Module manager: Chunyu Xiu and Su Jung Jee
Email: C.Xiu@leeds.ac.uk and S.Jee@leeds.ac.uk
Taught: 1 Jun to 30 Sep View Timetable
Year running 2026/27
| LUBS5317M | Dissertation in Artificial Intelligence for Business |
This module is not approved as an Elective
The aim of this module is for students to undertake an applied project working with a client organisation/external agencies/research centres to plan, negotiate, research and deliver a defined project. Projects will be offered and students selected on a competitive basis. Dependent on the nature of the project, students will work with either the People, Work and Employment Department or the Analytics, Operations and Technology Department. Analytics, Technology and Operations Department (ATOD) Applied Project: The opportunities for applied projects offered by ATOD will focus on the impact of Artificial Intelligence for tackling grand challenges in business and society. Students will produce a topical, independent report underpinned by either collaborative work with ATOD colleagues researching cutting edge aspects of AI or a bespoke project based within an organisation or other stakeholder under the guidance of industry experts and academic tutors. Projects will be practical or theoretical, and in line with LUBS’ purpose, having the potential to make a real impact on the economy, society or the planet. People Work and Employment (PWE) Applied Project: The project applied offered by PWE will involve engagement with key stakeholders across global universities, businesses, government and civil society, through Digital Futures at Work research centre (DIGIT) co-labs. Projects will be imagined, scoped and developed in partnership between PWE and these stakeholders, to provide opportunities for students to work on 'live' projects related to AI and work. Some projects will offer students opportunities to undertake primary research on areas including sustainable/ethical AI and digital adoption, and will cover a range of different sectors of the labour market and civil society. Other projects will allow students to undertake secondary analysis, including analysis of the Employers Digital Practices at Work Survey, a unique longitudinal survey, funded and commissioned by the DIGIT centre.
All applied projects will involve the gathering and analysis of primary data and/or secondary data on a contemporary artificial intelligence issue. The range of issues covered in projects will be aligned to the taught contents of the programme and students will also acquire considerable insight into broader management issues when they negotiate with the project brief, operationalise their research strategy or discuss findings with stakeholders. Under faculty supervision, individual students will apply the mix of theoretical skills and applied techniques on the MSc. to a 'live' relevant issue.
On successful completion of the module students will be able to:
ALO 1 Utilise the conceptual and applied thinking obtained from the programme and apply it to a project related to AI for Business.
ALO 2 Acquire, critically analyse and present conceptual and empirical material derived from primary and/or secondary sources using appropriate academic rigour
ALO 3 Specifically evaluate the appropriateness and impact of AI for the chosen applied domain
ALO 4 Implement an appropriate project design under the guidance and supervision of a faculty supervisor and one of a range of external stakeholders.
On successful completion of the module students will be able to:
SLO 1. Academic skills:
Independent learning: students will take ownership of their project, managing their time and resources as they navigate real world challenges, fostering self-directed learning.
Written communication skill: students will produce a professional project report, refining their ability to communicate complex theoretical ideas and technical detail clearly and effectively.
Verbal communication skills: regular meetings with organisational stakeholders and academic supervisors will provide opportunities to practise and enhance effective personal communication
Critical thinking: tackling real-world issues and applying theoretical frameworks will require students to analyse information, evaluate options and make informed decisions.
SLO 2. Technical and Digital:
The likely focus of the project on AI will enable the student to develop understanding of relevant digital and technical solutions.
SLO 3. Work-readiness and professionalism:
Negotiation: students negotiate project scope deliverables and timelines with stakeholders and supervisors.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Supervision | 5 | 1 | 5 |
| Lecture | 4 | 2.5 | 10 |
| Private study hours | 435 | ||
| Total Contact hours | 15 | ||
| Total hours (100hr per 10 credits) | 450 | ||
Students' progress will be monitored through regular meetings with their supervisor. These meetings will each have a milestone and actions will be noted, minuted and recorded. Students will be encouraged to submit a 3,000 word piece of work (unassessed) by June, to receive formative feedback on their writing.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Project | 10,000 word project report | 85 |
| Reflective log | 2,000 word individual reflective progress log | 15 |
| Total percentage (Assessment Coursework) | 100 | |
The resit for this module will be 100% by 10,000 word project report.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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