AI-Enabled Analytics for Marketing Strategy MGT5502
- Academic Session: 2026-27
- School: Adam Smith Business School
- Credits: 10
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: No
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
The course is designed to equip students with strategic insight into how artificial intelligence is transforming marketing practice. Through theory, real-world case studies, and hands-on experimentation with AI tools, students will develop critical thinking, ethical awareness, and practical skills to assess, implement, and improve AI-driven marketing strategies. Emphasis is placed on not just using AI-but challenging it, refining it, and aligning it with strategic goals - reflection-driven.
Timetable
5 x 2 hour lectures
3 x 2 hour tutorials
Requirements of Entry
Students must be registered on one of the associated programmes listed in this course specification.
Excluded Courses
None
Co-requisites
None
Assessment
1. Report; Individual; 1700 words; 100%, ILOs 1-4.
Course Aims
This course aims to:
■ Develop students' understanding of how AI-enabled analytics support data-driven decision-making in contemporary marketing contexts, examining how such systems influence strategic choices and marketing performance.
■ Equip students with the analytical and evaluative capabilities required to interpret, apply, and critically assess AI-enabled analytical approaches, including consideration of ethical, governance, and societal implications in technology-mediated marketing decision contexts.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
1. Explain and critically examine the role of AI-enabled analytics in contemporary marketing strategy, including how such systems support data-driven decision-making and strategic performance.
2. Interpret and evaluate customer, market, and performance data generated through AI-enabled analytical systems in order to assess their implications for marketing strategy.
3. Apply and synthesise AI-enabled analytical approaches to marketing scenarios, integrating data, analytical outputs, and strategic frameworks to justify marketing decisions.
4. Critically evaluate the effectiveness, limitations, and risks of AI-enabled analytics in marketing, including ethical, governance, and societal considerations associated with their use.