In an AI-driven era, boards must navigate both the rapid advancement of artificial intelligence and its transformative effects on business strategy, data management, and workforce dynamics. Insights from MIT Sloan’s report Leading with AI and recent McKinsey research, highlight critical steps for boards to support sustainable and responsible AI integration. Below, we explore how boards can leverage AI for competitive advantage, ensuring its alignment with core values and long-term objectives.
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Building a Strategic AI Framework
AI is not simply a trend; it requires a strategy that connects directly with business objectives. Boards should champion the development of an AI playbook that answers key questions: What critical problems can AI solve, and how will AI support core business strategies? This exercise, recommended by Paul McDonagh-Smith from MIT, allows boards to direct resources toward AI initiatives that promise clear value and reduces the risk of misalignment or wasted investment.
In addition, ensuring that an organization’s data is “AI-ready” is crucial. AI’s success hinges on data that is complete, governed, and managed with robust oversight. Boards should oversee data governance frameworks, ensuring alignment with data privacy standards and ethical considerations. As highlighted by McKinsey, treating data as a strategic asset aligns with emerging “arena” dynamics—high-growth sectors where AI plays a transformative role.
Embracing a Culture of Responsible AI Use
As companies experiment with AI, boards must ensure an organizational culture that balances innovation with accountability. Promoting a mindset that values learning from AI pilots and proofs of concept, while embedding ethics into every AI usage, is crucial for sustaining responsible AI growth.
The potential for AI to introduce biases or misinform makes transparency and responsibility essential. Boards should advocate for systems that detect and mitigate biases, ensuring that AI-driven processes are held accountable to ethical standards. Some boards may benefit from establishing a formal technology or AI ethics committee to regularly review AI implementations and safeguard brand integrity and stakeholder trust.
Up-skilling and Redefining Roles
AI is redefining work, creating a “jagged technological frontier” where some tasks are suited to automation while others require human oversight. Recent studies show that AI can boost productivity by as much as 40% for skilled workers when applied correctly. However, boards must ensure investments in upskilling are strategic, bridging skill gaps essential for AI’s effective integration.
Encouraging roles that complement AI can boost organizational efficiency. For example, using AI to handle routine analytics frees human expertise for complex problem-solving and strategic planning. This approach not only maximizes AI’s value but also aligns with McKinsey’s recommendation to embrace big moves and targeted resource allocation for impactful outcomes.
Embracing Experimentation and Speed
Organizations are increasingly leveraging generative AI to accelerate time to market, improve customer interactions, and streamline internal processes. Companies like Pfizer, for instance, have used generative AI to reduce time-intensive document classification processes, allowing quicker progress in drug development.
Boards should encourage a two-tier approach to AI strategy: fast-paced experimentation coupled with long-term planning. This dual approach allows organizations to capture quick wins while integrating learnings into a more sustainable, strategic framework. Leveraging generative AI to enhance efficiency can position organizations for competitive advantage, especially in industries where speed and responsiveness are critical.
Redefining Board and C-Suite Collaboration
An effective AI strategy hinges on continuous, close collaboration between the board and the C-suite. Boards should go beyond traditional oversight, actively guiding AI initiatives, especially in discussions around ethical, regulatory, and social implications. To manage AI-related risks, boards can adopt a dynamic capabilities approach, ensuring that they adapt as technology and regulations evolve.
As AI capabilities grow, so too do the responsibilities of boards to lead with insight, agility, and foresight. By championing responsible AI use, fostering a culture of learning and accountability, and aligning AI with core strategies, boards can steer their organizations toward a sustainable, AI-powered future.
Strengthening Board Competencies in AI
Technology expertise in the boardroom has become indispensable. Boards that prioritize “tech-savvy” leadership—such as bringing on members with technology expertise or creating technology committees—are better positioned to oversee transformative AI strategies. Regular training sessions on emerging AI technologies and industry applications can help boards remain current, empowering them to make informed decisions and guide their organizations toward a sustainable, AI-driven future.
Contribute to Research and Learn More
We are currently updating our Academic research AI Leadership for Boards originally done with Combient and the Wallenberg Companies, led by Professor Robin Teigland, Research Scientist, Chair and NED Liselotte Engstam and Research Scientist, CEO and Board Member Fernanda Torre and Review by INSEAD and MIT, and now updating with support form the Swedish Internet Foundation (Internetstiftelsen).
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Conclusion: Leading with Insight, Agility, and Foresight
As AI capabilities expand, so do the responsibilities of boards to lead with insight, agility, and foresight. By fostering a culture of responsible AI use, encouraging continuous learning and accountability, and aligning AI initiatives with core business strategies, boards can effectively guide their organizations toward a sustainable, AI-powered future. The evolving landscape demands that boards stay informed and proactive, ensuring that AI not only drives competitive advantage but also aligns with the values and long-term mission of the organization.
Frequently Asked Questions
What is the board’s role in developing an AI strategy?
Boards should champion the development of a strategic AI framework that aligns with the organization’s core business objectives. This involves identifying key problems AI can solve and ensuring that AI initiatives contribute to the overall business strategy. Boards should also oversee data governance frameworks to ensure data is “AI-ready,” meaning complete, well-governed, and managed with robust oversight.
How can boards foster a culture of responsible AI use?
Boards are crucial in shaping an organizational culture that balances AI innovation with accountability. They should promote a mindset that values learning from AI pilots and proofs of concept while embedding ethical considerations into AI usage. This includes advocating for systems that uphold transparency, responsibility, and bias detection. Boards may also consider establishing committees dedicated to AI ethics and risk mitigation.
What is the “jagged technological frontier” in the context of AI and the workforce?
The “jagged technological frontier” refers to the uneven impact of AI on the workforce. While AI can automate certain tasks, others require human oversight. Boards must recognize this disparity and ensure the organization invest in up-skilling initiatives to bridge skills gaps and redefine roles to complement AI capabilities.
What is the board’s role in managing the risks associated with AI?
Boards should actively engage in discussions about AI’s ethical, regulatory, and social implications. They can adopt frameworks for dynamic board capabilities, ensuring they adapt to evolving AI technologies and regulations. By fostering a culture of accountability and transparency, boards can mitigate risks and build stakeholder trust.
How can boards encourage experimentation with AI while ensuring long-term strategic alignment?
Boards should encourage a two-tier approach to AI strategy: rapid experimentation alongside long-term planning. This dual approach allows organizations to capture quick wins through pilot projects while integrating learnings into a sustainable, strategic framework.
How does the use of generative AI contribute to competitive advantage?
Generative AI can accelerate time to market, improve customer interactions, and streamline internal processes. Organizations like Pfizer have utilized generative AI to expedite document classification, leading to faster drug development. By leveraging generative AI for enhanced efficiency, organizations can gain a competitive edge, particularly in industries where speed and responsiveness are paramount.
What does effective collaboration between the board and C-suite look like in the context of AI?
Effective AI strategy requires ongoing collaboration between the board and the C-suite. Boards must go beyond traditional oversight and actively guide AI initiatives. This includes engaging in discussions about AI’s ethical, regulatory, and social implications. The C-suite should provide the board with the necessary information and insights to make informed decisions.
How can boards stay informed about the rapidly evolving landscape of AI?
Boards can stay informed about AI advancements through continuous learning and engagement with industry experts. This includes attending conferences, workshops, and seminars focused on AI and its implications. Board networks that provide webinars with peer exchanges, content and board tailored training programs like Boards Impact Forum are important sources. Additionally, boards can leverage resources from organizations like INSEAD, MIT Sloan, Harvard and IMD, and contribute to research initiatives to deepen their understanding of AI’s evolving landscape.
Glossary of Key Terms
- AI Playbook: A strategic document outlining how an organization will leverage AI, including identifying target problems, aligning with business goals, and outlining implementation plans.
- AI-Ready Data: Data that is complete, well-structured, governed, and easily accessible for AI algorithms to process and learn from.
- Generative AI: A type of AI that can create new content, such as text, images, or code, based on existing data patterns and prompts.
- Jagged Technological Frontier: A concept describing the uneven impact of AI, where certain tasks are automated while others still require human expertise, creating a need for workforce adaptation and upskilling.
- Dynamic Board Capabilities: The ability of a board to adapt and evolve its skills, knowledge, and processes to effectively oversee AI initiatives and manage associated risks in a rapidly changing technological landscape.
Earlier Relevant Blogposts
Learning More
MIT Sloan’s report, Leading with AI
Bending Time in the age of GenAI- Is your Board Ready?, Accenture
The Next Big Areans of Competition, McKinsey
Eight shifts that will take your strategy into high gear, McKinsey
Webinars, Peer Exchanges and Events
Events Autumn 2024 and Digoshen Calendar Autumn 2024
Board Programs
“Boards Oversight of Responsible AI”
“Boards Oversight of Sustainability“
About 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
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