Overview
Course overview
A non-technical AI programme helping leaders understand strategy, governance, risk, workforce change and responsible adoption without needing to code. The course is built around practical learning, professional confidence and clear progression. Learners are encouraged to apply ideas to realistic business situations and leave with a stronger ability to communicate decisions effectively.
What you will study
Analyse the skills landscape of the AI era and identify the competencies organisations must build to remain competitive. Examine research on human skills that complement AI, including critical thinking, creativity, emotional intelligence, and complex problem-solving, alongside technical AI literacy requirements. Learn how to conduct future skills assessments using scenario planning and workforce analysis. Develop a prioritised future skills framework for your organisation or sector.
Redesign roles and job structures to optimise the collaboration between human workers and AI systems. Examine task decomposition methodologies that identify which elements of current roles are candidates for AI augmentation or automation. Learn how to design enriched human roles that focus on judgement, relationships, and creativity. Apply job redesign frameworks to real roles, creating new job architectures that increase productivity, satisfaction, and strategic value.
Build a comprehensive reskilling strategy that prepares your workforce for AI-driven role changes. Examine reskilling programme design, delivery approaches, and the psychological dimensions of helping employees navigate significant career transitions. Learn how leading organisations have designed large-scale reskilling initiatives. Develop a reskilling strategy with clear eligibility criteria, learning pathways, support structures, and measurable success metrics.
Design and lead high-performing teams that work effectively alongside AI tools and systems. Examine how team roles, norms, and collaboration processes change when AI is embedded in team workflows. Learn how to build psychological safety and trust when teams use AI for decision support. Develop practical guidance for team leaders on introducing AI tools, managing related anxieties, and creating team cultures that combine human judgement with AI capability.
Apply data and analytics to understand workforce dynamics and make evidence-based talent decisions. Examine workforce planning models, predictive attrition analytics, skills inventory systems, and talent pipeline analysis. Learn how to use AI-powered HR analytics tools responsibly and interpret results for leadership decision-making. Develop a talent analytics capability plan that improves the quality of strategic workforce planning and talent management decisions.
Develop a structured workforce transformation roadmap that sequences people-related changes in support of your AI strategy. Examine how to align workforce planning with technology deployment timelines and business transformation milestones. Learn how to build a workforce roadmap with clear phases, workforce targets, and transition plans for affected employee groups. Develop a communication strategy that gives employees visibility of their future within the organisation.
Design structured learning pathways that build AI-relevant capabilities at scale across your workforce. Examine learning pathway design principles, blended learning approaches, and the use of AI in personalising learning experiences. Learn how to map current capability levels, define target competencies, and build progressive learning journeys. Develop learning pathway blueprints for key workforce segments including leaders, technical specialists, and operational employees.
Build the organisational-level capabilities required to sustain AI-driven competitive advantage over time. Examine how capabilities differ from individual skills and why building organisational capability requires systemic interventions. Learn how to diagnose capability strengths and gaps using maturity frameworks. Develop a capability building strategy that strengthens the organisation's collective ability to learn, adapt, and innovate in an AI-driven competitive environment.
Design communication strategies that help employees navigate AI-driven workforce transformation with confidence and commitment. Examine communication frameworks for large-scale change, including narrative design, channel strategy, and two-way dialogue mechanisms. Learn how to address employee concerns about AI and automation honestly and constructively. Develop a change communication plan with targeted messages for different employee audiences throughout multi-year transformation.
Develop strategies to retain critical talent during periods of significant AI-driven transformation. Examine the specific retention risks created by automation anxiety, skills uncertainty, and competitive talent markets for AI expertise. Learn how to design compelling employee value propositions that differentiate your organisation. Develop a targeted retention strategy for your most critical employee segments, combining career development, recognition, leadership quality, and culture to reduce unwanted attrition.
Who is this for?
Working professionals, managers, founders, team leaders and ambitious learners seeking practical development.
Learning outcome
By the end of the programme, learners should have a clearer professional framework, stronger confidence and a practical action plan that can be applied in study, work or organisational decision-making.
Assessment and delivery style
Teaching is designed to be interactive, applied and professionally relevant. Activities may include case discussion, guided exercises, workplace examples, short presentations, reflective planning and tutor-led feedback.
