Act, AI systems used in employment-related decisions are classified as high-risk. This includes systems used to support or inform decisions about recruitment, promotion, task allocation, performance evaluation, and termination.
The reasoning is straightforward. Employment decisions have a direct and lasting impact on individuals’ economic security, career progression, and dignity at work. When AI is used in these contexts, even small biases or design flaws can scale quickly, systematically disadvantaging certain groups based on gender, age, race/ethnicity, disability, or other protected characteristics.
The EU AI Act sets clear conditions for its the responsible use of AI in talent management. High-risk AI systems must be:
- Transparent (Art. 13)
- Subject to meaningful human oversight (Art. 14)
- Designed to prevent bias and discriminatory outcomes (Art. 12, Art. 15)
- Capable of being explained to those affected by their decisions (Art. 86).
In practice, this shifts AI in talent management and employment decisions from an efficiency tool to a governed system, one that must be justified, monitored, documented, and continuously assessed.
Four talent management areas under scrutiny
The EU AI Act highlights four core areas of talent management where AI use raises particular risks. Across each area, the same underlying principles apply: transparency, human oversight, bias prevention, and explainability.
1. Recruitment and applicant screening
AI is widely used to screen CVs, rank candidates, assess video interviews, and predict job performance. Under the EU AI Act, candidates must be informed when such systems are used, and organizations must be able to demonstrate that these tools do not introduce discriminatory bias. Recruiters and hiring managers must retain responsibility. AI-generated outputs should inform (not replace) human judgment and organizations must also be prepared to explain how final decisions were reached. Clear documentation will become critical in demonstrating compliance and fairness.
2. Promotion, progression, and termination decisions
AI systems are capable of informing performance evaluations, promotion readiness, and retention risk. Again, organizations must ensure that progression and termination decisions are subject to meaningful human review, supported by clear criteria, and monitored for disparate outcomes across different employee groups.
3. Task allocation and role assignment
Organizations using AI to allocate tasks, shifts, or projects based on behavioural data or inferred traits to increase operational efficiency. To avoid risks, the EU AI Act emphasizes that employers must understand what data is being used, what assumptions are embedded in the system, and whether outcomes remain equitable over time.
4. Performance monitoring and evaluation
AI-enabled performance monitoring tools raise important questions about transparency. Employees must be informed when such systems are in use, and organizations must be able to explain how monitoring data feeds into evaluations or decisions. Transparency is essential to maintaining employee confidence and trust.
Building readiness with the EDGE Standards
While the EU AI Act is a new regulatory instrument, many of its underlying principles will be familiar to organizations already working systematically on workplace fairness.
The EDGE Standards focus on how core people processes—pay, recruitment and promotion, professional development and training, flexible working, and organizational culture—operate in practice, and whether they produce fair and inclusive outcomes. This perspective is highly relevant in an AI-enabled workplace.
EDGE Certification® supports organizations in building the governance, transparency, and fairness infrastructure needed to responsibly deploy AI in employment decisions, in line with the principles of the EU Artificial Intelligence Act. This includes:
- Objective, measurable evidence on representation at all levels of the organization, pay equity, effectiveness of policies and practices to ensure equitable career flows, and inclusiveness of the culture.
- Clear documentation and structured action plans, strengthening explainability and accountability in decision-making.
- Independent verification, enhancing credibility and trust in workforce data and processes.
- A continuous certification cycle, enabling organizations to monitor progress, identify unintended consequences, and adjust course over time.
AI and workplace fairness will be a core focus of the EDGE Certified Foundation’s standards development in the year ahead. As technology evolves, so too must the frameworks used to assess its impact on careers and opportunities.
Organizations that invest now in transparency, governance, and fairness will be better positioned, not only to meet regulatory expectations, but to build trust with employees, candidates, investors, and other stakeholders in an increasingly automated world.
