AIRON Thematic Groups bring together professionals working across research support to deepen their understanding of the responsible, ethical and effective use of artificial intelligence within different areas of research operations.

Each group provides an educational forum where participants can:

• share knowledge and experiences
• discuss case studies and emerging developments
• explore the opportunities, challenges and governance of AI
• exchange ideas and good practice
• contribute to informed discussion and collective learning

Through these groups, AIRON encourages knowledge sharing, peer learning and informed understanding, helping research professionals navigate the evolving role of AI across the research and innovation ecosystem.

Thematic Groups Leadership

The AIRON Thematic Groups are led by Jeff Warner, who supports the development of AIRON’s educational community by encouraging collaboration, shared learning and the exchange of knowledge across research support disciplines.

Research Management & Research Culture

This group focuses on the people, structures, and practices that enable excellent research environments and effective research support.

The group explores how AI can help strengthen research management practice while supporting positive organisational change and responsible innovation.

Focus areas

• research management workflows and professional practice
• organisational change and AI adoption
• skills development and capability building
• researcher development and support
• inclusive and responsible research culture.

 Pre-Award & Post-Award

This group explores how AI can support the research funding lifecycle — from funding discovery and proposal development through to project delivery and reporting.

Members share practical experiences of using AI tools to streamline processes, support researchers, and improve efficiency in research administration.

Focus areas

• funding discovery and call analysis
• proposal development and grant writing support
• costing, approvals, and institutional workflows
• award acceptance and project setup
• post-award delivery, reporting, and compliance.

Contracts, Governance, Ethics, IP & Technology Transfer

This group focuses on responsible research governance, legal frameworks, and the translation of research into innovation and societal impact.

Members explore how AI may influence research governance, intellectual property management, and technology transfer processes.

Focus areas

• research contracts and collaboration agreements
• legal review, negotiation, and compliance
• research governance and policy development
• research ethics, integrity, and responsible AI
• intellectual property management and protection
• technology transfer and research commercialisation
• industry collaboration and innovation partnerships
• knowledge exchange and pathways to impact.

Research Data, Intelligence & Assessment

This group focuses on research information systems, analytics, and data-driven decision-making in research organisations.

Members explore how AI can support research intelligence, institutional analytics, and research evaluation while maintaining transparency, fairness, and responsible data governance.

Focus areas

• research information systems and institutional data
• research analytics, dashboards, and reporting
• research assessment and evaluation
• data governance, quality, and bias mitigation
• AI-enabled institutional intelligence workflows.

Library & Scholarly Communication

This group explores how AI is beginning to influence scholarly communication, knowledge discovery, and research information management.

Members discuss emerging tools and practices that support access to knowledge and responsible stewardship of research outputs.

Focus areas

• literature discovery and synthesis
• repositories, metadata, and persistent identifiers
• open access and scholarly publishing workflows
• research data management and stewardship
• knowledge management and digital library services.