Advancing responsible AI adoption across the global research ecosystem.

AIRON Expert Groups bring together practitioners, innovators, and thought leaders from across the research community. These groups develop shared frameworks, guidance, and resources that help institutions adopt AI responsibly, effectively, and in alignment with research integrity and operational excellence.

Each Expert Group reflects a core domain of research operations and includes specialists who are contributing expertise to AIRON’s mission.

Funding & Awards

This group examines how AI can strengthen the full funding lifecycle — from identifying opportunities to developing competitive proposals, negotiating contracts, and managing awards. It focuses on practical, responsible applications that improve efficiency and support research excellence.

Focus Areas

• Funding discovery and eligibility checks
• Pre-award strategy and grant development
• Proposal writing and narrative intelligence
• Contracts, legal review, and compliance
• Post-award management and financial forecasting
• Research project management and workflow automation.

 Research Information & Data Systems

This group focuses on the systems, data infrastructure, and digital workflows that underpin modern research operations. It addresses how AI can improve information management, metadata, analytics, open research intelligence, and data governance.

Focus Areas

• Research information management systems and dashboards
• Libraries, metadata, and knowledge management
• Literature analysis, synthesis, and repository automation
• Data governance, security, and bias mitigation
• Institutional AI workflows and local LLM development
• Policy intelligence and open science compliance.

Research Governance, Ethics & Responsible AI

This group leads AIRON’s work on creating ethical, transparent, and fair approaches to AI adoption. It develops governance frameworks, risk models, and policy guidance to ensure AI supports — rather than threatens — research integrity, accountability, and equity.

Focus Areas

• Responsible AI governance and policy
• Ethical risk assessment and mitigations
• Transparency, accountability, and fairness
• Equity, diversity, and inclusion in AI adoption
• Policy development and regulatory trends.

People, Skills & Culture

This group looks at the cultural and human aspects of AI adoption — including workforce readiness, capability development, change management, and evolving professional roles in research operations.

Focus Areas

• AI readiness and organizational change
• Workforce development and micro-credentialing
• AI-enabled learning and training frameworks
• Staff engagement and adoption behaviors
• Professional competencies for the AI-enabled workforce.

Innovation, Impact & Partnerships

This group explores how AI can accelerate innovation, enhance research impact, and strengthen partnerships across academia, industry, and funding organizations. The group focuses on real-world value creation and collaborative models.

Focus Areas

• Innovation scouting and commercialization pathways
• IP management and technology transfer
• Research impact tracking and engagement analytics
• Partnerships with funders, industry, and technology providers
• Collaborative development of responsible AI tools and practices.