From Regulation to Requirements: An Automated Requirement Derivation and Explanation Pipeline
arXiv:2607.04448v1 Announce Type: cross Abstract: Ensuring software compliance with regulations such as the General Data Protection Regulation (GDPR) and the Artificial Intelligence Act (EU AI Act) poses a significant challenge, as requirements engineers must translate complex legal text into actionable software requirements - a process that remains largely manual and error-prone in practice. We present an automated regulation-to-requirements pipeline that identifies requirement-bearing clauses in regulatory documents and derives system-agnostic software requirements, accompanied by plain-lang
The increasing complexity of AI regulations like the EU AI Act and GDPR, coupled with the rapid development of AI for automating knowledge work, creates an urgent need for efficient compliance solutions.
This development addresses a critical bottleneck in software development and AI governance, significantly reducing the manual effort and error rate associated with regulatory compliance, thus accelerating AI deployment in regulated industries.
The process of translating complex legal texts into actionable software requirements transitions from a largely manual, error-prone task to an automated, more reliable pipeline, impacting development cycles and compliance costs.
- · Software Development Firms
- · AI Governance Consultancies
- · LegalTech Providers
- · Regulated Industries
- · Traditional Compliance Consulting
- · Manual Requirements Engineering
- · Companies slow to adopt automation
Automated compliance reduces time-to-market for regulated software and AI applications.
Increased compliance automation could lead to more stringent regulatory enforcement due to lower overheads, thereby leveling the playing field for compliant firms.
The legal and regulatory frameworks themselves might evolve to become more machine-readable, influencing future legislative drafting processes globally.
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Read at arXiv cs.AI