Methodology

Every record on this site is held to four standards:

1. Primary-source citations. Every law and every bill carries at least one primary source — an ILGA bill-status page, the full bill text, or the signed Public Act — visible on the page and dated with the day it was retrieved.
2. A single source of truth. All content lives in one typed dataset. Every headline number is computed from that dataset, never typed by hand, so counts cannot disagree from one page to the next.
3. Plain-English analysis. Each statute is explained with the same template — what it requires, who is covered, what the exposure is, and the key dates.
4. Freshness and verification. A global “as of” date, a per-record verification date, this methodology, and a changelog that records what changed and when.

This reference tracks Illinois legislation that names artificial intelligence or that carries substantive AI provisions, across the 104th General Assembly. It covers enacted statutes and the bills moving through the current session.

What it deliberately does not track, because these deserve their own treatment and a different sourcing discipline:

• Agency rules and guidance (for example, IDHR's rulemaking under PA 103-0804 or ISBE's guidance under PA 104-0399), where much of the operative enforcement detail is actually set.
• Court cases and Attorney General opinions, which will define these statutes in ways the text does not.
• Federal action and preemption questions, noted where they bear on an Illinois law but not tracked as records.

Analyst notes — the read on where a bill is likely to land — are interpretive, and are marked as analysis rather than record. The status and history of each bill stay tied to ILGA's record of action.

Every enacted statute and tracked bill carries at least one primary source — the Illinois General Assembly bill-status page, the full bill text, or the signed Public Act — dated with the day it was retrieved. Derived figures trace to a statute or to a computation over this dataset.

The Illinois General Assembly (ilga.gov) is the canonical source. For each record, the authoritative reference is the ILGA bill-status page, the full bill text, or the signed Public Act PDF — linked directly, with the date it was retrieved. Where a Public Act number is not yet confirmed, the record says so rather than assert one.

Each source is labelled by type — Public Act, Bill status, Bill text, or Compiled Statutes — followed by its publisher, host, and the date it was retrieved. A “retrieved” date is a promise about when the link was last confirmed, not a claim that the underlying law has not changed since. When in doubt, the linked primary source governs, not this summary of it.

The record is reviewed against ILGA after each major legislative milestone: committee deadlines, chamber floor deadlines, spring and fall adjournment, and gubernatorial action on passed bills.

The global “as of July 31, 2026” stamp in the footer is the date the whole record was last reconciled against ILGA. Each law and bill also carries its own verification date. Every substantive change is logged in the changelog.

Bill status

Law status

Sectors

The controlled vocabulary of 7 sectors — Healthcare, Employment, IP / Creative, Education, Criminal / Child Safety, Consumer Protection, Frontier AI — is the closed set every enacted law is tagged against. The sector count on the site is the length of this list, which is why it cannot drift out of step with the laws it describes.

Regulatory vectors

A vector is a thematic grouping — a hypothesis about the regulatory aim a set of bills shares. The 6 vectors are an analytic lens, not a fact of any statute. They were drawn by reading each bill's text and mechanism, and a bill may sit in more than one. They are argued for, and revisable.

1. 01 Frontier Model & Systemic Risk. Competing frameworks target the developers of the largest AI models — mandating safety frameworks, incident reporting to the Attorney General, and civil penalties for noncompliance. Includes creation of ILCompute, a public cloud computing resource.
2. 02 Algorithmic Discrimination & Consumer Civil Rights. Extends anti-discrimination protections beyond employment into housing, credit, and public accommodations. Bans surveillance-based dynamic pricing and algorithmic wage discrimination.
3. 03 Transparency, Provenance & Disclosure. Mandates digital watermarking on all AI-generated media, professional disclosure requirements, strict synthetic content labels in political advertising, and consumer notification when interacting with AI systems.
4. 04 Companion AI & Minor Protection. First-of-its-kind regulation of emotionally adaptive AI companions. Requires crisis intervention protocols, persistent machine-disclosure, parental consent for minors, and suicide/self-harm detection.
5. 05 Data Privacy, Neuro-Data & Model Training. Institutes default opt-out for AI model training on user data. Creates comprehensive data broker registry. Extends privacy protections to neural and biometric data from consumer devices.
6. 06 Public Sector & Human-in-the-Loop. Prohibits public agencies from deploying automated decision systems without meaningful human review. Bans AI in teacher evaluations. Creates state AI governance task force and frameworks for state procurement of AI.

This is a public record, and public records improve by being checked. If a figure looks wrong, a status is stale, or a source has moved, report a correction. The dataset and the code that renders it are open at GitHub.