Community colleges: personnel: qualifications.

Senator Cervantes frames a measure that ties staffing at California's community colleges to the system’s established minimum qualifications, requiring the instructor of record and a broad roster of personnel to meet those standards and to align with the position-specific qualifications already in the Education Code, while explicitly allowing the use of artificial intelligence tools in college operations and student services.

The amended framework directs that the instructor of record for a course must meet the minimum qualifications for teaching credit or noncredit instruction, and that a range of positions—including librarians, counselors, student personnel workers, supervisors, administrators, chief administrative officers, EOPS workers, DSPS workers, apprenticeship instructors, and supervisors of health—must be filled only by individuals who satisfy the minimum qualifications for their position under the relevant qualification provisions, or the corresponding qualifications for that role under the established framework. The bill preserves an explicit allowance for using AI tools in operations or services.

The measure does not introduce new enforcement mechanisms but relies on existing regulatory and hiring processes within the California Community Colleges to verify compliance with the prescribed qualification standards. It does not specify an explicit effective date or transition timeline and does not provide funding or appropriations to implement the changes. Ambiguities noted in the accompanying analysis include how credential-based grandfather rights and “alternative qualifications” interact with the new requirements and how transition steps would be phased in.

For implementation, districts would need to inventory affected positions, map current qualifications to the established standards, and adjust recruiting, job classifications, and records to document compliance. Personnel and HR staff may need to review credentials, update postings, and plan staff development where gaps exist, all while respecting the retained allowance for AI usage in day-to-day operations. The policy context centers on formalizing alignment between staffing in listed roles and the state’s predefined qualification framework.