Module manager: Professor Mark Stuart
Email: m.a.stuart@lubs.leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
This module is not approved as an Elective
This module offers students a comprehensive and intellectually rich journey through the past, present, and emerging future of artificial intelligence as a transformative force in business, work, and society. Rather than treating AI as a purely technical phenomenon, the module situates it within long‑term patterns of technological change, strategic decision‑making, and socio‑economic evolution. Students explore how AI is reshaping organisational practices, labour markets, and global competitiveness, while also grappling with the ethical, regulatory, and human‑centred challenges that accompany rapid digital transformation. At its core, the module equips students with the analytical tools to understand why AI is being adopted, how it is being implemented, and what its consequences are likely to be for different stakeholders. It blends historical analysis, theoretical frameworks, empirical research, international comparisons, and real‑world case studies. For students interested in business strategy, public policy, organisational change, or the future of work, this module provides a powerful foundation for navigating one of the most consequential technological shifts of the 21st century.
This module examines the adoption of AI and advanced digital technologies. Students will be equipped with an understanding of what it means to develop an organisational strategy for the adoption of responsible AI. The module will consider historical perspectives, key drivers and motivations for the adoption of AI technologies within organisations, with consideration of the potential benefits and challenges across a range of sectors and countries.
On successful completion of the module students will be able to:
1. Critically interpret empirical evidence on digital adoption using surveys, international datasets, and case study material.
2. Evaluate the strategic choices made by firms in adopting AI technologies and the consequences for work, productivity, and organisational practices.
3. Synthesise theoretical and empirical insights to form reasoned arguments about the societal and organisational impacts of AI.
4. Assess the strengths and limitations of different regulatory and governance approaches to managing AI‑related risks and harms.
On successful completion of the module students will be able to:
Academic Skills
1. Critical Thinking: Apply cognitive skills of critical thinking, analysis and synthesis
Enterprise Skills
2. Applying Commercial, Ethical, Sustainable, Digital and Inter-Disciplinary Literacies: Developing and applying a breadth of knowledge to assess the consequences and impact of ideas, opportunities and actions
Technical Skills
3. Business Model Appreciation: Assess the implications of different business models of AI adoption, including contemporary policy debates surrounding digital skills, AI governance, and regulatory frameworks.
Work Ready Skills
4. Communication: Communicate effectively both orally and in writing
5. Creativity: The ability to generate ideas, demonstrate originality and imaginative thinking, and think beyond expected or accepted ideas.
This module covers the historical development of artificial intelligence and examines how innovation, institutions, and strategic choices have shaped its evolution. Students will study the key drivers of AI adoption within firms and assess how these trends influence global patterns of digital adoption. The module includes corporate case studies that illustrate technological disruption in practice, alongside applied perspectives on how AI is implemented across different sectors. It also explores the skills and capability building needed for effective AI use, as well as the policy approaches that support organisational and national readiness. Further topics include the regulation and governance of AI, with an emphasis on responsible adoption and participatory design to ensure ethical and inclusive development and deployment.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Workshop | 10 | 2 | 20 |
| Private study hours | 130 | ||
| Total Contact hours | 20 | ||
| Total hours (100hr per 10 credits) | 150 | ||
The seminars will be utilised to provide a formative feedback opportunity to the students. Students will work on real-world case studies, and wherever relevant, data sets will be provided to students to practice issue-mapping, use of analytical tools and solution development. Students will be provided feedback on feasibility, prioritisation, and alignment of options/recommended solutions with the case context. Storyboard drafts and ‘tell in 60 seconds’ pitch exercises will be used to provide feedback on messaging, clarity, sequencing, clarity and coherence.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Case Study | 3000- words Case study (challenge-based) coursework focused on Business strategy and AI adoption | 100 |
| Total percentage (Assessment Coursework) | 100 | |
The resit for this module will be 100% by 3,000-word coursework (either an alternative case study or a different set of case review questions will be provided).
Check the module area in Minerva for your reading list
Last updated: 13/05/2026
Errors, omissions, failed links etc should be notified to the Catalogue Team