Bridging R&D and Innovation Management through AI-Augmented Organizational Memory
You’ve been personally invited to the interview stage of this study. Everything you need is on this page — the study in brief, your informed consent, and a way to book a time that suits you. It takes about three minutes.
- One interview · about 90 minutes
- Includes a short S4IL demo
- Voluntary · withdraw anytime
- Anonymised · GDPR & PDPL
Participant profile. This study is open to anyone who has held — or currently holds — a role in R&D, Innovation, or Knowledge Management within the past 5 years, in a Saudi Arabian RDI organisation. Exposure to three or more innovation or R&D projects (past or present) is the only other prerequisite.
Why this research matters
Saudi Arabia’s Vision 2030 places Research, Development and Innovation at the heart of the Kingdom’s transition to a knowledge-based economy. Yet practitioners inside RDI organizations consistently report the same friction: ideas and insights generated on the R&D side rarely translate into the innovation pipeline on the commercial side. Organizational memory — the tacit and explicit knowledge accumulated across projects, people, and partnerships — is fragmented, under-documented, and lost in transition.
This study investigates whether AI-Augmented Organizational Memory can act as a structural bridge between R&D outputs and Innovation Management decision-making, and whether a measurable framework — the Return on Innovation Investment (ROI²) — can make that bridge visible to decision-makers.
The framework in brief
What taking part involves
A single conversation of about 90 minutes, by video call or in person, including a short demonstration of the S4IL research prototype. Participation is entirely voluntary and there is no financial compensation — but every participant receives a complimentary copy of the forthcoming book The Innovator’s Compass, and an acknowledgement in the thesis unless you prefer to remain anonymous.
Ethics, consent & data protection
This study has received formal ethics clearance from the Research Ethics Committee of Universidad Católica San Antonio de Murcia (UCAM). Student ID: ON901L2411A07 · Supervisor: Dr. Vimala Sanjeevkumar. Your data is processed in compliance with the EU GDPR and Saudi Arabia’s Personal Data Protection Law (PDPL). You may withdraw at any stage before the thesis is submitted for defence; on withdrawal, your data is deleted within 30 days. Interview transcripts are stored on encrypted infrastructure, accessible only to the researcher and his supervisor, and names of individuals and organisations are pseudonymised in all published outputs.
The full Participant Information Sheet and the 27-question Interview Protocol are sent to you by email — in English and Arabic — once your interview is confirmed, keeping them off the open web. This is an independent academic study: it is not commissioned, funded, or directed by any employer or client, including the researcher’s current employer.
Your consent is recorded — now pick a time
Choose a 90-minute slot that suits you below. If none of the times work, propose another or email research@yrp.me and we’ll arrange one.
Researcher: Yann Rousselot-Pailley · UCAM (via Exeed College) · Supervisor: Dr. Vimala Sanjeevkumar. You may request access to, correction of, or deletion of your data at any time at research@yrp.me.