Organising and Managing Change in the Digital Age

BMAN74541 Organising and Managing Change in the Digital Age 15 Semester 1 Postgraduate Taught Level 7 Andrea Lagna Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 In an era where AI and data-driven technologies are transforming business and society, effective leadership is crucial to managing and sustaining organizational change. This course equips students with the skills and strategies needed to manage and lead AI-driven transformations successfully. You will explore the unique challenges AI presents to leadership, organizational culture, communication, and power dynamics, and learn how to overcome resistance while aligning human and technological elements for sustainable change. Through real-world case studies, practical frameworks, and a change management project, students will develop the expertise needed to guide organizations through the complexities and challenges of AI adoption, ensuring long-term success in a rapidly evolving global business environment shaped by data and AI. In an era where AI and data-driven technologies are transforming business and society, effective leadership is crucial to managing and sustaining organizational change. This course equips students with the skills and strategies needed to manage and lead AI-driven transformations successfully. You will explore the unique challenges AI presents to leadership, organizational culture, communication, and power dynamics, and learn how to overcome resistance while aligning human and technological elements for sustainable change. Through real-world case studies, practical frameworks, and a change management project, students will develop the expertise needed to guide organizations through the complexities and challenges of AI adoption, ensuring long-term success in a rapidly evolving global business environment shaped by data and AI. Specifically, the unit aims to:  • Equip students with an in-depth understanding of organizational change models and the unique challenges and opportunities AI presents in driving transformation. • Prepare students to manage AI-driven changes, focusing on building leadership strategies that foster innovation, manage resistance, and align teams with AI adoption. • Enable students to navigate the human-centric aspects of AI adoption, including managing organizational culture, politics, and power dynamics to support successful human-centric, AI-driven change. • Teach students how to implement and measure AI-driven change initiatives, ensuring long-term sustainability and continuous improvement through effective metrics and feedback mechanisms.   Knowledge and understanding               KU1       Describe key theories and models of organisational change, including the integration of AI into these frameworks.               KU2       Explain the unique challenges and opportunities AI presents in driving organisational change.               KU3       Explain the impact of AI on organizational culture, power dynamics, and leadership.Intellectual skills             IS1         Analyse and critically evaluate traditional change management models and their applicability in AI-driven transformations.               IS2         Identify strategic leadership approaches for managing AI adoption, focusing on innovation, team alignment, and overcoming resistance.               IS3         Synthesise theoretical and practical knowledge to create effective change management plans that foster human-centric, AI-driven transformations.Practical skills                   PS1        Implement AI-driven change initiatives, applying practical tools and methodologies for leadership and change management.               PS2        Manage and navigate power dynamics, cultural challenges, and stakeholder concerns in AI-driven organisational change.               PS3        Measure the success and sustainability of AI-driven organisational change through the development of feedback loops and continuous improvement metrics.Transferable skills and personal qualities         TS1        Communicate research results effectively, ensuring transparency and managing expectations during Group/team working (collaborating, active listening, planning and organising) Innovation/creativity Understanding innovation (developing your commercial awareness) Leadership (learning to lead, developing your social intelligence, enterprise and entrepreneurship) Problem solving (problem solving, analysis and evaluation, critical thinking) Written communication Interpersonal Skills (becoming an effective communicator, developing emotional intelligence, growing your network, personal skills) Other Digital Proficiency (digital tools and software, data analysis, digital citizenship) Syllabus (indicative curriculum content):Week 1: Introduction to organizational change in the age of AITopics: Overview of organizational change, impact of AI on businesses, types of AI-driven change.Week 2: Theories and models of changeTopics: Traditional change models (Lewin’s, Kotter’s), integrating AI into these models, differences between AI-driven change and traditional change.Week 3: Leading AI-driven organizational changeTopics: Leadership in AI-driven transformations, change leadership vs. AI leadership, fostering a culture that supports AI integrationWeek 4: Organizational culture and AITopics: Organizational culture in the context of AI, aligning culture with technology, overcoming cultural resistance to AIWeek 5: Organizational politics and power in AI-driven changeTopics: The role of power and politics in AI adoption, strategies for navigating power dynamics, influencing key stakeholders, internal power strugglesWeek 6: Human-centric change and AI adoptionTopics: Balancing human roles with AI, managing employee concerns, the human side of AI-driven changeWeek 7: Change communication in the age of AITopics: Communication strategies for AI adoption, managing stakeholder expectations, transparency in AI-driven changeWeek 8: Technology, AI, and organizational structureTopics: Impact of AI on organizational structure, digital networks, scalability of AI-driven processes, flattening hierarchiesWeek 9: Measuring and sustaining AI-driven changeTopics: Metrics for measuring AI change success, sustaining AI integration, continuous improvement, feedback loops in AI adoptionWeek 10: Integrating and applying AI-driven organizational change conceptsTopics: Synthesizing course concepts into a comprehensive change management plan   • Interactive lectures (20 hours) • Tutorials on assessment (10 hours) • Guided independent study (120 hours) Total: 150 hours   3 Report 100% Written feedback provided on CLE N • Battilana, J., & Casciaro, T. (2021). Power, for All: How It Really Works and Why It’s Everyone's Business. New York: Simon & Schuster. • Kane, G., Phillips, A., Copulsky, J., & Andrus, G. (2019). The Technology Fallacy: How People Are the Real Key to Digital Transformation. Cambridge: MIT Press. • Leonardi, P., & Neeley, T. (2022). The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston: Harvard Business Review Press. • Iansiti, M., & Lakhani, K. R. (2020). Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press. • Davenport, T. (2019). The AI Advantage: How to Put the Artificial Intelligence Revolution to Work. Cambridge: MIT Press. • Kotter, J. P. (2012). Leading Change. Boston: Harvard Business Review Press. • Pfeffer, J. (1992). Managing with Power: Politics and Influence in Organizations. Boston: Harvard Business School Press. • Schildt, H. (2020). The data imperative: How digitalization is reshaping management, organizing, and work. Oxford: Oxford University Press. • Senior, B and Swailes, S, (2020). Organizational Change. London: Pearson. Lectures 20 Tutorials 10 0 120