A Socio-Technical Framework for Scaling and De-Risking Enterprise AI
Explore how enterprises can overcome the common pitfalls of AI pilot projects and embed AI widely across functions. Identify strategic, operational, and behavioral enablers to manage AI scaling risks and deliver measurable business value.
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Project Description
Project Overview
This project explores the challenges of scaling Generative AI across enterprises, focusing on the gap between successful pilots and full enterprise integration. It addresses the socio-technical factors causing scaling failures and aims to develop a framework for systematic de-risking at strategic, operational, and tactical levels, ensuring sustainable AI adoption.
What You Will Do
You will employ a mixed methods research design combining Socio-Technical Systems Theory and Organisational Information Processing Theory. The project will involve case studies with industry partners, analysis of organisational processes, and exploration of AI scaling enablers and governance mechanisms across varied enterprise contexts.
Expected Outcomes
The research will produce insight into effective risk orchestration for AI scaling, identify dynamic configurations enabling enterprise-wide AI infusion, and create roadmaps for responsible, sustainable, and scalable AI deployment in industry.
Why This Matters
With over 80% of AI initiatives failing to deliver impact due to socio-technical misalignment, this project addresses critical risks and systemic vulnerabilities in AI adoption. Its findings will help organisations realise durable value from AI, reduce compliance and reputational risks, and secure long-term enterprise viability.
Entry Requirements
How to Apply
Eligibility
Supervisor Profile
Dr Fatima Gillani is a researcher focusing on the intersection of artificial intelligence and organizational systems, with an emphasis on how socio-technical dynamics influence AI adoption and scaling in business contexts. Her work employs mixed-methods approaches to address challenges in enterprise technology integration and governance.