RESPONSIBLE AI FOR BUSINESS - 2025/6

Module Overview

This module explores the ethical, societal, and regulatory dimensions of Artificial Intelligence (AI) and data technologies in business and organisational contexts. MBA students will examine the broader impact of AI across various stakeholders, with a particular focus on ethical principles, socially responsible innovation, policy implications, and accountability. Through engagement with foundational frameworks and real-world case studies, students will learn to assess risk and unintended consequences, navigate evolving regulatory approaches, apply ethical frameworks, and evaluate responsible AI strategies. Topics include algorithmic bias, data ethics, AI explainability, surveillance, global regulation, and cybersecurity, among others. The module equips future business leaders to engage thoughtfully and responsibly with AI and data technologies, leading initiatives that are not only innovative but also transparent, inclusive, socially beneficial, and aligned with evolving societal expectations that demand ethical leadership.

Module provider

Surrey Business School

Module Leader

SOTUNDE Deji (SBS)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Module Availability

Semester 2

Prerequisites / Co-requisites

None

Module content

Indicative content includes:
¿ AI, Data and Society
¿ Bias, Fairness, and Inclusion in AI Systems
¿ Privacy and Personal Data
¿ Explainability, Transparency, and Trust in AI
¿ Ethical Risk, Accountability, and the Limits of AI and Automation
¿ Global AI Governance and Regulatory Trends
¿ Algorithmic Power and Control
¿ Cybersecurity, Safety, and Resilience in AI Systems

Assessment pattern

Alternative Assessment

Individual assessment in place of the group presentation

Assessment Strategy

The assessment strategy is designed to enable students to demonstrate their ability to critically engage with the ethical, societal, and policy implications of AI and data use in business. It assesses students¿ capacity to evaluate real-world cases, apply ethical and governance frameworks, and reflect on responsible strategies that encompass organisational and societal responsibilities. The assessments provide a balance of individual reflection and collaborative problem-solving, supporting both conceptual understanding and practical application in leadership contexts.
Thus, the summative assessment for this module consists of:
¿ Group Presentation
¿ Individual Essay
Formative assessment:
Formative assessment in this module takes place throughout its delivery, with students receiving regular feedback through class participation, case study discussions, and guided learning components.

Feedback:
¿ Oral Feedback: Students will receive regular in-class feedback throughout the module. They will also receive oral feedback after the group presentation.
¿ Written feedback: Students will receive written feedback on both assessments. This will be provided by a first marker and the moderator in the context of the marking rubric uploaded on SurreyLearn.

Module aims

• Develop a critical understanding of the impact of AI and data technologies on society, business, and individuals.
• Examine the role of policy, regulation, and governance in shaping the responsible use of AI and data in organisational decision-making and operations.
• Explore ethical principles and responsible innovation frameworks, including fairness, accountability, transparency, and explainability, relevant to AI use in organisational practices.
• Examine responsible AI and data strategies that promote trust, accountability, and stakeholder alignment.
• Assess the potential risks and unintended consequences of AI and data use in business.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to develop students¿ critical understanding of responsible AI and data governance by engaging them in applied, reflective, and participatory learning experiences. The module adopts an applied, discussion-led approach to teaching, combining interactive lectures, real-world case studies, ethical scenario analysis, and group-based activities. Students will engage critically with contemporary examples of AI use in business, exploring regulatory, ethical, societal, and governance challenges through a mix of individual and group-based activities. Learning is supported by guided independent study, curated readings, online resources, and multimedia content to deepen understanding of the topics. The teaching strategy emphasises critical thinking, peer learning, and reflective practice, preparing students to lead responsibly in AI- and data-driven environments. Students are expected to prepare for each session through assigned readings and are encouraged to explore current developments in AI and data beyond the classroom.

The learning and teaching methods include:
¿ Interactive lectures introducing key concepts, frameworks, and real-world examples.
¿ Case study analysis of responsible AI deployment in the business context.
¿ Ethical dilemma discussions to explore and debate complex decision scenarios.
¿ Group activities and structured discussions, encouraging critical reflection and peer-to-peer learning.
¿ Guided independent study, including curated reading lists and materials, online resources, and practices to support self-directed learning.
¿ Guest lectures or industry speakers (where possible) to provide insight into current practices and trends.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: MANM609

Other information

Surrey Business School, MBA programme is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability, and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas: Digital capabilities: Through exploring how AI and data technologies shape business strategy, regulation, and stakeholder trust, students develop a strong conceptual understanding of digital systems. They also critically evaluate digital risks, algorithmic decision-making and control, and emerging governance frameworks that underpin responsible digital transformation. Employability: Students engage with real-world challenges around AI adoption, governance, and ethics in business. By analysing case studies, developing strategic responses and policy recommendations, and through group work, students build critical thinking, communication, and leadership skills that are highly valued in data-driven industries and senior management roles. Global and cultural capabilities: The module draws on international case studies and global regulatory frameworks, encouraging students to explore how AI and data practices vary across cultural and legal contexts. This fosters awareness of global perspectives, ethical norms, and stakeholder diversity in data governance. Resourcefulness and Resilience: Students work both independently and collaboratively to solve complex ethical problems, assess emerging risks, and manage uncertainty in AI deployment. The module fosters resilience by encouraging critical self-reflection, ethical leadership, and decision-making under ambiguity. Sustainability: Students will develop a thorough understanding of the broader impact of AI and data technologies beyond market profitability. Understanding and analysing the societal, ethical, and policy implications of these emerging technologies provides students with a system-level perspective on sustainable and responsible innovation. The module encourages students to consider the long-term consequences of AI adoption, evaluate trade-offs, and think critically about how technology can support more inclusive, equitable, and resilient business practices.

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2025/6 academic year.