Module manager: Nathalie Benesova
Email: N.H.Benesova@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
This module is not approved as a discovery module
AI is shaping the way businesses operate and has significantly disrupted some industries and professions. As a result, employer requirements for skills and knowledge across different areas of business are evolving. Traditional career pathways are being challenged, and both employers and employees must adapt to these changes. Such adaptability is crucial for future career success. To navigate this landscape, you will need to develop awareness, knowledge, and skills tailored to different organisational settings, job roles, and industries. While this may seem complex, there are effective ways to accelerate your development in these areas. Through immersive and experiential learning approaches, this module will support you in building your AI readiness. The module focuses on preparing you for key stages of the job search process, including internships, placements, graduate roles, and interviews, as well as developing your ability to engage in broader business practices and conversations around AI. As part of the module, you will also have the opportunity to earn a digital badge to demonstrate your AI-related experience and skills.
AI for Business Practice has been designed in collaboration with industry partners to develop awareness, knowledge, and skills for the effective use of AI across organisations, roles, and sectors commonly entered by business and management graduates, including those undertaking internships or a year in industry. To achieve this, the module is structured around the application of AI within key thematic areas, ranging from strategy, sustainability, and ethics to higher-level conceptual thinking about AI. This approach will enable you to critically assess the direction of future AI developments. While this is not a technical module, you will gain practical experience in using a range of AI tools effectively, equipping you to add value to future employers.
The module is guided by the following objectives:
1. Building awareness of AI in business - Awareness is the foundation of understanding. You will develop an understanding of AI and its role across different organisational functions, processes, and industries. This will enable you to engage with the complexities of AI, achieve the broader aims of the module, and discuss AI in an informed and balanced manner, including in professional contexts such as job interviews.
2. Practising AI-related and AI-enabled solutions - Organisations require practical solutions, and while AI offers significant opportunities, it also introduces challenges. By addressing real-world problems from a variety of organisational and industry contexts, you will learn to identify where AI creates value, recognise potential risks, and design AI-enabled solutions to business problems.
3. Critically evaluating the impacts of AI - The impact of AI varies across contexts. In some cases, it can address complex challenges and deliver significant efficiencies; in others, it may produce short-term gains while creating longer-term issues. You will develop the ability to evaluate AI-enabled solutions critically, considering both their benefits and limitations, and to identify ways to mitigate associated risks.
4. Developing skills for AI work readiness - The module emphasises transferable skills. You will develop practical AI-related competencies, including prompt engineering, alongside the ability to use AI tools in an ethical, sustainable, and professionally appropriate manner. These capabilities are increasingly expected by employers.
The module adopts an immersive, experiential learning approach, emphasising learning by doing. It consists of five learning units, each delivered over two weeks. The first week introduces key concepts, while the second focuses on applying these concepts to real-world problems in a workshop setting. Workshops are highly interactive, with students working primarily in teams. Teamwork is structured around a consultancy model, with dynamic team composition that may change between sessions. The learning activities are designed to be both innovative and academically rigorous, while also ensuring an engaging and enjoyable learning experience.
On successful completion of the module students will be able to:
1. Understand the opportunities and challenges AI presents for organisations, and through experiential learning coupled with reflection, students will understand these in the context of different organisational and business settings.
2. Identify the opportunities AI presents for businesses, and through solving real organisational problems, students will be able to demonstrate experience with AI and thereby signal your experience in this area.
3. Critically evaluate the differences between and benefits of different AI tools and platforms and work with AI in an efficient and effective manner through applied activities, such as case studies or simulations.
4. Recognise different perspectives on AI and become an independent thinker, able to discuss AI in a balanced, and informed manner, and thereby signal AI awareness to prospective employers during the selection process and in the workplace.
On successful completion of the module, students will be able to demonstrate:
Work Readiness - The ability to reflect, communicate effectively both verbally and in writing, use information technology appropriately, and work collaboratively within a team while demonstrating personal responsibility and accountability. Through active learning and reflection, students will also develop commercial awareness, creativity, negotiation skills, and critical thinking.
Digital Skills - The ability to use AI tools to develop creative solutions for business processes, problem-solving, and innovation, as well as to support ongoing digital development in professional contexts.
Enterprise Skills - The ability to identify opportunities and solutions across different areas of economic activity and business contexts (including domain-specific applications of AI). Students will develop creativity, self-confidence, and self-awareness, alongside skills in collaboration and communication, including adaptability and resilience, thereby strengthening their enterprise mindset.
Academic Skills - The ability to learn through experience, develop understanding through reflection and critical thinking, and negotiate outcomes with others. Students will enhance their research capabilities, critically evaluate their own knowledge, and demonstrate an understanding of academic integrity, particularly in relation to the use of AI.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Seminars | 5 | 2 | 10 |
| Lecture | 1 | 1 | 1 |
| Lecture | 2 | 1.5 | 1.5 |
| Lecture | 5 | 1 | 5 |
| Independent online learning hours | 30 | ||
| Private study hours | 52.5 | ||
| Total Contact hours | 17.5 | ||
| Total hours (100hr per 10 credits) | 100 | ||
Formative feedback is an integral component of learning on this module. At the end of each unit (i.e. every two weeks), students will prepare a reflective log of up to 500 words. Each submission will receive AI-generated individual feedback, while the cohort will also receive feedback from the unit lead. This will take the form of exam-style commentary, reflecting on students’ progress to date and providing guidance for subsequent learning. This approach will support students in understanding their progress and the expectations of the module. It will also enable them to critically engage with the differences between AI-generated and human-generated feedback, encouraging reflection on the benefits and limitations of AI. These insights will be valuable in informing their final assessment.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Assignment | 2,500 words individual assignment. Students will prepare a report based on 5 reflective logs scaffolded around the LOs; logs will be prepared at the end of each learning unit; the ability to complete individual logs is not dependent on attendance. | 100 |
| Total percentage (Assessment Coursework) | 100 | |
This is an individual assessment that does not normally require an alternative format. However, in line with University policy, alternative assessments can be provided where appropriate and upon request. A range of assessment methods is available to ensure that the module’s learning outcomes can be appropriately evaluated, and any alternative assessment will be designed in accordance with the nature of the request. The assessment requires students to reflect on their learning throughout the module, with a focus on the development of AI-related skills, knowledge, and understanding of applications. While it is possible to complete the assignment without submitting all five individual learning logs, students are strongly encouraged to engage with them. It is expected that those who complete at least three logs will perform better than those who do not engage consistently throughout the module. As the module is optional, expectations will be clearly communicated at the outset. The resit assessment will also take the form of a 2,500-word reflective assignment, supported by a structured framework provided to students. As with the original assessment, students may complete the resit without having submitted all five learning logs; however, they will be encouraged to further develop their reflections through engagement with the online self-paced learning materials.
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Last updated: 30/04/2026
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