The Reflective Practitioner: Cognition and Philosophy in the AI Era (DBA605)

DBA605 The Reflective Practitioner equips senior executives with the philosophical grounding, cognitive foundations, and practical frameworks to lead personal and organisational transformation in the AI era. The course examines how AI reshapes knowledge creation, decision-making, and organisational design, drawing on philosophy of science to strengthen candidates’ approach to empirical research. Topics span AI-augmented decision-making, translating personal AI mastery into professional practice, personal knowledge management, and the reflective practices that enable senior leaders to translate experience into rigorous applied research. Students are expected to develop hands-on skills in building AI-powered knowledge bases, designing research workflows, and driving AI adoption in their organisations. The course is ideal for senior leaders seeking to drive both personal and organisational transformation while strengthening their doctoral research foundations.

• Philosophy of science for applied business research: epistemology, critical inquiry, and what counts as evidence in the AI era
• Cognitive foundations for AI-era leaders: reflective practice, attention management, and AI as cognitive amplifier
• Building personal knowledge systems: AI-powered knowledge bases, second-brain frameworks, and research workflows
• Data literacy for senior leaders: leveraging data and AI tools for evidence-based decision-making
• AI-augmented decision-making: how AI transforms decision-making practice, communication, and strategic thinking
• Translating personal AI mastery into professional practice: redesigning business models, processes, and value chains around AI capabilities
• Scaling reflective practices from individual to enterprise settings: redesigning teams, workflows, and organisational structures for human–AI collaboration
• Translating industry experience into research: from practitioner knowledge to applied research questions
• Personal knowledge iteration: continuous learning, upskilling, and staying current in a fast-moving landscape
• AI-powered research productivity: using AI tools to accelerate literature review, analysis, and writing
• Critical engagement: limits, risks and ethics of AI adoption in business and research
• Designing your DBA research journey: from experience to applied impact

• Analyse foundational concepts of reflective practice, philosophy of science, and cognitive learning as to how they apply to applied research in the AI era
• Examine how AI tools and personal knowledge systems can be leveraged to enhance leadership decision-making and research productivity
• Propose a strategy for integrating professional experience with AI capabilities to drive personal and organisational transformation
• Judge approaches to AI-augmented decision-making and knowledge management
• Create an integrated personal knowledge and research framework that combines AI tools, data, and practitioner experience
• Defend a reasoned approach to leading organisational and personal transformation in the AI era