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Agricultural and digital innovations are advancing rapidly, creating new opportunities to explore how regulatory review processes can become more efficient, transparent, and scalable while maintaining rigorous oversight. This perspective introduces Rules-as-Code (RaC), the practice of translating regulatory requirements into machine-executable logic as a mechanism to realize this transition. Two case studies illustrate how RaC can support automated compliance checks in pesticide and crop biotechnology risk assessments. By providing a standardized digital representation of regulatory requirements, RaC offers a framework to enhance consistency, efficiency, and regulatory preparedness in an increasingly data-rich scientific landscape.
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Riter et al. (2026) studied this question.
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