module specification

The business world is currently undergoing profound technological change. Digitalisation has reached new heights and new technologies are helping tackle ever more tasks that are complex. This trend is driven in particular by the availability of large quantities of data – big data (BD) – and by the improved opportunities for using this data through artificial intelligence (AI). The relevance of BDAI is growing as technology, companies, and consumers interact. First, current technological progress facilitates the extensive and practical use of BDAI. Second, companies are increasingly relying on data and the value they extract from it to optimise their business models and processes. Third, consumer behaviour is increasingly shaped by digital applications, which in turn boosts the generation and availability of data. As such this module focuses on the relevance and management of BDAI in business context. This module also focuses on how to lead successful BDAI initiatives by prioritizing the right opportunities, building a diverse team, shaping the strategies and strategic experiments and continuously managing business solutions to benefit the organizations as a whole.

n/a

• Introduction to Big Data and AI LO1, LO2
• AI and BD in organisational context LO1, LO2
• AI influence on competitiveness and market LO1, LO2
• Decision making and BDAI LO1, LO2
• Problem solving - Understand if a problem can be solved and how do you solve the problem LO1, LO2
• Challenges of AI and BD - The disruptive power of Digital Transformation LO1, LO2
• Developing an enterprise strategy LO1, LO2
• Ethics, Law and GDPR LO1, LO2
• AI in practice LO1, LO2

Delivery of the module will consist of Lecture /Seminars. Students will be encouraged to research BDAI management issues from a variety of sources in addition to module materials including newspapers, textbooks and on-line sources to identify aspects relevant to their areas of study.

Workshops will provide the opportunity for the whole class to come together and to interact with the lecturer who will provide the basic BDAI management theories and present a set of examples and real-world cases.

On successful completion of the module, students will be able to:

LO1. Evaluate managing success factors of BDAI and the implementation of the strategies for the use of BDAI in the business context.
LO2. Apply the assessment of the opportunities as well as risks of an increased use of big data and artificial intelligence within the business context.

The assessment strategy is based on complete transparency between staff and students on the basis on which academic judgements are made. Briefings at the beginning of the module, assignment brief and feedback sheet will include the grading schedule, which contains detailed descriptors on how student achievement of specified learning outcomes translates into grades.

Students will receive formative feedback together with summative feedback at designated points. Formative feedback will be provided consistently. Students will be offered the opportunity to discuss the formative feedback in class. This helps prepare students for the first summative assignment.

Ongoing in-class and in-person feedback together with the structured summative assignment feedback sheets provide multiple opportunities for students to develop an understanding of the subject and the necessary skills to demonstrate good academic practice. The students will be able to demonstrate the extent to which they have achieved the intended learning outcomes.

Textbooks:

Core Text:

Wodecki, A. (2018) Artificial Intelligence in Value Creation: Improving Competitive Advantage. Switzerland: Palgrave McMillan.

Yao, M., Jia, M. and Zhou, A. (2018) Applied Artificial Intelligence: A Handbook For
Business Leaders. USA: Topbots.

Other Texts:

Davenport, T. (2018) The AI Advantage: How to Put the Artificial Intelligence Revolution
to Work (Management on the Cutting Edge). Cambridge: MIT.

Donald, M. (2019) Leading and Managing Change in the Age of Disruption and Artificial Intelligence. UK: Emerald.

Kampakis, S. (2018) The Decision Maker’s Handbook to Data Science: A guide for non-technical executives, managers and founders. USA: Creative Common.

King, K. (2019) Using Artificial Intelligence in Marketing: How to Harness AI and Maintain the Competitive Edge. UK: Kogan Page.

Marr, B. (2016) Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results. UK: Wiley.

Tegmark, M. (2018) Life 3.0: Being Human in the Age of Artificial Intelligence. UK: Penguine.

Journals:

Journal of Management Information Systems (JMIS)
European Journal of Information Systems (EJIS)
Information and Management
Management Information Systems Quarterly (MIS Quarterly)
Journal of Strategic Information Systems
International Journal of Information Management (IJIM)
Journal of Information Technology (JIT)
Journal of Information Science
Behaviour & Information Technology
Information Systems Journal
Journal of Knowledge Management
Knowledge management Research and Practice
Harvard Business Review
Websites: Digital Marketing Institute/ Digital Leadership Institute

Electronic Databases: to be provided in class/Weblearn

Social Media Source: to be provided in class/Weblearn