Advanced AI and Digital Transformation for Leaders Training Course – Online, 27 Dec 2026 – 7 Jan 2027

Advanced AI and Digital Transformation for Leaders is a 2-week training course for senior leaders, transformation directors and managers steering digital change, and it ends with an AI-enabled transformation roadmap each participant brings back to the executive table. Intelligent automation, cloud platforms and generative AI are redrawing how organisations are structured and how work flows between people and systems. Jupiter Prime Training runs this course on AI and digital transformation.

Why AI and Digital Transformation Matters Now

Three forces shape digital transformation today: platforms and intelligent automation that make legacy operating models expensive to keep, a workforce whose roles are being reshaped by AI assistants, and boards that judge leaders on whether change actually lands rather than on how many systems are bought. A utility that redesigns field operations around sensor data and automated dispatch gains resilience; a bank that layers AI on unchanged processes often adds cost and confusion. The course rests on the McKinsey 7-S Framework, Kotter's 8-Step Change Model, the Capability Maturity Model approach to digital maturity and ISO/IEC 42001 for AI management systems.

Who Gains Most from AI and Digital Transformation

• Those who set the direction of enterprise-wide change and answer to the board for its progress
• Those who redesign operating models, structures and decision rights around digital capabilities
• Those who sponsor automation, platform and data modernisation portfolios
• Those who lead culture, capability building and workforce transition through change
• Those who oversee technology risk, architecture choices and AI controls at executive level

Executive committees and transformation offices gain most when a business leader, a technology leader and a people leader attend together and shape one direction for change.

AI and Digital Transformation Capabilities

Transformation directors and senior managers leave equipped to turn digital ambition into a sequenced, governed change effort:

• Assess digital and AI maturity across processes, platforms, skills and culture — for setting the transformation baseline
• Design a target operating model that redistributes work between people, automation and AI agents — for structural decisions
• Weigh platform, cloud and data architecture options against agility and lock-in — for chief technology and procurement decisions
• Apply Kotter's model and the McKinsey 7-S Framework to align culture, structure and systems — for change leadership
• Build a transformation portfolio with stage gates, funding tranches and outcome measures — for board oversight
• Communicate a risk-aware transformation narrative to staff, customers and investors — for stakeholder confidence

Key AI and Digital Transformation Terms

• Digital transformation — the redesign of an organisation's operating model, processes and customer experience around digital and AI capabilities.
• Target operating model — a description of how an organisation will run in future: structure, processes, technology, people and governance.
• Intelligent automation — the combination of robotic process automation with AI so that systems handle judgement-based as well as rule-based tasks.
• Digital maturity — the degree to which an organisation's strategy, culture, skills and technology support digital ways of working.
• Enterprise architecture — the blueprint linking business capabilities, applications, data and infrastructure so technology choices fit together.
• McKinsey 7-S Framework — a model of seven linked elements, from strategy and structure to shared values, that must align for change to hold.

AI and Digital Transformation Day by Day

Day 1: Forces Reshaping Organisations

• Platform Economics and Ecosystems — How Digital Rivals Change Industry Structure
• Generative AI and Agentic Systems — New Possibilities for Knowledge Work
• Workforce and Skills Shifts — Roles Augmented, Automated or Created
• Customer Expectation Trends — Omnichannel and Real-Time Service
• Transformation Failure Patterns — Lessons From Stalled Programmes

Day 2: Digital Maturity and Transformation Ambition

• Digital Maturity Models — Scoring Strategy, Culture, Skills and Technology
• Capability Heat Mapping — Locating Gaps That Block Change
• Transformation Ambition Statements — Choosing Optimise, Extend or Reinvent
• Digital North Star Metrics — Defining What Success Looks Like
• Executive Alignment Workshops — Agreeing Priorities Across the Leadership

Day 3: Redesigning the Operating Model

• Target Operating Model Design — Structure, Processes and Decision Rights
• McKinsey 7-S Analysis — Aligning Strategy, Systems and Shared Values
• Product-Centric and Agile Structures — Cross-Functional Teams Around Customers
• Human and AI Work Allocation — Deciding Who Does What
• Shared Services and Centres of Excellence — Scaling Digital Capabilities

Day 4: Process Automation and Intelligent Automation

• Process Mining — Revealing Real Workflows and Bottlenecks
• Robotic Process Automation — Candidate Selection and Limits
• Intelligent Automation Design — Combining Rules, AI and Human Review
• AI Agents in Operations — Delegated Tasks and Escalation Paths
• Automation Benefit Tracking — Cycle Time, Error Rates and Capacity Released

Day 5: Data, Platforms and Architecture Choices

• Enterprise Architecture Principles — Fitting Business Capabilities to Technology
• Cloud Migration Strategies — Rehost, Refactor or Replace Decisions
• Data Platform Patterns — Warehouses, Lakes and Data Mesh
• Legacy Modernisation Paths — Sequencing Core System Replacement
• Vendor and Ecosystem Strategy — Avoiding Lock-In While Moving Fast

Day 6: Customer and Employee Experience

• Customer Journey Mapping — Moments Where Digital Changes Loyalty
• Personalisation Engines — Tailoring Offers and Service at Scale
• Employee Experience Platforms — Digital Tools That Shape Productivity
• Service Design Blueprints — Front-Stage and Back-Stage Alignment
• Experience Measurement — Net Promoter and Effort Scores

Day 7: Culture and Change Leadership

• Kotter's 8-Step Change Model — Building Urgency and Guiding Coalitions
• Digital Culture Diagnostics — Experimentation, Collaboration and Learning Habits
• Change Resistance Mapping — Stakeholder Concerns and Responses
• Leadership Role Modelling — Visible Behaviours That Signal Change
• Workforce Transition Planning — Reskilling, Redeployment and Communication

Day 8: Portfolio, Funding and Measurement

• Transformation Portfolio Design — Balancing Quick Wins and Structural Shifts
• Stage-Gate and Tranche Funding — Releasing Investment Against Evidence
• Objectives and Key Results — Linking Initiatives to Strategic Outcomes
• Transformation Office Set-Up — Cadence, Reporting and Escalation
• Benefits Realisation Tracking — Measuring Outcomes Beyond Go-Live

Day 9: Risk, Controls and Responsible AI

• ISO/IEC 42001 Principles — Management System Controls for AI
• Cyber Resilience in Digital Operations — Protecting New Attack Surfaces
• Responsible AI Policies — Fairness, Transparency and Human Oversight
• Third-Party and Cloud Risk — Contracts, Concentration and Exit Plans
• Board Reporting on Digital Risk — Indicators Directors Need

Day 10: Building the Transformation Roadmap

• Maturity Gap Prioritisation — Applying Day Two Scores to Roadmap Choices
• Operating Model Transition States — Applying Day Three Designs in Phases
• Change and Culture Workstream — Applying Day Seven Methods to the Roadmap
• Executive Narrative and Board Pitch — Securing Commitment for Phase One
• Transformation Roadmap Assembly — Phases, Portfolio, Funding Gates and Measures

Applying AI and Digital Transformation After the Course

• Run a digital maturity assessment with the executive committee and agree the three capability gaps that most constrain change.
• Use process mining on one end-to-end workflow to choose the first intelligent automation candidate and its benefit measures.

AI and Digital Transformation Questions (FAQ)

What is AI and digital transformation for leaders, and why does it matter now?

AI and digital transformation for leaders is the redesign of an organisation's operating model, processes and culture around digital platforms, automation and AI. It matters now because rivals using these capabilities are lowering costs and raising service expectations faster than traditional change can respond.

Which roles gain most from advanced AI and digital transformation training for leaders?

Chief executives' direct reports, transformation directors, operations and technology heads, and people leaders gain most from advanced AI and digital transformation training for leaders. They set direction, own the operating model and lead staff through change.

How is an AI and digital transformation course for leaders different from an IT project management course?

An AI and digital transformation course for leaders addresses operating models, culture, portfolios and board oversight across the whole organisation. An IT project management course focuses on scheduling, scoping and delivering individual technology projects to time and budget.

What do participants bring back from AI and digital transformation training for leaders?

Participants bring back a digital maturity baseline, a target operating model sketch, an automation candidate list, a change and culture workstream and a funded portfolio structure. You can use them straight away to brief your executive committee.

AI and Digital Transformation: The Way Forward

The AI-enabled transformation roadmap sets out phases, portfolio, funding gates and measures in one view leaders can steer by. The first decision it informs is what the organisation changes in phase one and what waits. Executive committees and transformation offices use it together, and the operating model transition states are worth revisiting once phase one benefits are measured.