Workforce Impacts & EU AI Act Implementation

Informational Submission on Workforce Impacts & EU AI Act Implementation

Date: January 2026

Submitted by: Voice for Change Foundation

Author: Kevin Bihan-Poudec, Founder

Overview

This page documents an informational, non-binding submission provided to the European Commission in support of the implementation of Regulation (EU) 2024/1689 (the AI Act).

The submission focuses on workforce-related considerations relevant to the operationalization of the AI Act’s human-centric, risk-based framework, informed by empirical observations from the United States, where large-scale AI deployment has progressed rapidly in advance of comprehensive governance.

The materials are offered to support implementation quality, post-market monitoring, and guidance development. They do not propose amendments to the AI Act, nor do they advocate restrictions on innovation or deployment.

Purpose of the Submission

The purpose of this submission is to contribute implementation-level insight to the European Union’s ongoing work on AI governance by:

• Sharing observed workforce dynamics from early large-scale AI deployment;

• Highlighting second-order effects that influence adoption, trust, and legitimacy;

• Demonstrating how workforce considerations intersect with existing AI Act mechanisms;

• Supporting predictable, scalable, and trusted AI deployment consistent with the Regulation’s objectives.

This submission is informational and non-binding. Any consideration or use of the materials remains entirely at the discretion of the European Commission and within established procedures for guidance, delegated acts, or future review.

Why Workforce Impacts Matter for AI Act Implementation

Experience from early-deploying jurisdictions indicates that workforce-facing AI systems—particularly in employment, hiring, and access-to-opportunity contexts—often become high-salience test cases for public trust in AI governance.

Where implementation lacks operational clarity, these systems can generate:

• Adoption resistance despite technical capability;

• Institutional uncertainty for deployers;

• Broader trust spillovers affecting adjacent AI use cases.

Conversely, where deployment expectations are clear and oversight is operationalized, AI adoption tends to be more stable, predictable, and socially legitimate.

For this reason, workforce considerations are not peripheral to the AI Act’s success, but structural to its effective implementation.

The materials also highlight how the pace and concentration of AI-enabled workforce substitution may serve as contextual signals for post-market monitoring and systemic-risk awareness, without implying quantitative limits, employment controls, or deployment caps.

Documents Included in This Submission

The submission consists of a modular implementation support set, designed to be used independently or together.

1. Executive Implementation Brief

Workforce Considerations in the Implementation of the AI Act

Purpose:

A concise, circulation-ready brief intended for policy officers and Heads of Unit.

Focus:

• Why workforce impacts are relevant to implementation quality;

• Key observations from early AI deployment;

• Alignment with the AI Act’s human-centric, risk-based design.

Status: Informational, non-binding

Download: Executive Implementation Brief (PDF)

2. Annex A – Workforce Impact Appendix

This Annex serves as an implementation-support appendix intended to inform post-market monitoring and guidance development within the existing scope of the AI Act and does not constitute a proposal for legislative amendment or additional compliance requirements.

Purpose:

A technical appendix structured to support post-market monitoring, guidance work, and internal reference.

Focus:

• Observed workforce dynamics in AI deployment;

• Second-order effects relevant to adoption, trust, and systemic risk;

• Illustrative, non-prescriptive indicators—including rate-of-change dynamics—relevant to post-market monitoring.

Status: Informational technical annex

Download: Annex A – Workforce Impact Appendix (PDF)

3. AI Act Implementation Mapping Note

Purpose:

A clarification note demonstrating where workforce considerations intersect with existing AI Act mechanisms, without proposing new obligations.

Focus:

• High-risk AI systems in employment;

• Human oversight requirements;

• Transparency obligations;

• Post-market monitoring;

• Fundamental rights protection.

Status: Informational, non-binding implementation note

Download: AI Act Implementation Mapping Note (PDF)

4. Public Transparency Statement

Purpose:

This page itself serves as a transparency record of the submission’s intent, scope, and non-binding nature, consistent with EU openness norms.

Scope and Positioning

This submission:

• Supports the AI Act’s human-centric approach;

• Recognizes the EU’s leadership in responsible AI governance;

• Does not introduce new regulatory categories;

• Does not advocate restrictions on innovation;

• Does not represent an official position of any EU institution.

The materials are intended to inform implementation reflection, not to advance advocacy or legislative proposals.

About the Author and Organization

Kevin Bihan-Poudec is a data analyst with over ten years of professional experience across multiple industries and the founder of the Voice for Change Foundation, a nonprofit organization focused on ethical AI, workforce stability, and responsible technology governance.

Over the past two years, he has conducted independent analysis of labor-market dynamics associated with large-scale AI deployment, informed by professional expertise and direct experience navigating AI-mediated employment systems.

Transparency and Public Availability

This page is published to provide public context for the submission and to make the materials accessible for reference by policymakers, researchers, and other stakeholders.

Publication of this page does not imply endorsement, consideration, or adoption by any European Union institution.

Disclosure: This content reflects original human critical thinking, informed and supported by AI-assisted research and analysis.