Convenor
Convenor's affiliation
Arash Hajikhani
Henry Lopez Vega, Daniele Rotolo, Tatjana Titareva
Co-convenors
LUT University
Abstract
Note: The session follows a Professional Development Workshop (PDW) format and does not require a paper submission. Details on how to participate in the PDW will be provided after 2nd February.
This interactive hands-on workshop invites scholars and practitioners in R&D management to explore how artificial intelligence can be responsibly and effectively embedded in research and innovation practices. Going beyond traditional presentations, participants will engage directly with AI tools for writing, data analysis, and validation—developing both critical awareness and practical literacy in AI-assisted research. The session builds on extensive experience in organizing similar workshops for scholars, including the AI4STIP1 initiative at the University of Manchester, which has trained researchers in the responsible use of AI for science, technology, and innovation policy.
Participants will experiment with accessible tools, engage in light coding exercises, and discuss evolving research methods and best practices for AI adoption in R&D contexts.
Description
Artificial Intelligence (AI) is rapidly reshaping how we conduct, communicate, and validate research in R&D and innovation management. From automating literature reviews and generating research ideas to analyzing complex datasets and validating outputs, AI tools increasingly act as both research assistants and epistemic partners. However, despite growing interest, many researchers and practitioners lack opportunities to experiment hands-on with these tools and reflect on their responsible use.
This workshop responds to this emerging need by providing a structured yet exploratory session for participants to learn by doing. Building on the AI4STIP (AI for Science, Technology, and Innovation Policy) training program hosted at the University of Manchester, the workshop adapts that proven model into a focused, compact format tailored for R&D Management Conference participants. Over 90 minutes (or a half-day, if scheduling allows), attendees will engage with practical exercises that demonstrate AI’s potential and pitfalls in research workflows.
The session will be organized around three experiential modules:
1. AI for Academic Writing and Idea Generation – Participants will test AI-assisted literature synthesis and research framing tools, reflecting on transparency and authorship ethics as well as the tools limitations and challenges.
2. AI for Data Analysis and Visualization – A guided exploration of generative and analytical AI platforms for quantitative and qualitative data interpretation, including light coding exercises.
3. AI for Validation and Responsible Use – A discussion and live demo on evaluating and auditing AI results for robustness, bias, and reproducibility.
The workshop emphasizes responsible and reflexive practice—encouraging critical engagement with AI outputs rather than blind adoption. It aims to create a shared learning environment where both academics and practitioners can exchange insights, test methods, and co-develop good practices for AI integration in R&D management.
Given the increasing number of R&D management studies employing AI-based methods (with over 50 recent publications in 2024–25 alone), this workshop offers a timely and valuable contribution to the conference theme, “Creativity and resilience in an era of technological disruption.” It also aligns with the conference’s mission to bridge research and practice, offering attendees not just discussion, but skills and literacy they can immediately apply in their work.
Participants are encouraged to bring laptops and curiosity—no advanced coding skills are required. The organizers will provide guided materials, live demos, and space for open dialogue about the evolving future of AI in R&D research and management.