Educational infrastructure forresponsible AI adoption
Nexus Institute for AI Learning (NIAIL) develops and disseminates competency frameworks, measurement systems, and implementation models that help community colleges, universities, and workforce organizations across the United States build the capability for effective, responsible, safe, and sustainable AI strategy and implementation.
Nonprofit research and implementation organization · OhioAI adoption is outpacing educational infrastructure
Artificial intelligence is reshaping work, education, and organizational practice. Yet the systems needed to prepare people to adopt AI effectively, safely, responsibly, and sustainably have not developed at the same pace. Competency definitions remain fragmented across higher-education and workforce contexts and across occupational domains, measurement is uneven, and institutions often lack practical models for translating AI strategy into curriculum, assessment, and educator practice. Nexus Institute exists to help close that gap.
The AI Education and Workforce Readiness Initiative
Five interconnected systems, developed as a single body of work to define, develop, evaluate, and implement AI competencies, build pathways for developing them, measure their attainment, support institutional implementation, and govern how AI is integrated into learning systems.
AI Competency Frameworks and Standards
Defines the knowledge, skills, dispositions, and responsible practices learners and workers need for effective, safe, responsible, and sustainable AI adoption — across STEM and non-STEM fields and occupations alike.
Competency-Based Learning, Assessment, Professional Development, and Credentialing Systems
Translates defined competencies into structured learning experiences, authentic assessment, professional development, and credentialing pathways designed for adaptation across institutional contexts.
Assessment and Measurement Systems
The Generic AI Competency (GAIC) Scale is being developed and psychometrically validated to measure whether AI competency is actually developing, not simply whether a course was completed.
Validation underwayGlobal AI Education and Workforce Readiness Implementation Framework (GAEWRIF)
Examines the organizational capability required to implement, coordinate, and continuously improve AI competency development across educational institutions and workforce organizations, including leadership, governance, educator development, competency-based learning and assessment, technological infrastructure, stakeholder engagement, quality assurance, and continuous organizational learning. The framework also examines an Instructional Translation Layer through which institutional capability is connected to curriculum alignment, authentic assessment, and educator practice.
In active developmentHuman–AI Instructional Design Operating System (IDOS)
An enterprise operating framework, introduced in The Learning Operating System, for designing, producing, and continuously improving the Institute's AI-assisted instructional materials under continuous human oversight and review.
Generic AI Competency (GAIC) Scale
A discipline-agnostic measure of applied AI competency across cognitive–metacognitive and technomoral–affective dimensions, designed to work across STEM and non-STEM disciplines rather than within a single field.
Research → Implementation
Nexus connects evidence generation with institutional application. We develop, measure, test, refine, and disseminate educational infrastructure rather than treating research and implementation as separate activities.
AI Learning Communities for Adult Learners
NIAIL is developing a community-based application of the AI Education and Workforce Readiness Initiative for adult learners, initially in Appalachian Ohio. These AI Learning Communities are intended to provide sustained, contextually relevant opportunities for adults to develop and apply AI competencies in community and workforce settings.
Community organizations, libraries, workforce-development organizations, and other appropriate local partners may serve as implementation partners as the approach is developed and evaluated.
The initial Appalachian application is intended to provide an authentic setting for evaluating and refining the approach before adaptation to other educational, community, and workforce contexts.
Research program
Evidence before broader implementation. The Initiative is built on a continuous evidence-generation cycle, not a one-time release.
AI competency measurement
Developing and validating instruments, including the GAIC Scale, that measure AI competency across educational and workforce contexts.
Competency-based learning & credentialing
Studying how competency frameworks translate into learning, assessment, credentialing, and workforce preparation, including a national labor-market study mapping employer demand for AI competencies.
Institutional AI capability
Studying how organizations translate AI strategy into curriculum, governance, educator practice, and sustainable implementation, through GAEWRIF and related scholarship.
Each phase comprises multiple stages — ten in total across the full lifecycle — moving from initial needs analysis through institutional implementation and adaptation across diverse institutional contexts, with evidence from later stages continuously informing earlier ones.
Publications & Research
Generic AI Competency (GAIC) Scale
Psychometric development and validation of a discipline-agnostic AI competency instrument.
Validation underwayMapping Employer Demand for AI Competencies
National labor-market research across STEM and non-STEM occupations assessing the workforce relevance of the GAIC Scale.
Research underwayAI Governance in Higher Education
A conceptual manuscript examining how colleges and universities connect formal AI policy to demonstrated institutional capability.
Under peer reviewGlobal AI Education and Workforce Readiness Implementation Framework (GAEWRIF)
Implementation-science research and framework development on institutional AI readiness.
In active developmentThe Learning Operating System
Book-length framework introducing IDOS, coordinating disciplined Human–AI collaboration across the instructional design lifecycle.
Published · Version 1.0AI Competency Development and Policy-Capability Gaps
A two-part cross-sector qualitative study examining AI competency development and institutional/organizational capability gaps across community college, university, and workforce settings.
In progress · IRB-FY27-158Research funding
- Student Enhancement Award, GAIC Scale — Ohio University (2026) — $5,994
- Patton College of Education Research Grant, GAIC Scale — Ohio University (2026) — $1,000
- Centre for International Studies Research Grant, AI Policy Research — Ohio University (2022) — $1,650
- Centre for International Studies Research Grant, AI Policy Research — Ohio University (2021) — $2,000
Start where the challenge is greatest.
Nexus Institute for AI is beginning its implementation work in underserved and Appalachian communities in Ohio, developing and testing educational infrastructure for the conditions in which AI adoption can be most difficult. Evidence generated in these contexts can then inform adaptation across broader institutional and workforce settings. Ohio is not the limit of the mission — it is the starting point.
Who we serve
Nexus Institute for AI develops tools for organizations responsible for preparing people to learn, work, and participate effectively in an AI-enabled society.
About Nexus
Nexus Institute for AI Learning, or NIAIL, is an independent nonprofit research and implementation organization focused on the educational infrastructure required for responsible AI adoption.
Founder
NIAIL was founded by Joshua Osondu, a Ph.D. Candidate in Innovative Learning Design and Technology at Ohio University. His research focuses on AI competency, educational measurement, instructional systems design, implementation science, and AI governance.
Platform
The Institute provides an organizational platform for continuing this work beyond any single research project, institution, or appointment — developing, evaluating, and disseminating these tools for use across the field.
Build with us.
We welcome conversations with institutions, workforce organizations, researchers, libraries, funders, and implementation partners interested in advancing responsible AI education and workforce readiness.