Global AI/Regulatory Tracker
Access real-time global regulatory insights and AI governance updates — no more manual searches or missed opportunities
A saved example of what you can collect and monitor with Jsonify. Create your own version in Jsonify.
Build this in JsonifyYour original goal is prefilled.
Goal
I want to get comprehensive, real-time data on global regulatory updates and evolving AI governance frameworks from official government and industry standards websites.
Source coverage
- govinfo.gov
- federalregister.gov
- nist.gov
- whitehouse.gov
- europa.eu
- regulations.gov
- ai.gov
- iso.org
- iec.ch
- oecd.org
- isoc.org
- w3.org
Sample data
Illustrative sample data from the original configuration, not live or verified results.
| id | Source | Title | Document Type | Summary | Jurisdiction | Effective Date | Status | Action Required | Estimated Impact | Link |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | federalregister.gov | Guidance on Safe Deployment of Foundation Models in Federal Procurements | Notice | OMB and GSA publish guidance clarifying procurement safeguards for foundation models, including documentation, testing, and bias assessments. | United States (Federal) | 2026-02-02 | Published | Agencies to update RFP templates and include risk assessment attachments | High — applies to all federal AI procurements; may delay some solicitations | https://www.federalregister.gov/docket/2026-0001/guidance-foundation-models-gsa-omb |
| 2 | whitehouse.gov | Executive Order on International AI Safety Standards Coordination | Executive Order | Directs interagency coordination with allies to promote interoperable safety and audit standards for AI systems and to accelerate diplomatic engagement. | United States (Federal) | 2026-02-01 | Enacted | DoS and OSTP to open bilateral talks; agencies to map existing standards | Very High — shapes international regulatory alignment and trade policy | https://www.whitehouse.gov/briefing-room/presidential-actions/2026-execorder-ai-safety |
| 3 | nist.gov | NIST SP 800-999 Draft: Risk Framework for Adaptive Machine Learning | Draft Standard | Proposes a lifecycle risk management framework for adaptive ML systems including continuous monitoring and model-change controls. | United States (Federal) | 2026-02-03 | Draft for Public Comment | Submit public comments within 60 days and run pilot implementations | High — expected to inform procurement and certification | https://www.nist.gov/publications/sp-800-999-risk-framework-adaptive-ml |
| 4 | ai.gov | Federal AI Research Funding Priorities 2026-2028 | Policy Paper | AI.gov outlines prioritized research areas: robustness, interpretability, privacy-preserving ML, and socio-technical impacts. | United States (Federal) | 2026-02-04 | Published | Research institutions to align grant proposals; agencies to update RFAs | Medium — influences funding directions and grant review | https://www.ai.gov/policy/federal-research-priorities-2026 |
| 5 | govinfo.gov | Agency Record: DOJ Antitrust Guidance on AI Market Practices | Rulemaking Record | DOJ releases findings and recommended safeguards against anti-competitive data-sharing agreements in AI marketplaces. | United States (Federal) | 2026-02-02 | Final Report | Companies to review data-sharing contracts; potential investigations signaled | Medium — enforcement focus on mergers and data pools | https://www.govinfo.gov/content/pkg/2026-doj-ai-antitrust |
| 6 | regulations.gov | Proposed Rule: Transparency Requirements for Automated Decision Systems | Proposed Rule | Proposal would require covered entities to publish model documentation, impact assessments, and redress mechanisms for ADS. | United States (Federal) | 2026-02-03 | Open for Comment | Stakeholders to submit comments by deadline; compliance planning recommended | High — broad compliance obligations for firms using ADS | https://www.regulations.gov/docket/FTC-2026-ADS-transparency |
| 7 | europa.eu | EU Commission Recommendation on AI Interoperability Profiles | Recommendation | Non-binding guidance encouraging member states to adopt common data formats and interface standards for AI model exchange and certification. | European Union | 2026-02-01 | Published | Member states encouraged to harmonize procurement specifications | Medium — facilitates cross-border AI deployment | https://commission.europa.eu/document/ai-interoperability-2026 |
| 8 | europa.eu | Draft Regulation: Strengthened AI System Conformity Assessment Procedures | Draft Regulation | Updates to conformity pathways for high-risk AI systems, adding third-party auditing and post-market surveillance requirements. | European Union | 2026-02-04 | Proposal (Trilogue Negotiations) | Industry to prepare for extended certification timelines | High — increases certification cost and time for high-risk products | https://eur-lex.europa.eu/legal-content/AI-conformity-2026 |
| 9 | oecd.org | Working Paper: Measuring Economic Impact of AI Regulation | Working Paper | Presents models projecting GDP and employment effects under varying regulatory stringency scenarios across OECD members. | OECD (International) | 2026-02-02 | Published | Policymakers to consider model outputs when designing interventions | Medium — informs macro policy debates | https://www.oecd.org/ai/measuring-economic-impact-2026.pdf |
| 10 | iso.org | ISO/CD 4200: Governance of Generative AI — Committee Draft | Committee Draft | International committee draft proposing governance principles for generative AI including provenance, watermarking, and audit trails. | International (ISO) | 2026-02-03 | Committee Draft | National bodies to review and vote on draft | Medium — could become global interoperability baseline | https://www.iso.org/standard/cd-4200-generative-ai |
| 11 | iec.ch | IEC TS: Safety Assessment Methods for AI-Integrated Industrial Control Systems | Technical Specification | Details recommended safety assurance methods and test cases for AI components in industrial control contexts. | International (IEC) | 2026-02-04 | Published (TS) | Manufacturers to adopt test protocols and report conformity | Medium — affects industrial suppliers and operators | https://www.iec.ch/technical-specifications/ai-ics-2026 |
| 12 | w3.org | W3C Note: Accessible AI Outputs and Semantic Metadata | Technical Note | Guidance for embedding semantic metadata and accessibility labels in AI-generated content to improve discoverability and inclusivity. | International (Standards) | 2026-02-02 | Published | Developers to implement metadata schemas; vendors to update documentation | Low — improves UX and compliance with accessibility laws | https://www.w3.org/TR/ai-accessible-metadata-2026 |
| 13 | isoc.org | Internet Society Brief: Governance Principles for Decentralized AI | Policy Brief | Argues for multi-stakeholder governance approaches for decentralized AI systems and outlines trust-building measures. | International | 2026-02-01 | Published | Civil society and industry to engage in multi-stakeholder dialogues | Low — normative influence on governance debates | https://www.internetsociety.org/resources/decentralized-ai-governance-2026 |
| 14 | regulations.gov | Notice: Public Workshop on AI Safety Testing Methodologies | Notice | CFTC and NIST announce a joint public workshop on standardized testing methodologies for AI safety and robustness. | United States (Federal) | 2026-02-03 | Published | Register to attend; submit testing proposals | Low — information-sharing and standards development | https://www.regulations.gov/event/nist-cftc-ai-testing-workshop-2026 |
| 15 | federalregister.gov | Final Rule: Privacy Safeguards for AI-Powered Healthcare Tools | Final Rule | HHS issues rule tightening patient consent, data minimization, and audit trails for AI clinical decision support tools. | United States (Federal) | 2026-02-04 | Final | Healthcare providers/vendors must update privacy practices and submit compliance plans | High — significant compliance costs for health-tech firms | https://www.federalregister.gov/documents/2026/hhs-ai-healthcare-privacy |
| 16 | nist.gov | Model Card Standard v2.0 | Publication | Updates recommended fields and verification procedures for model cards to improve transparency and reproducibility. | United States (Non-regulatory Guidance) | 2026-02-02 | Published | Organizations encouraged to adopt v2.0 fields in model documentation | Medium — impacts reporting practices across sectors | https://www.nist.gov/publications/model-card-standard-v2 |
| 17 | europa.eu | Guidance: AI and Consumer Protection — Right to Explanation | Guidance Note | Clarifies application of consumer protection rules to algorithmic decisions and explains redress options for EU consumers. | European Union | 2026-02-03 | Published | Businesses to update terms and disclosure practices | Medium — affects digital service providers and platforms | https://ec.europa.eu/info/publications/ai-consumer-protection-2026 |
| 18 | whitehouse.gov | OSTP Memorandum: Federal Dataset Sharing for Responsible AI | Memorandum | Memorandum promoting secure sharing of government datasets for AI research with privacy-preserving access controls and licensing terms. | United States (Federal) | 2026-02-01 | Issued | Agencies to inventory datasets and publish access frameworks | Medium — increases available research data while protecting privacy | https://www.whitehouse.gov/wp-content/uploads/2026/02/ostp-dataset-sharing-memo.pdf |
| 19 | iec.ch | Amendment: IEC 80079 Extension for AI in Hazardous Environments | Amendment | Adds clauses describing certification criteria for AI controllers in explosive atmospheres and hazardous locations. | International (IEC) | 2026-02-04 | Published Amendment | Product certification labs to update test matrices | Low — targeted impact on specialized sectors | https://www.iec.ch/amendments/iec-80079-ai-2026 |
| 20 | iso.org | ISO Public Consultation: Data Provenance for AI Training Sets | Public Consultation | ISO invites comments on proposed provenance metadata schema for datasets used in AI training to improve traceability and compliance. | International (ISO) | 2026-02-03 | Open for Comment | Stakeholders to submit feedback within consultation window | Medium — informs future dataset standards | https://www.iso.org/consultations/data-provenance-ai-2026 |
| 21 | govinfo.gov | Congressional Report: Economic Implications of AI Export Controls | Report | Congressional research service publishes analysis of options and trade-offs for U.S. export controls on advanced AI capabilities. | United States (Federal) | 2026-02-02 | Published | Legislators and industry to review recommended options | High — potential to affect international technology flows | https://www.govinfo.gov/crs-reports/ai-export-controls-2026 |
| 22 | oecd.org | Recommendation: AI Ethics Impact Assessment Toolkit | Toolkit | A practical toolkit to help governments and organizations perform ethics impact assessments for AI systems, with templates and checklists. | OECD (International) | 2026-02-04 | Published | Adopt toolkit for procurement and oversight processes | Low — supports implementation capacity building | https://www.oecd.org/ai/ethics-impact-assessment-toolkit-2026 |
| 23 | isoc.org | Statement: Net Neutrality Principles Applied to AI Traffic Prioritization | Policy Statement | Internet Society issues principles discouraging discriminatory prioritization of AI model traffic by network operators. | Global (Policy) | 2026-02-01 | Published | Advocates and regulators to consider principles in telecom rulemaking | Low — influences regulatory debates on network neutrality | https://www.internetsociety.org/policy/ai-traffic-prioritization-2026 |
| 24 | w3.org | Community Draft: Verifiable Credentials for Model Provenance | Community Draft | Draft specification for issuing verifiable credentials asserting model lineage, training data attestations, and governance claims. | International (Web Standards) | 2026-02-03 | Community Draft | Developers to experiment with credential schemas and provide feedback | Medium — could enable cross-platform trust signals | https://www.w3.org/community/model-provenance-draft-2026 |
| 25 | federalregister.gov | Proposed Rule: Mandatory Incident Reporting for High-Risk AI Systems | Proposed Rule | Agencies propose a mandatory timeline and format for reporting serious AI-related incidents that cause harm or significant outages. | United States (Federal) | 2026-02-02 | Open for Comment | Organizations to prepare incident response and reporting workflows | High — increases regulatory reporting burden and transparency | https://www.federalregister.gov/docket/ai-incident-reporting-2026 |
| 26 | ai.gov | Framework: Public-Private Partnership for AI Safety Testbeds | Framework Document | Details structure and funding model for testbeds to evaluate AI robustness in real-world settings, led by government and industry partners. | United States (Federal) | 2026-02-04 | Published | Industry partners to apply for participation and funding | Medium — accelerates collaborative safety evaluations | https://www.ai.gov/initiatives/ai-safety-testbeds-2026 |
| 27 | europa.eu | EU-UK Cooperation Agreement on AI Certification Recognition | Agreement | EU and UK agree to mutually recognize certain AI certification schemes to reduce trade friction for certified products. | European Union / United Kingdom | 2026-02-03 | Signed | Certifying bodies to align procedures for mutual recognition | Medium — eases market access for certified AI products | https://commission.europa.eu/presscorner/detail/eu-uk-ai-certification-2026 |
| 28 | nist.gov | Challenge Event Results: Adversarial Robustness Evaluation 2025-2026 | Results Brief | NIST publishes results from a multi-party adversarial robustness challenge and recommends benchmark improvements. | United States (Research) | 2026-02-02 | Published | Researchers and vendors to adopt updated benchmarks | Low — technical community guidance | https://www.nist.gov/challenges/adversarial-robustness-2026-results |
Insights and analytics
- Total Regulatory Updates Today (metric)
- Trends in AI Governance Frameworks (line)
- Latest Regulatory Changes by Source (table)
- Distribution of Regulatory Updates by Region (donut)
- Number of Updates by Source (bar)
- Top 5 Regulatory Bodies by Update Frequency (horizontal_bar)
- Total AI Governance Frameworks Published (metric)
- Cumulative Updates Over Time (area)
- Key Observations on AI Regulations (insights)
- Detailed Listing of Current AI Regulations (table)
- AI Governance Framework Adoption Rate (line)
- Percentage of Updates Impacting Businesses (metric)
Change notifications
- New Regulation Detected — new update available ai.gov
- Regulation Update Found — has been updated nist.gov
- New Document Available — just published federalregister.gov
- Regulation Removed — is no longer available regulations.gov
- Effective Date Changed — effective date updated whitehouse.gov
Integrations and delivery
- api
- bigquery
Make this your own
Start with this goal in Jsonify, then choose the sources and data you need.
Build this in Jsonify