Advanced Mini MBA in AI and Digital Transformation Training Course – Istanbul, 20 Jun – 1 Jul 2027

Mini MBA in AI and Digital Transformation is a 2-week advanced training course for senior managers, directors and transformation leaders who must set direction for AI-enabled change, and who leave with an AI transformation roadmap. Organisations now face pressure to redesign operating models, platforms and investment rules at once, while boards question whether digital spending is paying off. Jupiter Prime Training runs this course as an executive mini MBA for leaders accountable for that agenda.

Why Mini MBA in AI and Digital Transformation Matters Now

Three forces shape this subject today: AI capabilities that reshape cost structures and customer expectations across sectors, boards and investors demanding evidence that transformation spending creates value, and workforces facing role changes that require visible leadership. An organisation that leads this well redesigns its operating model deliberately and funds the right initiatives in the right order; one that leads it poorly accumulates disconnected projects, technical debt and change fatigue. The course rests on ISO/IEC 42001, the international standard for an artificial intelligence management system, and the NIST AI Risk Management Framework (NIST AI RMF) for executive oversight of AI risk.

Who Gains Most from Mini MBA in AI and Digital Transformation

• Executives accountable for enterprise strategy and the transformation agenda
• Directors who own business units whose operating models are being redesigned
• Leaders of transformation or strategy offices who shape the change portfolio
• Finance and investment leads who approve digital business cases
• Technology and data leaders who set platform and architecture direction

Leadership teams gain most when a business unit director, a finance lead and a technology leader attend together, because transformation decisions depend on all three agreeing the same roadmap.

Mini MBA in AI and Digital Transformation Capabilities

Participants leave able to connect AI ambition to operating model, investment and governance choices that a board can approve and track.

• Assess where AI and digital capabilities shift the organisation's competitive position — boards setting ambition
• Design an operating model that places AI capability and decision rights clearly — executive committees
• Build investment cases using net present value and staged funding logic — finance committees
• Weigh initiatives in a prioritised portfolio with stage-gate criteria — transformation offices
• Specify AI governance structures aligned with international standards — risk and audit committees
• Communicate a transformation narrative that sustains workforce commitment — employees and line managers

Key Mini MBA in AI and Digital Transformation Terms

• Digital transformation — the redesign of strategy, processes, operating model and culture around digital and data capabilities to create new value.
• Operating model — the way an organisation arranges processes, structures, people, technology and decision rights to deliver its strategy.
• Value pool — a defined source of revenue or cost saving where improvement opportunities can be sized and prioritised.
• Real options — an approach that values the flexibility to expand, delay or abandon an investment as uncertainty resolves.
• Stage-gate review — a decision point where an initiative is continued, redirected or stopped based on agreed evidence.
• Benefit realisation — the discipline of tracking whether promised outcomes from an investment actually occur and who owns them.

Mini MBA in AI and Digital Transformation Day by Day

Day 1: Strategic Context for AI-Enabled Change

• Industry Disruption Mapping — Where AI Rewrites Cost and Revenue Models
• Digital Maturity Diagnostics — Locating the Organisation on the Curve
• Competitive Positioning with AI — Differentiation Versus Parity Moves
• Board-Level Transformation Questions — Ambition, Pace and Risk Tolerance
• Case Contrasts from Banking and Logistics Transformations

Day 2: Transformation Strategy Formulation

• Value Pool Analysis — Sizing Where Digital and AI Create Advantage
• Strategic Themes and North-Star Metrics — Framing the Ambition
• Horizon Planning — Balancing Core Optimisation and New Ventures
• Ecosystem and Partnership Strategy — Platforms, Alliances and Acquisitions
• Strategy-on-a-Page — Communicating Direction to the Executive Committee

Day 3: Operating Model Redesign

• Operating Model Canvas — Processes, Structures, Roles and Decision Rights
• Centre of Excellence Versus Federated Models — Placing AI Capability
• Agile Product Teams — Moving from Projects to Persistent Value Streams
• Process Redesign with Intelligent Automation — Removing Hand-Offs
• Spans, Layers and New Roles — Organisation Design for Digital Work

Day 4: Data Platforms and Architecture Choices

• Data Strategy Pillars — Quality, Access, Ownership and Monetisation
• Cloud, Lakehouse and Integration Patterns — Executive-Level Trade-Offs
• Build, Buy or Partner for AI Capability — Total Cost and Control
• Technical Debt and Legacy Modernisation — Sequencing Replacement
• Cybersecurity Considerations in Platform Decisions

Day 5: Investment Cases and Financial Discipline

• Transformation Business Case Structure — Benefits, Costs and Assumptions
• Net Present Value and Payback for Digital Initiatives
• Real Options Thinking — Valuing Staged Investment Under Uncertainty
• Benefit Realisation Tracking — Linking Spend to Measurable Outcomes
• Funding Models — Annual Budgets Versus Rolling Product Funding

Day 6: Portfolio Prioritisation

• Initiative Scoring Models — Value, Feasibility and Strategic Fit
• Portfolio Heatmaps — Balancing Risk Across the Change Agenda
• Dependency and Capacity Mapping — Avoiding Overloaded Business Units
• Stage-Gate Reviews — Continue, Pivot or Stop Decisions
• Quick Wins Versus Foundational Bets — Sequencing for Momentum

Day 7: AI Governance at Executive Level

• ISO/IEC 42001 — Establishing an AI Management System Across the Enterprise
• NIST AI RMF — Govern, Map, Measure and Manage for Strategic Initiatives
• AI Ethics Principles — Fairness, Transparency and Accountability in Policy
• Board Reporting on AI Risk — Dashboards and Escalation Thresholds
• Responsible AI Committees — Composition, Mandate and Decision Rights

Day 8: Change Leadership and Culture

• Transformation Narrative — Explaining Why, What and How to the Workforce
• Staged Change Leadership — Building Urgency and Coalitions for AI Adoption
• Leadership Behaviours That Accelerate or Stall Digital Change
• Workforce Reskilling Roadmaps — Capability Gaps and Learning Paths
• Resistance Diagnostics — Spotting and Addressing Sources of Push-Back

Day 9: Measuring Transformation Value

• Transformation Scorecards — Leading and Lagging Indicators
• Digital Adoption Metrics — Usage, Process Coverage and Cycle Time
• Financial Value Tracking — Cost-to-Serve, Revenue Uplift and Margin
• Customer and Employee Experience Measures — NPS and Engagement Signals
• Quarterly Business Reviews — Adjusting the Roadmap on Evidence

Day 10: Practising the AI Transformation Roadmap

• Strategy and Value Pool Applied — Framing a Real Agenda from Participants' Organisations
• Operating Model and Platform Choices — Combining Earlier Design Decisions
• Investment Case and Portfolio Sequence — Prioritising the First Waves
• Governance and Change Plan — Embedding Oversight and Adoption Actions
• AI Transformation Roadmap — Completing and Presenting to a Mock Board

Applying Mini MBA in AI and Digital Transformation After the Course

• Score the current initiative list with the portfolio model and present a reprioritised sequence to the executive committee
• Draft the mandate and membership of a responsible AI committee and agree its escalation thresholds with the risk function

Mini MBA in AI and Digital Transformation Questions (FAQ)

What is a mini MBA in AI and digital transformation, and why does it matter now?

It is an executive course that connects strategy, operating model, data platforms, investment and governance for AI-enabled change. It matters now because AI is reshaping cost and revenue models, and boards expect transformation spending to show measurable returns.

Which roles gain most from a mini MBA in AI and digital transformation?

Senior managers, directors and transformation leaders gain most. You set direction, approve investment or redesign business units, so you need one integrated view of strategy, finance, technology and change leadership.

How does a mini MBA in AI and digital transformation differ from a foundation AI for business course?

It works at executive depth across the whole enterprise. A foundation course explains AI use cases and basic adoption, whereas this subject covers operating model redesign, investment cases, portfolio prioritisation, board-level governance and transformation measurement.

What do you bring back from a mini MBA in AI and digital transformation?

You bring back a transformation roadmap for your own organisation. It links strategic themes, operating model choices, a prioritised investment portfolio, governance arrangements and the scorecard used to track value.

Mini MBA in AI and Digital Transformation: The Way Forward

The AI transformation roadmap first informs which initiatives form the opening wave and how they are funded. Executives, finance leads and technology leaders use it to agree sequence, governance and value measures. After the first quarterly review, revisit portfolio scores and benefit assumptions, because early results usually reveal where adoption, data readiness or capacity differ from the original plan.