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
Explore how organisations build cultures that sustain innovation as a strategic capability. Examine the values, behaviours, and leadership approaches that foster creative thinking at scale. Learn how psychological safety, experimentation, and learning from failure drive breakthrough performance. Apply frameworks such as ambidextrous organisation theory and innovation culture audits to diagnose and strengthen your own organisational environment for continuous innovation.
Develop the leadership skills required to guide organisations through complex, high-stakes change. Examine Kotter's 8-step model, Lewin's change cycle, and ADKAR alongside practical case studies of successful and failed transformations. Explore how leaders build trust, manage resistance, and communicate with clarity during uncertainty. Apply structured change leadership tools to real scenarios, building your personal change leadership capability for AI-driven transformation.
Identify and overcome the human, technical, and structural obstacles that prevent organisations from successfully adopting new technologies. Examine cognitive biases, change fatigue, skills gaps, and cultural inertia as adoption barriers. Develop intervention strategies including targeted communication, incentive design, and pilot programmes. Use adoption curve analysis and stakeholder resistance mapping to prioritise your actions and accelerate organisation-wide uptake.
Design the governance, processes, and team structures that enable an organisation to deploy and scale AI effectively. Examine how leading organisations structure AI centres of excellence, federated teams, and hybrid operating models. Explore the interplay between IT, business units, data teams, and executive leadership. Develop a target operating model for AI that balances centralised control with business-unit agility and innovation.
Build the business case and engagement strategies needed to secure commitment from boards, leadership teams, and operational managers for AI and innovation initiatives. Examine persuasion frameworks, stakeholder mapping, and executive communication techniques. Learn how to translate technical capabilities into business value narratives. Practise presenting investment proposals and managing objections from sceptical or risk-averse stakeholders.
Develop a structured, phased roadmap for delivering organisational transformation. Examine how to sequence initiatives, manage interdependencies, and maintain momentum across multi-year programmes. Apply portfolio management principles to balance quick wins with long-term capability building. Learn how to build milestone frameworks, track progress, and communicate roadmap updates to diverse stakeholders throughout a complex AI transformation journey.
Lead deliberate cultural change that aligns employee beliefs and behaviours with strategic AI objectives. Examine how culture is diagnosed, shaped, and sustained through leadership actions, symbols, stories, and systems. Explore the relationship between culture and performance using models such as the Competing Values Framework. Develop a practical cultural change plan tailored to your organisational context and digital transformation ambitions.
Build the learning and development strategy needed to equip your workforce with AI-era skills. Examine competency frameworks, skills gap analysis, and learning pathway design. Explore formal training, coaching, peer learning, and experiential approaches to capability building. Apply a structured planning process to identify skill priorities, allocate resources effectively, and measure the business impact of learning investment across your organisation.
Manage the process of embedding new technology into daily business practice across teams and functions. Examine adoption lifecycle models, user experience principles, and change management techniques specific to technology deployment. Learn how champions, training, and support structures accelerate adoption. Develop a technology adoption plan that reduces resistance, maximises utilisation, and realises the full return on AI technology investment.
Define and track the metrics that demonstrate genuine organisational transformation and AI value creation. Examine leading and lagging indicators, balanced scorecard approaches, and outcome-based measurement frameworks. Learn how to distinguish activity metrics from value metrics and align measurement with strategic objectives. Develop a measurement framework with clear targets, data sources, and reporting cadences for your own transformation programme.
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.
