Module overview
This module explores human-machine collaboration, AI-driven augmentation, and robotics applications in business. It covers automation, intelligent systems, and adaptive interfaces that enhance productivity. Topics like robotic process automation (RPA), AI-powered decision support, and wearable technology are included. Ethical considerations, workforce adaptation, and the impact on employment trends are analysed. Real-world case studies in healthcare, manufacturing, and retail illustrate how robotics and augmentation optimize efficiency, innovation, and user experience. Practical hands-on exposure to robotics frameworks and AI integration tools are emphasized.
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Effectively communicate complex AI and management concepts, research findings, and strategic solutions to a variety of stakeholders.
- Demonstrate practices that are ethical, responsible and sustainable.
- Demonstrate proficiency in the use of AI tools and technologies for data analysis, aiding in the strategic decision-making process across various business contexts.
- Demonstrate how new technologies, including AI, can shape businesses and societies. Classify AI technologies, evaluate solutions and redesign processes and business models to utilize them. Reflect on how AI can support people and processes in an organisation.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Use computing and IT resources effectively.
- Evaluate and select AI solutions for complex problems by distinguishing the real value from the hype.
- Use library and other resources, including the application of bibliographical skills.
- Demonstrate effective project management skills, including the ability to plan, execute, and manage both time and resources in AI-driven projects, ensuring successful outcomes.
- Employ digital literacy skills, particularly in utilizing AI technologies and data analysis tools, to drive decision-making and innovation in business practices.
- Adapt to and manage change at an increasingly faster rate, a vital skill in the rapidly evolving field of AI and management.
- Utilize critical thinking and AI-enhanced problem-solving skills across diverse business scenarios, preparing you to address and resolve challenges swiftly and efficiently.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- The ethical, social, and economic implications of AI deployment in business, emphasizing responsible management and decision-making.
- The role and impact of AI in modern business practices, including its integration into business models and operations.
- How AI technologies can drive innovation and efficiency across various sectors, enhancing business strategies and competitive advantage.
- The analytical techniques necessary for AI-driven decision making enable effective strategy and problem-solving in complex business environments.
Syllabus
The exact topics covered in this module will depend on the configuration of the team of tutors and their respective research areas within strategy and innovation management. The module may include, but is not limited to, the following topics:
•Understanding human-machine collaboration: Evaluate AI-driven automation, wearable technology, and robotics for enhancing business operations.
•Integrating robotics in business: Develop practical skills in applying robotic process automation (RPA) and augmentation tools to optimize workflows.
•Analysing ethical and workforce Implications: Assess how automation impacts employment trends, ethical concerns, and workforce adaptation.
•Industry applications and case Studies: Examine real-world examples in healthcare, manufacturing, and retail to understand robotics' role in innovation.
•Hands-on exposure to AI and robotics tools: Gain practical experience with AI frameworks for implementing human-machine collaboration effectively
Learning and Teaching
Teaching and learning methods
Teaching methods include:
Lectures, interactive case studies, simulation game, directed reading, and private/guided study.
Learning activities include:
• Introductory lectures
• Group work: presentation
• Case study/problem-solving activities
• Private study: argumentative essay
• Use of video and online materials
Class activities, such as problem-solving activities, discussions and use of case studies, will provide opportunities for you to gain feedback from your tutor and/or peers about their level of understanding and knowledge before any formal summative assessment.
| Type | Hours |
|---|---|
| Seminar | 10 |
| Lecture | 24 |
| Independent Study | 116 |
| Total study time | 150 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Assignment | 70% |
| Group Case Study | 30% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Individual report | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Individual report | 100% |