AI Now Institute · Oct 26, 2026
Kate Brennan argues A.I. rules should focus on corporate negligence
Markdown · JSON · Original source
Kate Brennan, who leads the policy agenda on A.I. and corporate power at the AI Now Institute, argues that government should focus on corporate negligence and stop harmful products from entering the market. She says A.I. companies’ spending on technology creates pressure to deploy it broadly, including in public institutions and contracts where it may not be fit for purpose or secure. Brennan cites a Bain estimate that, by 2031, companies would need $6 trillion in annual revenue to sustain their current level of capital expenditure, which she says is $1.5 trillion a year. She argues that products causing significant harm, including injury, death or cybersecurity attacks, could be subject to strict liability, whether or not a company knew or should have known of the danger. This excerpt presents Brennan’s perspective; it does not include the full panel’s views. How would lawmakers define significant harm and apply strict liability to A.I. products?
Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.
Original source
AI Now Institute · Article
Source details
Original source date: Oct 26, 2026 (2026-10-26T17:49:25+00:00).
Date basis: Date stated by the publisher.
Added to Escape Meridian: 2026-10-29T15:18:04.453Z. First observed: 2026-10-26T18:07:04.790Z. Retrieved: 2026-10-29T15:17:19.198Z.
Referenced by
Recorded citations and public file attachments. A reference alone does not establish agreement or influence.
No public references recorded here yet.
Limits
The evidence is an excerpt featuring Brennan; it does not include the full roundtable or other experts’ views. The revenue and capital expenditure figures are attributed to Bain’s estimate, not presented as observed outcomes. The excerpt does not specify how lawmakers would define significant harm or apply strict liability to AI products.
Open question
How would lawmakers define significant harm and apply strict liability to A.I. products?
Source-stated
Kate Brennan leads the policy agenda on AI and corporate power at the AI Now Institute.
Kate Brennan, a former Google tech worker, leads the policy agenda on A.I. and corporate power at the AI Now Institute
Source-stated
Brennan says AI companies’ spending on development creates pressure to deploy the technology broadly, including in public institutions and contracts where it may not be fit for purpose or secure.
they need to push this tech everywhere, into all of our public institutions and contracting, including in areas where A.I. is not fit for purpose, is not secure
Source-stated
Brennan cites a Bain estimate that companies would need $6 trillion in annual revenue by 2031 to sustain capital expenditure of $1.5 trillion a year.
Bain estimates that by 2031, they will have to achieve $6 trillion of revenue annually to sustain their current level of capital expenditure, which is $1.5 trillion a year.
Source-stated
Brennan says products causing significant harm could be subject to strict liability, whether or not the company knew or should have known of the danger.
if your product causes significant harm, whether that’s injury to people, death, cybersecurity attacks, then you could be held strictly liable — meaning whether or not you knew or should have known the danger.
Source and contributor context
AI Now Institute · Article author
These are credits stated by the source; they do not establish a profile match or authorship of every passage.
Source media
No suitable media was found by the supported page extraction.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Capital expenditure
Money a company spends on long-lasting assets such as buildings, chips and power equipment.
Kate Brennan
Kate Brennan is an AI Now Institute researcher and coauthor of its 2025 report on power and policy in AI.
AI Now Institute
AI Now Institute studies the power and institutions shaping AI and advocates for public accountability.
Editorial provenance
Version 1. Publication ID: 224de0e2-a7cd-410e-879e-b8608223bf86.
Prepared by gpt-6-luna; grounding review by gpt-6-luna.
Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T15:18:04.453Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: useful_perspective.
Observation: a8b0ea449089801c17160d868540452fb25a5720a21b4c43ae4bc674abe92101. Source text hash: 50469c432545f7db9f96515cf0bf6a9e487571a7f127fe71030d5bf7737c5e83.
Revision and source-check history
Version 1 · 2026-10-29T15:18:04.453Z
Kate Brennan argues A.I. rules should focus on corporate negligence
Kate Brennan, who leads the policy agenda on A.I. and corporate power at the AI Now Institute, argues that government should focus on corporate negligence and stop harmful products from entering the market. She says A.I. companies’ spending on technology creates pressure to deploy it broadly, including in public institutions and contracts where it may not be fit for purpose or secure. Brennan cites a Bain estimate that, by 2031, companies would need $6 trillion in annual revenue to sustain their current level of capital expenditure, which she says is $1.5 trillion a year. She argues that products causing significant harm, including injury, death or cybersecurity attacks, could be subject to strict liability, whether or not a company knew or should have known of the danger. This excerpt presents Brennan’s perspective; it does not include the full panel’s views. How would lawmakers define significant harm and apply strict liability to A.I. products?
Original source
AI Now Institute · Article
Source details
Original source date: Oct 26, 2026 (2026-10-26T17:49:25+00:00).
Date basis: Date stated by the publisher.
Added to Escape Meridian: 2026-10-29T15:18:04.453Z. First observed: 2026-10-26T18:07:04.790Z. Retrieved: 2026-10-29T15:17:19.198Z.
Limits
The evidence is an excerpt featuring Brennan; it does not include the full roundtable or other experts’ views. The revenue and capital expenditure figures are attributed to Bain’s estimate, not presented as observed outcomes. The excerpt does not specify how lawmakers would define significant harm or apply strict liability to AI products.
Open question
How would lawmakers define significant harm and apply strict liability to A.I. products?
Source-stated
Kate Brennan leads the policy agenda on AI and corporate power at the AI Now Institute.
Kate Brennan, a former Google tech worker, leads the policy agenda on A.I. and corporate power at the AI Now Institute
Source-stated
Brennan says AI companies’ spending on development creates pressure to deploy the technology broadly, including in public institutions and contracts where it may not be fit for purpose or secure.
they need to push this tech everywhere, into all of our public institutions and contracting, including in areas where A.I. is not fit for purpose, is not secure
Source-stated
Brennan cites a Bain estimate that companies would need $6 trillion in annual revenue by 2031 to sustain capital expenditure of $1.5 trillion a year.
Bain estimates that by 2031, they will have to achieve $6 trillion of revenue annually to sustain their current level of capital expenditure, which is $1.5 trillion a year.
Source-stated
Brennan says products causing significant harm could be subject to strict liability, whether or not the company knew or should have known of the danger.
if your product causes significant harm, whether that’s injury to people, death, cybersecurity attacks, then you could be held strictly liable — meaning whether or not you knew or should have known the danger.
Source and contributor context
AI Now Institute · Article author
These are credits stated by the source; they do not establish a profile match or authorship of every passage.
Source media
No suitable media was found by the supported page extraction.
Terms and references
Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.
Capital expenditure
Money a company spends on long-lasting assets such as buildings, chips and power equipment.
Kate Brennan
Kate Brennan is an AI Now Institute researcher and coauthor of its 2025 report on power and policy in AI.
AI Now Institute
AI Now Institute studies the power and institutions shaping AI and advocates for public accountability.
Editorial provenance
Version 1. Publication ID: 224de0e2-a7cd-410e-879e-b8608223bf86.
Prepared by gpt-6-luna; grounding review by gpt-6-luna.
Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T15:18:04.453Z. This checks fidelity to the source, not whether its claims are independently true.
Editorial selection: accept; reasons: useful_perspective.
Observation: a8b0ea449089801c17160d868540452fb25a5720a21b4c43ae4bc674abe92101. Source text hash: 50469c432545f7db9f96515cf0bf6a9e487571a7f127fe71030d5bf7737c5e83.
passed · 2026-10-29T15:18:04.453Z · anthropic/claude-opus-5.5
Publication: 224de0e2-a7cd-410e-879e-b8608223bf86
attribution — pass: The views are correctly attributed to Kate Brennan, and her role at the AI Now Institute matches the source. The Bain figures are presented as a Bain estimate that Brennan cites, not as the publisher's or reviewer's own claim.
Kate Brennan, a former Google tech worker, leads the policy agenda on A.I. and corporate power at the AI Now Institute
summary — pass: The title, summary and question accurately reflect Brennan's argument: deployment pressure from spending, a focus on corporate negligence, and strict liability. Strict liability is explained in plain language, and the summary notes this is one panelist's view. The question follows from what the evidence leaves unresolved. Repeating the question at the end of the summary is a style matter only.
The issue here is corporate negligence. That should be the focus.
date — pass: The originalPublished value of 2026-10-26 comes from the publisher page and matches the feed entry. The draft adds no conflicting date claims. The evidence does not show an earlier first publication of this page.
support — pass: Each claim is directly supported by verbatim source text. The draft keeps the revenue and spending figures as a cited estimate and frames strict liability as something that could apply, preserving the source's conditional wording. It adds no unsupported benefits or costs.
then you could be held strictly liable — meaning whether or not you knew or should have known the danger
media — pass: The selected media is the verified direct link to the original AI Now Institute page. This is the most direct way for readers to reach the actual source.
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