Course.
AI Business Strategy for Corporate Governance
In today’s rapidly evolving business landscape, AI has become a transformative force that plays a critical role in corporate governance. This course is designed to equip board members, owners, investors, and executives with the strategic knowledge and tools they need to navigate AI integration within their organizations. Participants will learn how to align AI initiatives with business goals, drive innovation, enhance decision-making, and safeguard ethical practices.
Quick facts:
Duration: The program is spread over 18 weeks, with one session every third week to allow for deep reflection and practical application between modules.
Coming dates for courses: TBA
Where: Hybrid - Remote & Stockholm
Course fee: 35 000 SEK ex VAT
(As a deb-alumnus you get a 10% discount)
Detta ingår:
XXX 4 lektionstimmar med teori, praktik och diskussioner
XXX Exklusiv tillgång till kursmaterial
XXX Nätverk och inspiration från kursdeltagare och kursledare
Course leader
Peter Kurzwelly.
Strategic Partnership Lead, AI Sweden
Peter Kurzwelly spearheads AI Sweden's expansion in Montreal, connecting Sweden with one of the world’s top AI ecosystems. His mission is to accelerate AI adoption in Sweden, enhancing national competitiveness and innovation. Peter also leads a community of Swedish CEOs and CXOs, turning AI potential into real-world impact. As the host of popular podcasts AI Sweden Podcast and The World We Are Building, he’s a recognized voice in the AI leadership space.
Course leader
Hanna Moisander.
Board Member and CEO, deb.
Hanna Moisander is an accomplished board member with extensive experience ranging from startups to billion-SEK companies. She excels in international board roles and listed environments, often taking on the chairperson position to establish and refine board operations. As the CEO and co-founder of deb. - diverse executive boards, Hanna combines her entrepreneurial spirit with a passion for proactive board work and continuous business development. In addition to her board responsibilities, she is an active advisor and angel investor, dedicated to driving growth and innovation across her diverse portfolio.
Absout the course.
Who should participate?
Program delivery
This course is intended for board Members responsible for overseeing AI initiatives, owners and Investors interested in leveraging AI for strategic growth, executive Leadership seeking to integrate AI into long-term corporate strategies.
Format: The course is delivered as a combination of live instructor-led sessions, self-paced readings, case studies, and practical exercises.
Modular Learning: The course is divided into several modules that allow participants to progressively build on their understanding of AI in corporate governance.
Flexible Participation: Available both online and in-person to accommodate different schedules and learning preferences.
Course content
The course is structured around Five Critical Pillars of AI Strategy that will guide participants through a comprehensive exploration of AI from a governance perspective.
Each pillar addresses the unique responsibilities and challenges faced by boards in implementing AI.
Key Topics Included:
Introduction to AI and Machine Learning
Algorithmic Bias and Ethical AI
Data Privacy and Regulatory Compliance
AI's Impact on Employment and Organizational Structure
AI in Strategic Decision-Making and Innovation
Corporate Governance and AI Ethics
Practical Workshops and Real-World Scenarios
Modules.
1.
AI Foundations for executives
Objective:
Equip executives with a high-level understanding of AI, its capabilities, and its strategic importance.
Topics Covered:
Understanding the Basics of AI: Introduction to machine learning, data science, and AI decision-making.
Industry-Specific AI Applications: Case studies highlighting AI applications across different industries.
Potential and Limitations of AI: What AI can and cannot do, including ethical concerns and risks.
Key Takeaways:
A basic grasp of AI’s relevance to their industry.
Ethical considerations Board members and executive teams needs to account for in their AI strategies.
2.
Vision and Strategy Development
Objective:
Equip executives with a high-level understanding of AI, its capabilities, and its strategic importance.
Topics Covered:
Understanding the Basics of AI: Introduction to machine learning, data science, and AI decision-making.
Industry-Specific AI Applications: Case studies highlighting AI applications across different industries.
Potential and Limitations of AI: What AI can and cannot do, including ethical concerns and risks.
Key Takeaways:
A basic grasp of AI’s relevance to their industry.
Ethical considerations Board members and executive teams needs to account for in their AI strategies.
3.
Leadership and AI-Driven Culture
Objective:
Foster AI leadership within the executive team and establish a culture of innovation.
Topics Covered:
AI Awareness Among Leadership: Encouraging the leadership team to champion AI initiatives.
Appointing AI Leadership: Strategies for integrating AI expertise into the leadership team.
Building a Data-Driven Culture: Creating an environment where data and AI-driven decisions are prioritized.
Key Takeaways:
Leadership’s role in AI adoption.
How to champion AI initiatives throughout the organization.
4.
Building Talent and Competence
Objective:
Ensure the operational team understands the importance of talent in driving AI success and that we have a talent strategy that aligns with this.
Topics Covered:
AI Skills and Competence Audit: Assessing current AI knowledge and talent gaps.
Hiring and Upskilling for AI: Identifying key roles like data scientists, AI engineers, and AI champions.
Fostering Continuous Learning: Encouraging a culture of continuous AI education and upskilling.
Key Takeaways:
A roadmap for building an AI-capable team.
Actionable steps for fostering internal AI expertise.
5.
Data Strategy and AI Governance
Objective:
Highlight the critical role of data in AI and ensure proper governance frameworks are established.
Topics Covered:
Establishing a Data-First Culture: Recognizing data as a strategic asset.
Data Infrastructure and Accessibility: Ensuring data availability and quality for AI initiatives.
AI Governance Framework: Defining roles, responsibilities, and addressing ethical issues in AI.
Key Takeaways:
Key elements of a strong data strategy.
Ethical considerations and governance required for AI initiatives.
6.
Scaling AI Projects and Measuring Success
Objective:
Enable Boards and executive teams to understand how to scale AI projects and measure their success.
Topics Covered:
Piloting AI Initiatives: Launching AI projects and learning from pilot testing.
Scaling AI for Business Impact: Integrating successful AI solutions into core operations.
Success Metrics and Communication: Defining KPIs and communicating AI wins to the board and beyond.
Key Takeaways:
A framework for piloting and scaling AI projects.
Clear metrics for assessing and communicating AI success.
Additional components.
Workshops & interactive sessions:
Each module is supported by practical group exercises, case studies, and real-world examples to ensure that participants can apply their learning directly to their business contexts.
Certification:
Upon successful completion of the course and a final examination, participants will receive a Certificate in AI for Business Strategy. This certification highlights a participant's understanding of AI's strategic and ethical implications in corporate governance.
Networking Opportunities
Throughout the program, participants will engage with peers, industry experts, and instructors to build a robust network of professionals working at the intersection of AI and corporate governance.