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Impact Assessment Helper


Added by:   OECD analyst
Added on:   28 Oct 2026
Updated by:   OECD analyst
Updated on:   28 Oct 2026

Konsekvenshjälpen is an AI assistant developed to help public officials produce higher-quality regulatory impact assessments. It provides step-by-step guidance based on Sweden’s Impact Assessment Ordinance and the Agency’s official guidance, helping users explore alternatives, identify affected stakeholders, and improve drafts among other tasks.

Name in original language

Konsekvenshjälpen

Initiative overview

Konsekvenshjälpen (“Impact Assessment Helper”) is a public-sector AI assistant which is responsible for guidance and training on regulatory impact assessments under the new Impact Assessment Ordinance (SFS 2024:183). We launched the service as a web-based prototype in 2025 to complement written guidance on the web and to provide on-demand, situation-specific support.

The assistant supports civil servants and inquiry teams across government throughout the impact assessment workflow: framing the problem and objectives, planning the work, proposing and comparing policy options (including the “do nothing” option), identifying affected stakeholders, selecting suitable analytical methods, suggesting data sources, and reviewing drafts for clarity and compliance. The goal is not to replace professional judgement, but to lower the threshold for asking the right questions early and consistently.

Technically, Konsekvenshjälpen combines retrieval-augmented generation with a tightly scoped system prompt. Retrieval is used to fetch relevant passages from the Agency’s curated guidance, while the model is instructed to base answers on (and refer back to) the ordinance and Agency materials. The deployed solution uses an OpenAI vector search component for retrieval and Anthropic Claude for response generation.

The Agency designed the tool with transparency and responsible use in mind: it is explicitly positioned as a drafting and reasoning aid, users are warned about hallucinations and asked not to input personal or sensitive information, and the team performs ongoing monitoring and updates. The Agency for Financial and Public Management expects the approach to be transferable to other jurisdictions by swapping the knowledge base and legal framework while retaining the same human-in-the-loop model of use.

Results, outcomes and impacts

Early user testing with experienced impact-assessment practitioners showed strong perceived usefulness. In immediate post-answer surveys, 96% of responses were rated relevant and usable, and 93% of respondents said they would recommend the service to others. ESV also observed that the tool can help first-time AI users adopt AI in analytical work. A full evaluation after five months of use will soon be concluded. Operationally, low marginal costs are estimated: for a medium-use scenario (200 active users per month, with approximately five questions each), the total annual cost for 2026 is estimated at up to SEK 120,000. Expected impacts include more consistent application of the methodology, fewer overlooked issues, and clearer regulation for affected stakeholders.

Other relevant details

Challenges and lessons learned: Key challenges included (1) quality assurance for outputs that are not simply ‘right or wrong’, (2) managing hallucination risk and ensuring legal/administrative alignment, and (3) addressing information-security concerns and user behaviour (copy-paste use without critical review). We responded by constraining the assistant’s scope to impact assessments, grounding answers in the ordinance and the Agency’s curated guidance, and using retrieval to reduce drift. The deployed model is configured for low creativity and is required to reference the legal text when relevant. Lessons learned: a small, authoritative knowledge base can outperform a broad one in government contexts; user testing with practitioners is essential for tuning tone and usefulness; and clear guardrails and user guidance (e.g. ‘do not share sensitive data’ and ‘verify facts’) are crucial. Ongoing monitoring, prompt iteration and periodic evaluation are necessary to keep pace with rapidly changing foundation models.

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Active

Start Year:

  • 2025

Target Sectors:


OECD AI Principles:

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