“This workshop will be useful to me going forward because I understood what I should ask myself when using AI, and how I can use it effectively as a tool for improvement.”
Anna🇮🇹 Italy
RGAIC
Competences for Responsible Generative AI Use at Work.
The RGAIC framework captures the competences employees need to use Generative AI knowledgeably, effectively, adaptively, socially appropriately, and ethically at work. It brings five interrelated dimensions together in a higher-order framework.
CognitiveFunctionalSocialMetaEthical
Ongoing research
Extending RGAIC into field and intervention settings.
Ongoing work is extending RGAIC through field and intervention studies examining how competences for responsible GenAI use develop and operate in practice.
Participant reflections
What participants took away.
Reflections following the Responsible GenAI Competences mini-workshop in the X-Culture Coaching Program.
“Moving forward, I will verify AI outputs, be transparent about its use, and rely on my own judgment rather than depending entirely on AI.”
Maxwell🇬🇭 Ghana
“I now see AI not as a shortcut, but as a tool that requires responsibility and ethical awareness.”
Raheem🇺🇸 United States
“Before the mini-workshop, I mostly thought about AI as a productivity tool. Now I see it as a powerful system that requires informed and reflective use.”
Giulia🇮🇹 Italy
“Moving forward, I feel more prepared to guide students responsibly.”
Nicole🇹🇼 Taiwan
“I will use AI as a support tool for structure and ideas, but always review and validate the output carefully.”
Johnny🇮🇹 Italy
“I want to think about AI, not simply use it.”
Amelia🇳🇱 Netherlands
“I will use GenAI as a tool for support while ensuring I critically evaluate the output and follow institutional guidelines.”
Aishani🇦🇺 Australia
“I’ll make sure I actually review and take responsibility for anything I use AI for, instead of just trusting it straight away.”
Jingwen🇦🇺 Australia
“I will always check the accuracy of what the AI writes and change the tone to make sure it feels personal and helpful for the students.”
Francesco🇮🇹 Italy
“AI will only become more common in our world, and we must learn how to use these tools to our advantage in addition to our own intelligence.”
Anabel🇺🇸 United States
“This workshop was very informative. It made me think about how I use these tools, where I make mistakes and how I can improve.”
Claudia🇮🇹 Italy
“I found the Friend Method especially valuable, and I will definitely apply it when using GenAI in both professional and personal contexts.”
Ema🇷🇸 Serbia
“I will strive to use AI selectively, carefully verify information, and ensure that what I create maintains its value and integrity.”
Mai🇹🇼 Taiwan
“This workshop will be useful to me going forward because I understood what I should ask myself when using AI, and how I can use it effectively as a tool for improvement.”
Anna🇮🇹 Italy
“Moving forward, I will verify AI outputs, be transparent about its use, and rely on my own judgment rather than depending entirely on AI.”
Maxwell🇬🇭 Ghana
“I now see AI not as a shortcut, but as a tool that requires responsibility and ethical awareness.”
Raheem🇺🇸 United States
“Before the mini-workshop, I mostly thought about AI as a productivity tool. Now I see it as a powerful system that requires informed and reflective use.”
Giulia🇮🇹 Italy
“Moving forward, I feel more prepared to guide students responsibly.”
Nicole🇹🇼 Taiwan
“I will use AI as a support tool for structure and ideas, but always review and validate the output carefully.”
Johnny🇮🇹 Italy
“I want to think about AI, not simply use it.”
Amelia🇳🇱 Netherlands
“I will use GenAI as a tool for support while ensuring I critically evaluate the output and follow institutional guidelines.”
Aishani🇦🇺 Australia
“I’ll make sure I actually review and take responsibility for anything I use AI for, instead of just trusting it straight away.”
Jingwen🇦🇺 Australia
“I will always check the accuracy of what the AI writes and change the tone to make sure it feels personal and helpful for the students.”
Francesco🇮🇹 Italy
“AI will only become more common in our world, and we must learn how to use these tools to our advantage in addition to our own intelligence.”
Anabel🇺🇸 United States
“This workshop was very informative. It made me think about how I use these tools, where I make mistakes and how I can improve.”
Claudia🇮🇹 Italy
“I found the Friend Method especially valuable, and I will definitely apply it when using GenAI in both professional and personal contexts.”
Ema🇷🇸 Serbia
“I will strive to use AI selectively, carefully verify information, and ensure that what I create maintains its value and integrity.”
Mai🇹🇼 Taiwan
Know more
Framework, validation, and evidence.
Open the sections below for the conceptual and methodological details behind RGAIC.
01Five dimensionsWhat the framework measures
Cognitive
Understanding how GenAI works, what shapes output quality, and where its strengths, limitations, and reliability boundaries lie.
Functional
Applying GenAI to task goals through effective prompting, iteration, problem solving, ideation, and purposeful use.
Social
Navigating AI-mediated communication with relational awareness, interpersonal appropriateness, and sensitivity to broader consequences.
Meta
Learning, reflecting, experimenting, and adapting as tools, practices, and interaction strategies continue to evolve.
Ethical
Recognizing and responding to ethical, legal, fairness, privacy, misinformation, and policy-related implications of GenAI use.
02Validation programmeHow the framework was developed
Theory & item generationHolistic competence frameworks and responsible GenAI literature.
Expert face validationAcademic and practitioner review; item pool refined.
Content validationFormal tests of definitional correspondence and distinctiveness.
Exploratory structureFive-factor structure examined with working professionals.
Confirmatory validationHigher-order structure benchmarked against alternatives.
Nomological networkTwo-wave field study linking GenAI training, RGAIC, and engagement.
03Evidence & citationWhat the research establishes
What the evidence establishes
A distinct, higher-order employee competence framework.
Across the development programme, RGAIC is empirically distinguishable from AI literacy and general professional competence and explains variance in GenAI-enabled job engagement beyond both. Detailed psychometric evidence is reported in the manuscript.
Singh, D. P., Shirish, A., Gonzalez-Gomez, H., & Taghavi, S. (2026). Employee Competences for Responsible Generative AI Use at Work: A Personal Resource Perspective. Academy of Management Proceedings, 2026(1).
https://doi.org/10.5465/amproc.2026.12056abstract ↗
The full scale-development manuscript is currently being revised for a first-round resubmission to the Human Resource Management Journal as part of its special issue on robust scale development for HRM research.
The RGAIC research programme is developed with Anuragini Shirish, Helena Gonzalez-Gomez, and Shiva Taghavi. Questions about research access: contact@dhruvpratapsingh.org.