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Reskilling the U.S. Military Workforce for the Agentic AI Era: A Framework for Educational Transformation

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Title: Reskilling the U.S. Military Workforce for the Agentic AI Era: A Framework for Educational Transformation
Language: English
Authors: Satyadhar Joshi (ORCID 0009-0002-6011-5080)
Source: Online Submission. 2025.
Peer Reviewed: N
Page Count: 13
Publication Date: 2025
Document Type: Reports - Research
Descriptors: Job Skills, Skill Development, Job Training, Military Personnel, Military Training, Artificial Intelligence, Labor Force Development, Technology Integration, Educational Change, Electronic Learning, Predictor Variables, Resource Allocation, Models, Curriculum Development, Career Readiness, Ethics, Governance
Abstract: The rapid emergence of agentic artificial intelligence (AI) systems represents a paradigm shift in military operations, demanding fundamental transformation of US military education. This paper presents a comprehensive framework for reskilling and redesigning military education to address critical workforce readiness gaps in the era of autonomous AI systems. Utilizing a mixed-methods review of defense reports, case studies, and quantitative workforce data, this paper develops a comprehensive framework for reskilling the defense force to address critical readiness gaps in the era of autonomous AI. Through analysis of current AI adoption trends, quantitative workforce assessments, and educational limitations, we identify that only 10-15% of military personnel feel adequately trained for agentic AI integration despite significant investments exceeding $600-900 million in next-generation AI capabilities. Our proposed solution features a multi-tiered educational architecture with progressive competency levels, a continuous curriculum development pipeline, and layered technology integration. The framework addresses identified skills gaps through foundational AI literacy for all personnel, operational competence for mid-career leaders, and strategic AI leadership development. Implementation strategies include phased rollout over 24-36 months, multi-stakeholder engagement models, and comprehensive assessment mechanisms. Findings demonstrate that successful agentic AI integration requires not only technical upskilling but also fundamental changes in pedagogical approaches, institutional culture, and resource allocation--with optimal distribution of 30-40% to technology infrastructure, 20-25% to faculty development, 15-20% to curriculum design, and program evaluation. This research provides actionable recommendations for military education institutions to prepare personnel for human-AI teaming, autonomous system oversight, and ethical AI application in complex operational environments. decrease medical as well as financial burden, hence improving the management of cirrhotic patients. These predictors, however, need further work to validate reliability. All results and proposals are from cited literature.
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED677111
Database: ERIC
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  Availability: 0
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  Data: Reskilling the U.S. Military Workforce for the Agentic AI Era: A Framework for Educational Transformation
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  Data: <searchLink fieldCode="AR" term="%22Satyadhar+Joshi%22">Satyadhar Joshi</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0002-6011-5080">0009-0002-6011-5080</externalLink>)
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  Data: 13
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  Data: <searchLink fieldCode="DE" term="%22Job+Skills%22">Job Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Skill+Development%22">Skill Development</searchLink><br /><searchLink fieldCode="DE" term="%22Job+Training%22">Job Training</searchLink><br /><searchLink fieldCode="DE" term="%22Military+Personnel%22">Military Personnel</searchLink><br /><searchLink fieldCode="DE" term="%22Military+Training%22">Military Training</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+Force+Development%22">Labor Force Development</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Change%22">Educational Change</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+Allocation%22">Resource Allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum+Development%22">Curriculum Development</searchLink><br /><searchLink fieldCode="DE" term="%22Career+Readiness%22">Career Readiness</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Governance%22">Governance</searchLink>
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  Data: The rapid emergence of agentic artificial intelligence (AI) systems represents a paradigm shift in military operations, demanding fundamental transformation of US military education. This paper presents a comprehensive framework for reskilling and redesigning military education to address critical workforce readiness gaps in the era of autonomous AI systems. Utilizing a mixed-methods review of defense reports, case studies, and quantitative workforce data, this paper develops a comprehensive framework for reskilling the defense force to address critical readiness gaps in the era of autonomous AI. Through analysis of current AI adoption trends, quantitative workforce assessments, and educational limitations, we identify that only 10-15% of military personnel feel adequately trained for agentic AI integration despite significant investments exceeding $600-900 million in next-generation AI capabilities. Our proposed solution features a multi-tiered educational architecture with progressive competency levels, a continuous curriculum development pipeline, and layered technology integration. The framework addresses identified skills gaps through foundational AI literacy for all personnel, operational competence for mid-career leaders, and strategic AI leadership development. Implementation strategies include phased rollout over 24-36 months, multi-stakeholder engagement models, and comprehensive assessment mechanisms. Findings demonstrate that successful agentic AI integration requires not only technical upskilling but also fundamental changes in pedagogical approaches, institutional culture, and resource allocation--with optimal distribution of 30-40% to technology infrastructure, 20-25% to faculty development, 15-20% to curriculum design, and program evaluation. This research provides actionable recommendations for military education institutions to prepare personnel for human-AI teaming, autonomous system oversight, and ethical AI application in complex operational environments. decrease medical as well as financial burden, hence improving the management of cirrhotic patients. These predictors, however, need further work to validate reliability. All results and proposals are from cited literature.
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    Languages:
      – Text: English
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      Pagination:
        PageCount: 13
    Subjects:
      – SubjectFull: Job Skills
        Type: general
      – SubjectFull: Skill Development
        Type: general
      – SubjectFull: Job Training
        Type: general
      – SubjectFull: Military Personnel
        Type: general
      – SubjectFull: Military Training
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      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Labor Force Development
        Type: general
      – SubjectFull: Technology Integration
        Type: general
      – SubjectFull: Educational Change
        Type: general
      – SubjectFull: Electronic Learning
        Type: general
      – SubjectFull: Predictor Variables
        Type: general
      – SubjectFull: Resource Allocation
        Type: general
      – SubjectFull: Models
        Type: general
      – SubjectFull: Curriculum Development
        Type: general
      – SubjectFull: Career Readiness
        Type: general
      – SubjectFull: Ethics
        Type: general
      – SubjectFull: Governance
        Type: general
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      – TitleFull: Reskilling the U.S. Military Workforce for the Agentic AI Era: A Framework for Educational Transformation
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            NameFull: Satyadhar Joshi
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              Type: published
              Y: 2025
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            – TitleFull: Online Submission
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