The Enterprise AI Compliance Workflow for U.S. State AI Regulations in 2026

The intake form, screening guide, vendor checklist, and documentation workflow every enterprise AI project now runs through

On Thursday, I ran a live session called What New U.S. AI Regulations Mean for Enterprise Adoption in 2026. It covered four things.

First, the four regulations reshaping enterprise AI in 2026:

• The June 2nd federal executive order on frontier model pre-release review.

• State-level frontier AI laws, led by California TFAIA and New York RAISE.

• State-level automated decision-making laws, led by California ADMT, Colorado SB 26-189, and Texas TRAIGA.

• Federal procurement guidance from the White House Office of Management and Budget.

Second, why enterprise AI adoption is no longer a software-access problem. The review functions your company already runs still apply, but each one now has to evaluate categories of exposure that traditional enterprise procurement was never designed to handle.

Third, the four Adoption Gates every AI project now clears before deployment: vendor selection, use-case screening, monitoring, and documentation.

Fourth, three practical steps to prepare: build a use-case intake before you build any pilot, ask vendors for evidence instead of assurances, and reduce your company’s dependency on any single AI vendor’s release schedule.

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📌 A quick note before we start. My paid subscription price is going up at the end of day July 31st from $5/month or $50/year to $10/month or $100/year. If you upgrade before then, or if you’re already a paid subscriber, you’ll stay at the current price for as long as your subscription remains active.

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What this piece gives you

The live gave you the framework. This piece gives you the workflow.

By the end, you’ll have six artifacts your team can install this week:

• A one-page use-case intake form.

• A screening guide that maps every AI project to the specific state laws that apply to it, across the seven U.S. states with active or upcoming AI regulations.

• A vendor evidence checklist covering eleven categories of documentation your legal team should require before any AI vendor evaluation begins.

• A monitoring log schema your data engineer can implement without additional infrastructure.

• A documentation template designed to survive a regulatory audit.

• A build order that shows your team how to put all five into place, in the sequence that saves the most rework.