BESE committee discusses AI literacy, index and cross‑sector alignment ahead of legislative season
January 09, 2026 | State Board of Elementary and Secondary Education (BESE), Boards & Commissions, Organizations, Executive, Louisiana
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Committee chairs and members used the meeting’s latter portion to update deliverables intended to prepare the board for the upcoming legislative session and district implementation.
Chairs outlined five core deliverables: define AI literacy and K–12 competencies; develop an AI index to track preparedness, exposure and proficiency; align K–12 with higher education and workforce partners; establish procurement and safe‑use guidance; and identify workforce pathways and feedback loops from industry to education.
Vanessa (committee lead on the AI index) described a matrix intended to minimize new district reporting while producing objective, verifiable evidence: categories for students, teachers and districts measured at three levels (preparedness, exposure, proficiency) and a short list of administratively reportable indicators (e.g., presence of an AI lead, district-level AI policy, number of teachers completing AI PD or microcredentials). She said the group intends the evidence to be optional initially and to leverage existing data structures.
Committee members emphasized local control and the importance of not adding instructional burden. Several members proposed a continuing, statutorily backed coordinating body or a governor‑led MOU like California’s AI workforce board to sustain cross-sector work and attract private and federal support.
Why it matters: The board intends to convert consensus work into legislative and administrative proposals ahead of a February meeting; committee members repeatedly noted that having a clear cost estimate for scaled PD and a visible organizational chart of cross-sector partners would strengthen legislative outreach and federal grant applications.
Next steps listed in the meeting included producing a visual org chart to show connectivity among K–12, higher ed and industry, refining the AI index evidence list, and preparing a February deliverable package the board can present to legislators and the governor’s office.
Chairs outlined five core deliverables: define AI literacy and K–12 competencies; develop an AI index to track preparedness, exposure and proficiency; align K–12 with higher education and workforce partners; establish procurement and safe‑use guidance; and identify workforce pathways and feedback loops from industry to education.
Vanessa (committee lead on the AI index) described a matrix intended to minimize new district reporting while producing objective, verifiable evidence: categories for students, teachers and districts measured at three levels (preparedness, exposure, proficiency) and a short list of administratively reportable indicators (e.g., presence of an AI lead, district-level AI policy, number of teachers completing AI PD or microcredentials). She said the group intends the evidence to be optional initially and to leverage existing data structures.
Committee members emphasized local control and the importance of not adding instructional burden. Several members proposed a continuing, statutorily backed coordinating body or a governor‑led MOU like California’s AI workforce board to sustain cross-sector work and attract private and federal support.
Why it matters: The board intends to convert consensus work into legislative and administrative proposals ahead of a February meeting; committee members repeatedly noted that having a clear cost estimate for scaled PD and a visible organizational chart of cross-sector partners would strengthen legislative outreach and federal grant applications.
Next steps listed in the meeting included producing a visual org chart to show connectivity among K–12, higher ed and industry, refining the AI index evidence list, and preparing a February deliverable package the board can present to legislators and the governor’s office.
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