AI Value Game Masterclass

Module 1: AI Transformation Readiness

Module Objective

You will gain a clear understanding of what top executives must assess before creating an AI strategy. You will learn to evaluate AI through the lens of business impact, organizational processes, operating models, and technological readiness—not merely as a “set of tools.”

The module includes real-world examples of strategic AI use cases across industries, demonstrating how AI influences specific P&L line items and drives measurable business value.

You will learn how to:

• Understand key AI technologies and their practical business applications.
• Identify areas where AI enhances organizational performance and creates competitive advantage. You will learn how to engage with data and IT teams, how to interpret AI use cases, and what input data sources and processes are required.
• Assess your company’s readiness for AI and proactively eliminate barriers such as technical debt, insufficient data quality, missing processes, or lack of skills.
• Build a simple AI readiness canvas for your own organization and set priorities to remove the most critical blockers.
• Evaluate the broader impact of AI on the organization and its environment, including processes, employees, role design, and team dynamics.
• Navigate ethical and regulatory topics such as data protection, bias, accountability, and fairness, and understand the fundamental principles of AI governance and regulatory compliance.

Module 2: Strategic Edge – Creating Value with AI

Module Objective

You will learn how to identify areas where AI delivers the greatest strategic impact. You will gain a framework for developing an AI strategy, business cases, and a managed initiative portfolio built on clearly measurable benefits, grounded in your actual data and processes.

You will learn how to:

• Identify where AI can create strategic impact within the organization—how to manage, prioritize, and scale an AI initiative portfolio. The module includes examples of typical strategic use cases (e.g., revenue growth, cost optimization, risk management) and discussions on how to translate similar approaches into your own business environment.
• Build a simple yet robust AI strategy that aligns with overall corporate strategy and digital transformation, including the definition of a vision, strategic pillars, and key initiatives.
• Design and measure the benefits of AI initiatives, with clear definitions of value, expected outcomes, and quantifiable impact.
• Evaluate AI investments based on business needs, risks, benefits, and strategic priorities. You will learn how to clearly prioritize AI initiatives.
• Optimize return on investment through structured benefit management and strategic execution, including the setup of measurable KPIs for selected use cases.

Module 3: Adoption Edge – Building an AI-Ready Organization

Module Objective

This module equips you with the capabilities to lead AI and digital transformation in a way that is truly adopted, functional, and sustainable. You will strengthen your ability to align strategy, communication, and stakeholder engagement so the company can not only pilot AI solutions but successfully adopt them across the entire organization.

You will learn how to:

• Design an adoption model tailored to your organization and use it to shape communication, stakeholder engagement, and all other elements required for a successful transformation.
• Lead AI initiatives across the organization and manage resistance, organizational blockers, and the most common barriers to adoption.
• Drive change, communication, and people development throughout AI transformation, including an overview of the capabilities that will be needed (e.g., data literacy, working with AI tools).
• Establish governance, accountability structures, and decision-making frameworks for AI, including defining new roles (such as AI Product Owner and AI Champion), and setting up data governance and compliance practices. You will learn how to manage stakeholder involvement and integrate these structures into company policies and processes.
• Prepare targeted communication plans for different stakeholder groups.
• Build a culture and internal ecosystem that continuously supports innovation—including practical ways to collect learning from internal data, pilots, and experimentation, and turn it into the next generation of digital products and services.

Module 4: Scaling and Innovation

Module Objective

In the final module, you will integrate all key elements into a single, functional framework. You will focus on how to systematically connect strategy, process redesign, adoption, and leadership to ensure AI becomes a long-term driver of performance, innovation, and competitive advantage. The module expands on real-world examples and practical guidance for scaling AI projects—for example, how to move from a successful internal pilot to a true enterprise-wide transformation, and how to engage different experts and departments at this stage of scale-up.

You will learn how to:

• Scale AI from pilot projects to enterprise-wide transformation and create new AI-native products, services, and business opportunities.
• Build and grow AI talent and partnerships—how to combine internal capabilities, external suppliers, startups, and strategic alliances to create a sustainable innovation ecosystem.
• Systematically develop an AI-native product stream (discovery → experimentation → pilot → scale) within real processes, including iteration cycles and structured collection of user feedback.
• Manage risks and establish enterprise-level governance for AI at scale, including the right setup of metrics, control mechanisms, and strategic decision rights across the organization (who approves which AI projects, when, and how).
• Apply inspirational case studies and hands-on mini-challenges where you will use your own data to identify opportunities for scaling existing AI solutions and define next steps for expansion. You will benchmark approaches across industries (from manufacturing to services) and learn how to engage users and stakeholders when introducing AI-driven innovation across the company.