Regulatory
Response

Why I built it, and why it will get better

I am trying to track what the real measurable effects of AI are being reported. I trace every number to its primary source. Where the data is confirmed, I say so. Where it is directionally accurate but imprecisely sourced, I say that too. Where it cannot be verified, I say that as well. This tracker is the result.

I am not an analyst or forecaster. I trace every number to its primary source. Where a number is confirmed, I say so. Where it is directionally accurate but imprecisely sourced, I say that too. Where it cannot be verified, I say that as well. Where credible sources disagree, I present both positions. This means my dashboard will sometimes show fewer data points than a typical industry report. I think that is a feature, not a bug.

I will update the tracker every month. Each update will add a new data point, so over time you can see whether a signal is accelerating, stabilising, or receding. Historical data will never be overwritten. After three or four updates, the trends will become the most important part of the dashboard. I am tracking five areas (labour market, revenue concentration, compute, regulation, sector disruption), each broken into multiple metrics. This page covers regulatory response, which has four metrics. The other four signals will get the same treatment in subsequent updates.

Methodology

Source selection: I search for primary regulatory texts (the EU AI Act itself, state legislation trackers), legal analysis from major firms (DLA Piper, Holland and Knight), and policy research organisations. I exclude any source where the underlying regulatory text cannot be located or where the interpretation is not traceable to the legislation.

Confidence ratings: VERY HIGH = published government dataset or peer-reviewed study with large sample. HIGH = primary dataset with transparent methodology. MEDIUM-HIGH = primary aggregator with broad scope. MEDIUM = secondary source or different methodology. MODERATE = contextual only, not directly comparable. LOW = qualitative or untraceable.

Limitations: Regulatory landscapes change quickly. The EU AI Act implementation timeline may shift. US state-level AI legislation is evolving weekly; the 20+ figure is a snapshot, not a continuous count. The EU Omnibus amendment is in progress and its final form is uncertain. Where data points cannot be traced to a single publication, I note this explicitly. My goal is to present what the regulatory environment shows, not to predict legislative outcomes.

Date of access: All sources were last accessed in June 2026. Source URLs were verified live during research. Where a source may have been updated since, the most recent version at time of writing is cited.

EU AI Act high-risk compliance deadline

The original claim: the EU AI Act classifies workplace AI, including recruitment, performance monitoring, work allocation, and termination decisions, as "high risk". Most high-risk (Annex III) obligations apply from August 2026, with the remaining high-risk obligations following in August 2027. Fines can reach 3% of global turnover. This traces directly to the EU AI Act itself and legal analysis from Holland and Knight.

US comprehensive federal AI law

The original claim: the United States has no comprehensive federal AI law. This is not a projection or an estimate. It is a statement of fact as of June 2026. Multiple bills have been introduced in Congress, but none has passed both chambers and been signed into law.

Preemptive federal law or state-level patchwork?

US state-level AI laws enacted or proposed

The original claim: over 20 US states have enacted or proposed AI-related legislation. This traces to Beyond Tomorrow's regulatory update and legal analysis from DLA Piper. The exact count is difficult because "AI law" covers everything from deepfake bans to employment disclosure requirements, and new bills are introduced weekly.

EU Omnibus simplification amendment

The original claim: the EU is already considering an "Omnibus" amendment to delay some high-risk AI obligations under the AI Act. This signals that even regulators feel the tension between safety and competitiveness. This traces to DLA Piper's legal analysis of the proposed amendment.

What I am watching

Sources and confidence key

Sources by metric

Confidence ratings

Severity assessment