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AI for Organizational Transformation & Innovation — Apply AI to Transform How Organizations Operate and Innovate

AI for Organizational Transformation & Innovation explores how artificial intelligence can reshape not only individual tasks but also operating models, products, services, decision systems, and the way organizations innovate. Participants connect AI opportunities to transformation priorities, redesign workflows and organizational interfaces, develop AI-enabled value propositions, and create conditions for experimentation and scale. The program combines innovation methods, portfolio thinking, human-AI collaboration, governance, and change leadership to help organizations move from scattered AI initiatives toward coordinated transformation and repeatable innovation capability.

Brussels

5 days

December 28, 2026 – January 1, 2027

Price

EUR 5,500

Initial Enrollment Request

Learning Objectives

Identify where AI can transform operating models, workflows, products, services, and decision processes.
Reframe business and organizational challenges as opportunities for AI-enabled innovation.
Design human-AI workflows and organizational interfaces that improve value creation and execution.
Build and prioritize a portfolio of AI transformation and innovation initiatives.
Establish experimentation, governance, capability, and scaling mechanisms for AI-enabled innovation.
Develop a transformation roadmap that connects AI initiatives to measurable organizational outcomes.

Detailed Daily Schedule

Day 1 — From AI Adoption to Organizational Transformation

Distinguish task automation from process, operating-model, and business transformation.
Identify where AI can change decisions, coordination, customer value, and knowledge flows.
Map organizational constraints that limit transformational impact.
Define transformation outcomes and value pools linked to strategic priorities. Build an AI transformation opportunity map.

Day 2 — AI-Enabled Operating Model and Workflow Redesign

Analyze end-to-end workflows rather than isolated AI tasks.
Reallocate work across people, AI systems, automation, and specialist roles.
Redesign handoffs, decision rights, controls, and information flows.
Identify organizational structures and capabilities required by new workflows.
Produce a future-state human-AI operating model for a selected process.

Day 3 — AI as an Innovation Engine

Use AI to expand problem discovery, ideation, experimentation, and prototyping.
Explore AI-enabled products, services, experiences, and business-model opportunities.
Frame innovation hypotheses around customer needs and strategic advantage.
Design rapid experiments with clear learning objectives and decision criteria.
Develop an AI-enabled innovation concept and validation plan.

Day 4 — Portfolio, Governance and Scaling

Build a portfolio across efficiency, growth, experience, and transformational initiatives.
Prioritize initiatives by strategic value, feasibility, learning potential, and risk.
Define governance for experimentation, investment, responsible AI, and scale decisions.
Identify reusable data, platform, talent, and change capabilities across initiatives.
Establish pathways from prototype to production and enterprise adoption.

Day 5 — Leading AI Transformation and Innovation

Align leadership narratives, incentives, culture, and workforce engagement with transformation.
Define metrics for adoption, innovation learning, business value, and organizational change.
Sequence initiatives and capability building into a coherent transformation roadmap.
Anticipate resistance, execution risks, and unintended organizational consequences.
Present an AI transformation and innovation agenda with priorities, owners, and next actions.