Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration

arXiv cs.AI / 4/25/2026

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Key Points

The paper examines how to translate EU AI Act governance requirements into real day-to-day software development, an area where team-level evidence has been limited.
It proposes an “internal expert collaboration” legal-text-to-action pipeline, using requirement extraction from legal texts, practitioner assessment/ideation, and collective prioritization for implementation.
The study identifies three practitioner response patterns—convergence, existing practice, and disconnection—and shows how these perceptions affect implementation and engagement.
Practitioners tend to prioritize requirements that support end-users or their own development goals, while verification-heavy requirements are often seen as administrative “box-ticking.”
The authors argue that governance can be either genuine or performative depending on whether teams understand how compliance directly improves system quality and user protection, and they position expert collaboration as a way to make governance work visible and jointly owned.

Abstract

Under the EU AI Act, translating AI governance requirements into software development practice remains challenging. While AI governance frameworks exist at industry and organizational levels, empirical evidence of team-level implementation is scarce. We address this "Last Mile" Challenge through insider action research embedded within an AI startup. We present a legal-text-to-action pipeline that translates EU AI Act requirements into actionable strategies through internal expert collaboration by extracting requirements from legal text, engaging practitioners in assessment and ideation, and prioritizing implementation through collective evaluation. Our analysis reveals three patterns in how practitioners perceive regulatory requirements: convergence (compliance aligns with development priorities), existing practice (current work already satisfies requirements), and disconnection (requirements perceived as administrative overhead). Based on these patterns, we discuss when governance might be treated genuinely or performatively. Practitioners prioritize requirements that serve end-users or their own development needs, but view verification-oriented requirements as box-ticking exercises. This distinction suggests a translation challenge: regulatory requirements risk superficial treatment unless practitioners understand how compliance serves system quality and user protection. Expert collaboration offers a practical mechanism for transforming governance from external imposition to shared ownership and making previously invisible governance work visible and collective.