Can AI Fire You? California’s No Robo Bosses Act Explained
California has passed a law restricting employers from relying on automated systems alone to discipline or fire employees. Known as the No Robo Bosses Act, Senate Bill 947 was signed on September 30, 2026. Its requirements become operative on July 1, 2027 (Office of Governor Gavin Newsom, 2026; S.B. 947, 2026).
For employees, the central issue is who checks an automated recommendation before it affects their job. For employers, it is whether the review process actually examines the evidence behind that recommendation.
As of October 26, 2026, the new requirements are not yet operative. This article explains the main provisions and practical questions employers can address while preparing.
What Is California’s No Robo Bosses Act?
SB 947 adds rules for automated decision systems, or ADS, to the California Labor Code.
The definition extends beyond generative AI. It covers qualifying computational processes using machine learning, statistical modeling, data analytics, or AI to produce outputs that assist or replace human judgment and materially affect people. Certain ordinary tools, including calculators, databases, and spam filters, are excluded (S.B. 947, 2026, § 1520).
For a workplace review, start with what the system does. A product’s marketing label alone will not explain whether its features or use fall within the law.
What Changes for Discipline and Termination?
The central restriction is straightforward: covered employers cannot base a disciplinary or termination decision solely on an ADS.
When an employer primarily relies on automated output, a human must corroborate the decision. The statute permits review of the data collected or used to produce that output, or other relevant supporting information. Examples include managerial evaluations, personnel records, work product, peer reviews, and witness interviews.
If the output cannot be corroborated, or the reviewer concludes it is inaccurate, incomplete, or misleading, the employer cannot use it for that decision (S.B. 947, 2026, § 1522; Zheliabovskii, 2026).
The practical distinction is between approving a recommendation and examining whether it is supported.
What Information Will Affected Employees Receive?
When an employer primarily relies on an ADS for discipline or termination, the law requires a separate, plain-language written notice when the employee is informed of the decision.
The notice must explain the reliance on automation, confirm human review and corroboration, provide a human contact and information about the employee’s data-description right, and explain the prohibition on retaliation.
The employee can request a meaningful, objective description of their own data used by the system. That is a data-description right, rather than a promise of access to the vendor’s source code (S.B. 947, 2026, §§ 1522–1524; Zheliabovskii, 2026).
For employers preparing their process, the notice and the underlying review need to tell the same story.
Who Should Review the Law’s Scope?
This is a California law, not a nationwide prohibition on AI at work. Its employer definition includes private employers and specified public entities.
The statute contains conditional exceptions involving qualifying collective bargaining agreements and certain federally required aviation or national-security-related operations. Coverage should be checked against the final text with employment counsel (S.B. 947, 2026, §§ 1520, 1526.5–1526.6).
Its discipline and termination provisions should not be presented as a general ban on AI-assisted hiring. Nor should the July 2027 start date be treated as permission to disregard other applicable employment protections in the meantime.
What Meaningful Review Could Look Like
Consider a hypothetical customer-support team. An automated dashboard recommends a warning because an employee’s resolution time exceeds a target.
Before accepting the recommendation, a reviewer examines the underlying tickets, checks the time calculation, and looks at whether the assigned cases match the type of work the target measures.
The reviewer discovers that the dashboard included time when cases were waiting for another department. That finding gives the team a concrete reason to question the recommendation and investigate how the measure was calculated.
This is an illustrative review exercise, not a reported incident or a complete compliance procedure.
The useful question is: could the reviewer explain what they checked, what they found, and why the evidence supports or undermines the proposed action?
A checkbox saying “manager approved” provides little insight into those questions on its own.
What Employers Can Prepare Now
Use the preparation period to trace one real decision process from start to finish. The following are practical planning suggestions.
Identify the outputs people rely on. Ask managers which dashboards, alerts, rankings, or recommendations influence their decisions. Record the enabled features and how the output is used.
Test whether reviewers can examine the evidence. Can they access the underlying records? Do they understand what the score measures? Can they identify missing or inaccurate information? Ask vendors for explanations where the answers are unclear.
Assign responsibility for review and follow-up. Decide who investigates questionable output, who resolves missing information, and who communicates with the employee. Avoid leaving ownership implicit between HR, managers, and the vendor.
Prepare employee communications with counsel. Review the notice requirements, data-description requests, and applicable exceptions together. A generic statement that the organization uses AI is not a substitute for understanding the requirements triggered by a particular decision.
These steps give the team a process to examine and improve. They do not guarantee compliance or establish that a tool is fair.
Why This Matters for Workplace Inclusion
At Diversity.com, fair opportunity includes how people are evaluated after they join an organization.
An automated score can appear precise while leaving important questions unanswered: which work counted, whether the records were accurate, and whether the reviewer understood the employee’s actual responsibilities.
Human review is valuable when it addresses those questions. It should not be assumed to eliminate bias simply because a person participates.
That is the inclusion relevance of this development: employees’ opportunities and livelihoods deserve decisions grounded in explainable evidence, with clear responsibility for examining the technology involved.
Final Thoughts
California’s No Robo Bosses Act gives employers a concrete reason to examine how automated recommendations become workplace decisions.
Start with one process. Identify the output, the evidence available to reviewers, and the person responsible for investigating concerns. Use that review to prepare for the law’s requirements with appropriate legal guidance.
If your team also uses automation earlier in the employment process, explore Diversity.com’s free AI Hiring Tool Review Guide. It offers questions about hiring-tool evidence, accessibility, and limitations. Its focus is candidate screening; it is not an SB 947 compliance checklist.
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Frequently Asked Questions
When does California’s No Robo Bosses Act start applying?
Its provisions become operative on July 1, 2027. Signing the law in September 2026 did not make those requirements immediately operative (S.B. 947, 2026, § 1526.7).
Does the law ban all AI in employment?
No. It regulates specified uses of automated decision systems, including reliance on them for discipline and termination. It should not be described as a blanket ban on AI workplace tools (S.B. 947, 2026).
Is a manager’s approval enough?
A sign-off alone does not demonstrate the required corroboration when an employer primarily relies on automated output. The review must examine supporting information, and unusable output cannot become the basis for the decision (S.B. 947, 2026, § 1522; Zheliabovskii, 2026).
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Sources & References
Office of Governor Gavin Newsom. (2026, September 30). California’s nation-leading AI framework just got stronger, Governor Newsom signs more first-in-the-nation worker protections and more. https://www.gov.ca.gov/2026/09/30/californias-nation-leading-ai-framework-just-got-stronger-governor-newsom-signs-more-first-in-the-nation-worker-protections-and-more/
S.B. 947, ch. 859, 2026 Cal. Stat. (2026). Employment: Automated decision systems [Chaptered September 30, 2026; adding California Labor Code §§ 1520–1526.7]. Chaptered text reproduced by LegiScan: https://legiscan.com/CA/text/SB947/id/3461122. Official legislative record: https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB947.
Zheliabovskii, R. (2026, October 5). Newsom signs revamped ‘No Robo Bosses Act’ into law. SHRM. https://www.shrm.org/topics-tools/employment-law-compliance/newsom-signs-revamped-no-robo-bosses-act-into-law
