More insights about AI Leadership for Boards

Insights into the book AI Leadership for Boards – The future of Corporate Governance by Torre, Teigland and Engstam, based on academic research, current version released 2020.

The research and book are currently being updated with the kind support of Internetstiftelsen. Planned release of updated book end 2024/beginning 2025.

As we are currently updating the research and book, do reach out to us if you have some perspective on Boards Leadership of AI.

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The summary below includes a FAQ, a Briefing, People list, a Study Guide, a Glossary, a Book Table of Contents (and a Podcast above)! Below information is produced based on the book with the insightful support of NotebookLM.

FAQ about AI and board work

8-question FAQ on the main themes and ideas presented in the text “AI Leadership for Boards – The Future of Corporate Governance”:

Why is it important for boards to understand AI?

In today’s digital era, AI has become a significant competitive factor. Boards that understand AI and its implications can better steer their companies toward successful implementation of AI, leading to increased growth and better risk management. Without this knowledge, companies risk falling behind and missing important opportunities.

What are the two main areas of competence that boards need to develop in AI?

The book identifies two main areas:

Guiding AI-powered business capabilities: This includes understanding and managing the collection, processing and analysis of data, driving AI-powered innovation and navigating business ecosystems.
Supervise AI governance capabilities: This means ensuring responsible data management, addressing ethical issues around AI, including “black box” decision-making, ensuring AI cyber security and leading AI governance within the business ecosystem.

How can boards govern the collection and use of data for AI?

Boards need to develop a deep understanding of data as a strategic asset. They should evaluate the company’s data collection strategy, both internal and external, and ensure that data is managed responsibly and in accordance with relevant laws and regulations, such as GDPR.

What role does innovation play in connection with AI and board work?

Boards need to foster a culture of innovation that embraces AI. They should challenge management to identify and explore uses for AI that can improve products, services and internal processes. Being at the forefront of AI-driven innovation is critical to maintaining competitiveness.

Why is AI Governance critical and how can boards monitor it?

AI governance is essential to ensure ethical and responsible use of AI. Boards should monitor that the company has clear policies and processes in place for data management, managing AI bias and cyber security. They should also consider the societal implications of AI and ensure that the company’s AI use is consistent with its values.

How can boards address the challenges of “black box” decision making in AI?

“Black box” decision making, where it is difficult to understand how AI systems make decisions, is a significant challenge. Boards should encourage the use of transparent and explainable AI models whenever possible. They should also ensure that there are mechanisms to review and challenge AI-driven decisions, especially when those decisions have significant consequences.

How does the business ecosystem affect the board’s work with AI?

In an increasingly connected world, business ecosystems are becoming increasingly important. Boards need to understand how AI affects the dynamics of these ecosystems and how the company can collaborate with partners to take advantage of AI’s capabilities. They should also monitor that AI governance extends to the entire ecosystem, including suppliers and partners.

How will AI affect board work in the future?

AI is expected to transform board work by automating tasks, providing data-driven insights and enabling more efficient decision-making processes. In the future, boards can use AI to analyze data, identify risks and opportunities, monitor performance and communicate with stakeholders.

Main themes and important points

This briefing analyzes the book “AI Leadership for Boards – The Future of Corporate Governance” by Fernanda Torre, Robin Teigland and Liselotte Engstam. The book is aimed at boards and highlights the importance of AI competence for successful corporate governance in an age of rapid technological development.

Main message:

Boards have a responsibility to understand and manage AI, not just as a technological tool, but as a force that reshapes value creation, business models and societal structures.
Boards need to develop skills in two main areas: Guiding AI-powered operational capabilities and Supervising AI governance .
The book presents a “Boards 4 AI Leadership Matrix” as a tool for assessing and developing the board’s AI competence.
AI is expected to reshape future board work by automating tasks, offering data-driven insights and enabling new forms of decision-making.

Key ideas and facts:

The Board’s Role in the AI Era:

“AI can and will be a true force for good if its potential and complexities are embraced by Boards of Directors who will set the tone from the top.” (Helen Pitcher OBE, former President of INSEAD Directors Network).
“The firm must also have a strong digital leadership capability to ensure successful digital transformation, ie digital competence also at the board level.” (The authors).
Boards need to challenge management and themselves to learn about AI and its implications for the future of work.

To guide AI-powered operational capabilities:

This means that the board should be able to guide the collection, processing and analysis of big data, guide AI-driven innovation strategy and guide the participation and growth in the company’s ecosystem.
“As big ideas are getting harder to find, companies are struggling to deliver value; however, a relatively untapped source of value is waiting to be seized: digital experiences.” (Fernanda Torre).
Boards need to evaluate how AI can improve offerings, operations and business models.
Collaboration with partners in the ecosystem is essential to rapidly scale up AI capabilities.

To supervise AI governance:

This includes overseeing data management, ethics and “black box” decision-making, AI cybersecurity, and ecosystem participation and leadership.
“Cybersecurity can be an enormous differentiator. We live in the Reputation Age, not the Information Age. Cybersecurity and Reputation of a Brand are closely linked,” (Anastassia Lauterbach, Professional Board Member).
“Boards need to develop an understanding of not only the gathering but also of the harvesting and analyzing of data.” (The authors).
Boards need to ensure that data is reliable, ethical and protected against cyber threats.
Boards need to establish clear AI governance policies that are aligned with relevant regulations and ethical principles.

Future board work:

“Ultimately, AI will dematerialize, demonetize and democratize all of these services, dramatically improving the quality of life for eight billion people, pushing us closer towards a world of abundance.” (Peter Diamandis, Founder Singularity University).
AI is expected to automate board tasks, provide data-driven insights and support strategic decision-making processes.
Algorithms can analyze board members’ communications, identify potential competitors and predict changes in customer preferences.
AI can complement the board by providing analysis, recommendations and support on complex issues.

Conclusion:

The book emphasizes that AI is not just a technical issue, but a strategic priority for boards. Developing AI skills and adopting a proactive and responsible approach to AI governance is critical to creating long-term value for shareholders, employees and society at large.

People in “AI Leadership for Boards”

Author:

Fernanda Torre: Innovation expert, teacher and research consultant with a focus on design, business and innovation. CEO of Next Agents and guest lecturer at the Stockholm School of Economics.
Robin Teigland: Professor of strategy and digitization at Chalmers University of Technology. Board member of Akademiska Hus and member of IVA. Researchers in social networks, strategy, innovation and entrepreneurship.
Liselotte Engstam: Experienced international leader and board professional with a focus on digital transformation and sustainability. Founder of Digoshen by Innovisa, advisor and speaker in digitization and board work.

People quoted:

Stanislav Shekshnia: Professor and co-director of the INSEAD Executive Development Program. Author of books on board work.
Torben Ballegaard: Chairman of the board and board member of several European companies. Author of the book “Value Adding Boards – Its Focus and Work”.
Helen Pitcher: Former Chair of the INSEAD Directors Network. Board professional with extensive experience from various industries.
Monica Lagercrantz: CEO and partner at Lagercrantz Associates. Founder of Boardclic. Expertise in board evaluations and recruitment of managers and board members.
Martin Huse: Professor Emeritus at the Business School BI in Norway. Author of the book “Value-Creating Boards”.
Jakob Stengel: Global Head of Board Practice at InterSearch. Chairman of the Board Network in Denmark.
Johan Dahlfors: Partner at Bridgepoint, former Board member of FCG Group/Advisens.
Kristian Bentzer: former CEO of FCG Group/Advisens.
Tom Johnstone: Chairman of Combient.
Mats Agervi: CEO of Combient.
Jonas Wettergren: HR director for Combient.
Ronnie Leten: former Chairman of Epiroc.
Jim Hagemann Snabe: Chairman of the Board of Siemens AG and former Chair AP Møller Mærsk. Co-author of the book “Dreams and Details: Reinvent your business and your leadership from a position of strength”.
Peter Diamandis: Founder of Singularity University. Chairman of XPRISE. Co-author of the book “Abundance: The Future Is Better Than You Think”.
Ginni Rometty: former CEO and Chairman of the Board of IBM.
Anastassia Lauterbach: formerProfessional board member. Co-author of the book “The Artificial Intelligence Imperative: A Practical Roadmap for Business”.
Robert Mueller: Former Director of the FBI.
Peter Zemsky: Former Professor of Strategy and Vice President of INSEAD.
Martha C. Nussbaum: Professor of Law and Ethics at the University of Chicago. Co-author of the book “The Fragility of Goodness: Luck and Ethics in Greek Tragedy and Philosophy”.
Jeanne Ross: Researcher at the MIT Center for Information Systems Research.
Marie Curie: Double Nobel laureate and founder of the Curie Institute.

Study guide

This study guide is designed to deepen your understanding of AI leadership for boards, focusing on the challenges and opportunities artificial intelligence (AI) brings to modern corporate governance.

Questions:

Why is it important for boards to have skills in AI in today’s business environment?
What are the two main competency areas the book identifies for AI leadership in boards?
How can boards guide companies’ AI-driven innovation strategy?
What is “black box” decision making in AI and what challenges does it pose for boards?
How do AI cyberthreats differ from traditional cyberthreats? Give examples.
How can boards monitor and manage AI-related cyber risks?
Why is it important for boards to understand and manage companies’ participation in business ecosystems in the context of AI?
How can boards use the “Boards 4 AI Leadership Matrix” as a tool to develop their skills?
Give examples of how AI can change board work in the future.
Why is it important to have a broad societal discussion about the challenges that AI brings, beyond discussions in boardrooms?

Response:

In an era characterized by rapid digitization and increased use of AI, it is crucial for boards to have competence in this area to be able to make well-founded strategic decisions that ensure companies’ competitiveness and risk management.
The two main areas of expertise are: 1) Guiding companies’ operational AI capabilities. 2) To monitor companies’ governance of AI.
Boards can guide AI-driven innovation by: Identifying and prioritizing uses for AI, ensuring access to high-quality data, fostering cross-functional collaboration, and continuously evaluating the impact of AI investments.
“Black box” decision making in AI means that it can be difficult to trace how the AI system arrived at a particular decision. This creates challenges regarding the distribution of responsibilities and transparency towards stakeholders.
AI cyber threats can be more sophisticated and harder to detect than traditional threats. For example, AI can be used to create fake data that tricks AI systems into making wrong decisions.
Boards can monitor cyber risks by: Creating clear data management and AI security policies, implementing robust security systems, and continuously evaluating and updating these systems.
AI is changing the way companies interact and collaborate within business ecosystems. Boards need to understand these changes in order to identify new opportunities and manage risks.
The “Boards 4 AI Leadership Matrix” is a tool that helps boards evaluate their current level of competence in AI and identify areas where they need to develop in order to effectively lead AI implementation.
AI can automate routine tasks, provide deeper insights through data analysis and support strategic decision-making. In the future, AI may even participate in board work as a digital board member.
AI affects the whole of society and it is important to have a broad discussion about its ethical, social and economic implications to ensure the responsible development and use of AI.

Essay questions:

Discuss how boards can balance the need to implement AI to increase competitiveness with ensuring the ethical and responsible use of AI.
Analyze how AI can change the relationship between the board, company management and employees in the future.
What are the biggest challenges and opportunities with integrating AI into board work?
How can boards manage the rapid development in AI and ensure they have access to up-to-date skills?
Discuss how AI can be used to promote sustainability and social responsibility within businesses.

Glossary:

AI (Artificial Intelligence): Computer programs or systems that can perform tasks that normally require human intelligence, e.g. problem solving, decision making and language learning.
Board of Directors: A group of people elected by shareholders to represent their interests and oversee corporate management.
Corporate governance: The set of rules, processes and structures that govern and control a company.
Data strategy: A plan for how a company will collect, store, analyze and use data.
Innovation: Development of new ideas, products, services or processes.
Business ecosystem: A network of companies and other actors that collaborate to create value.
Data governance: A set of policies and processes to ensure that data is accurate, complete and secure.
Cybersecurity: Protection of computer systems and networks against unauthorized access, use, disclosure, disruption, modification or destruction.
Black box: A system or process whose internal workings are unknown or incomprehensible to the user.
Stakeholder: A person or organization that is affected by or can affect a company.

AI Leadership for Boards – The Future of Corporate Governance

Foreword: The authors thank all interviewees and specific individuals who shared valuable knowledge and experiences in AI and digitization.

Summary: The book examines how boards can develop their skills in AI to lead companies in an era of rapid technological development. Two main areas are identified: managing AI-related operational capabilities and monitoring AI-related governance. The book also introduces the “Boards 4 AI Leadership Matrix”, a tool for evaluating and developing boards’ AI competence.

Chapter 1. Introduction: The chapter highlights the importance of board-level AI skills to navigate the rapidly changing digital era. The authors emphasize the need for boards to embrace AI to create value and maintain competitiveness.

Chapter 2. Background: The chapter provides a background to digital transformation and its impact on corporate governance. The concept of “ungoverned incompetence”, where boards lack the competence to make well-founded decisions about digitization, is discussed. Furthermore, results from surveys are presented that show the importance of both digital business capacity and digital leadership for successful digital transformation.

Chapter 3. Managing AI-related operational capacity: The chapter focuses on how boards can manage the operational capacity in AI.

3.1. Managing the collection, processing and analysis of big data in a data strategy: The section emphasizes the importance of understanding and managing the management of data sources, including large and alternative data sets, to train algorithms and create value.
3.2. Managing an AI-driven innovation strategy: The section highlights how AI enables new innovation opportunities and how synergies between innovation management and AI implementation can be created.
3.3. Driving participation and growth in an enterprise ecosystem: The section focuses on the opportunities of orchestrating digital ecosystems and platforms to accelerate AI implementation and value creation.

Chapter 4. Overseeing AI-related governance: The chapter addresses how boards can monitor and ensure responsible AI use.

4.1. Monitoring data management, ethics and “black box” decision-making: The section warns of challenges of lack of transparency in AI systems (“black box” decision-making) and emphasizes the importance of clear guidelines for data management and ethics to avoid reputational damage and legal problems.
4.2. Overseeing AI cybersecurity: The section highlights the importance of rethinking conventional security principles to develop long-term strategies to protect AI systems from cyberattacks.
4.3. Overseeing Participation and Leadership in Business Ecosystems: The section emphasizes the importance of boards ensuring that all actors in an ecosystem adhere to ethical and regulatory guidelines for AI use.

Chapter 5. Boards 4 AI Leadership Matrix – a tool for developing board skills: The chapter introduces the “Boards 4 AI Leadership Matrix”, a tool that helps boards assess their current AI skills and identify areas for improvement in both operational capacity and governance.

Chapter 6. Beyond competence to the board work of the future: The chapter discusses how AI will change the board work of the future, including the use of AI to streamline decision-making processes and the possibility of AI in the future taking on the role of board member.

Chapter 7. Conclusion: The chapter summarizes the main message of the book and emphasizes the importance of boards actively working to develop their AI skills to navigate the digital era. The authors call for continued research and discussion around AI’s impact on corporate governance and society at large.

References: A comprehensive list of scientific articles, reports and other sources used in the book.

The Authors: Presentation of the book’s three authors, including their background and expertise in AI, digitization and corporate governance.

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AI Leadership for Boards – The Future of Corporate Governance At Amazon

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Events Autumn 2024 and Digoshen Calendar Autumn 2024

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“Boards Oversight of Sustainability“

About Liselotte Engstam and Digoshen

This blog post was originally shared at the blog of Digoshen www.digoshen.com, and the blog of the Digoshen founder www.liselotteengstam.com

At Digoshen, we work hard to increase #futureinsights and help remove #digitalblindspots and #sustainabilityblindspots. We believe that Companies, Boards, and Business Leadership Teams need to understand more about the future and the digital & sustainable world to fully leverage the potential when bringing their business into the digital & more sustainable age. If you are a board member, consider joining our international board network and master programs.

Welcome to also explore the Digoshen Chatbot on AI Leadership for Boards and Boards Impact Forum, where the Digoshen Founder is the Chair.

Find a link to Digoshen Chair Liselotte Engstam Google Scholar Page

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AI Leadership for Boards – Book insights