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AI Literacy & Automation Readiness - Methodology Handbook
07/18/2026
2607186431567

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Operating manual for an organizational AI-literacy and automation-readiness diagnostic. It defines three literacy layers (individual, team, organizational), five Bloom-mapped maturity levels, and five weighted scoring vectors, including conceptual understanding, opportunity-spotting, frequency and depth, tool breadth, and trust and risk awareness. It specifies question types, a universal open-text rubric with graded example answers, role-relative expected profiles for engineers, product managers, operations managers, and executives, and a worked end-to-end aggregation from individual to team to organization, including research-referenced benchmarking and an Impact×Feasibility opportunity-ranking model.

Technical
ai literacy
diagnostic methodology
assessment framework
ai maturity model
automation readiness
ai governance
benchmarking

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Oscar Valenzuela
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2607186431550
AI Literacy & Automation Readiness — Methodology Handbook (v0.3)
07/18/2026
Oscar Valenzuela
Operating manual for an organizational AI-literacy and automation-readiness diagnostic. It defines three literacy layers (individual, team, organizational), five Bloom-mapped maturity levels, and five weighted scoring vectors, including conceptual understanding, opportunity-spotting, frequency and depth, tool breadth, and trust and risk awareness. It specifies question types, a universal open-text rubric with graded example answers, role-relative expected profiles for engineers, product managers, operations managers, and executives, and a worked end-to-end aggregation from individual to team to organization, including research-referenced benchmarking and an Impact×Feasibility opportunity-ranking model.
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Title AI Literacy & Automation Readiness - Methodology Handbook
Operating manual for an organizational AI-literacy and automation-readiness diagnostic. It defines three literacy layers (individual, team, organizational), five Bloom-mapped maturity levels, and five weighted scoring vectors, including conceptual understanding, opportunity-spotting, frequency and depth, tool breadth, and trust and risk awareness. It specifies question types, a universal open-text rubric with graded example answers, role-relative expected profiles for engineers, product managers, operations managers, and executives, and a worked end-to-end aggregation from individual to team to organization, including research-referenced benchmarking and an Impact×Feasibility opportunity-ranking model.
Work type Technical
Tags ai literacy, diagnostic methodology, assessment framework, ai maturity model, automation readiness, ai governance, benchmarking

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Identifier 2607186431567
Entry date Jul 18, 2026, 7:51 PM UTC
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Author. Holder Oscar Valenzuela. Date Jul 18, 2026.


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