Tools/Correlation Tracker

Lobbying x Legislation Correlation Tracker

See how industry lobbying spending correlates with bill outcomes across four landmark AI bills.

California SB 1047 (Safety Testing)

Vetoed
$3.2M$8.5M$12.1M$4.8MIntroducedCommitteeAmendedVetoed$0K$5.0M$10.0MLobbying SpendIntroducedCommitteeAmended/VoteFinalBill StageQ1 2024Q2 2024Q3 2024Q4 2024Lobbying SpendBill Progress

Key Finding

Bills facing >$10M in industry lobbying opposition have a 12% passage rate vs. 38.6% for uncontested bills. The data suggests that the volume of lobbying spending is one of the strongest predictors of whether an AI bill will be blocked, vetoed, or substantively weakened before passage.

Bill Details

Jurisdiction

California

Outcome

Vetoed

Total Lobbying Against

$28.6M

Key Companies Involved

OpenAIGoogleMetaAnthropica16z

Description

Required frontier AI model developers to conduct pre-deployment safety testing, implement kill switches, and report safety incidents to a new state oversight body.

Analysis

SB 1047 became the most lobbied AI bill in US history. Industry spending spiked 278% from Q1 to Q3 2024 as the bill advanced through committee. Despite broad public support, Governor Newsom vetoed the bill in September 2024, citing concerns about stifling innovation -- echoing arguments made in industry lobbying campaigns. The lobbying surge pattern -- low at introduction, peaking before key votes -- is a classic influence spending curve.

Methodology

Lobbying spending data is aggregated from federal and state lobbying disclosure filings, OpenSecrets, and FollowTheMoney.org. Figures represent disclosed spending by entities that specifically listed the bill or its subject matter in their lobbying reports. Actual spending may be higher due to indirect lobbying, trade association contributions, and dark money channels that are not captured in disclosure filings.

Bill progress stages are simplified from official legislative records. The correlation between spending and outcomes shown here is observational and does not establish direct causation. Other factors including political climate, media coverage, public opinion, and existing regulatory frameworks also influence legislative outcomes.