Board members must navigate an unpredictable landscape shaped by inflation, technological shifts, and evolving customer expectations. Leveraging data and AI strategically is essential for sustained growth and profitability.
This comprehensive guide synthesizes strategies from private equity (PE) firms, leading companies, and recent research to inform board-level decisions on managing disruption.
Find an upcoming webinar further down on how Boards can develop board practices that impact corporate renewal and company performance, based on academic research.
Understanding Disruption and Technology’s Role
Macro Challenges:
- Inflation, geopolitical tensions, and demographic changes add uncertainty to global markets.
- CEOs are concerned about external factors like climate change and emerging technologies.
Technology’s Influence:
- AI, automation, and pervasive connectivity offer new opportunities but require rapid adaptation.
- Despite optimism, many organizations struggle with integrating new technologies effectively.
What Boards Can Learn from the Leading Corporate and Private Equity Digital Playbook
Train and encourage employees:
- Train Board, Management and all staff on benefit, risk and usage of AI
- Assign objectives incl productivity improvement and sharing
- Encourage usage of digital tools including AI, while minding confidential data sharing, incl tools as ChatGPT/Copilot/Gemini etc and Github Copilot
Value Creation through Focused Growth Initiatives:
- PE-backed companies prioritize growth initiatives like pricing optimization and demand forecasting that directly impact enterprise value.
- Switching to subscription-based models or expanding product lines creates recurring revenue streams.
Strategic Alignment of Digital Projects:
- PE firms pursue digital projects that measurably enhance EBITDA or valuation multiples.
- Customer journey mapping identifies high-value customer segments, ensuring targeted marketing and higher ROI.
Predictive and Prescriptive Analytics for Decision-Making:
- Growth models provide insights into performance drivers, helping boards prioritize investments with the highest ROI.
- Accurate forecasting aligns inventory, staffing, and production with predicted demand, aiding strategic planning.
Implementing Strategy and a Repeatable Playbook:
- Ensure AI integration into Corporate Strategy, requiring significant operational changes, including revisting core objectives and management practices
- Standardized frameworks ensure consistent, rapid execution across businesses. Boards should adopt scalable digital transformation frameworks.
- Cross-sector solutions allow boards to apply strategies from other industries.
- Ensure evaluation for build or buy approach of AI capabilities
Fostering a Culture of Data-Driven Decision-Making:
- C-suite executives should understand the importance of data to align organizational strategy.
- Showcasing early wins eases resistance, encouraging broader adoption.
Case Studies: AI Strategies in Action
Moderna:
- Moderna’s AI adoption streamlines legal, research, and manufacturing processes.
- Initiatives like “mChat,” and 750 internal AI chatbots launched in two months, support internal efficiency and AI education.
- Moderna aims to launch 15 new products in five years with fewer people, capitalizing on AI-driven efficiencies.
Klarna:
- Klarna replaced 700 support roles with an OpenAI chatbot, significantly improving customer service response times and access.
- The company balances workforce reduction with strategic AI integration, aiming for responsible growth and transparency.
JPMorgan Chase:
- JPMorgan integrates AI into various banking operations, targeting $1.5 billion in business value from AI initiatives in 2023.
- It has 400 active AI use cases and leads the banking sector in AI patent applications.
Siemens:
- Siemens integrates AI to create an “industrial metaverse,” partnering with Nvidia to develop digital twins that improve industrial automation.
- A new AI Copilot developed with Microsoft enhances worker productivity.
Insights from Generative AI Research and Labor Market
Generative AI as a General-Purpose Technology:
- Generative AI has rapid improvement, pervasiveness, and complementary innovation that make it transformative across industries.
- By one estimate, 80% of jobs can be completed at least 10% faster using generative AI without loss of quality.
Faster Adoption and Economic Growth:
- Generative AI’s ease of diffusion means its productivity gains will be realized faster than historical technologies like steam engines.
- The technology can accelerate global GDP growth and help address skill gaps and labor shortages through upskilling.
New Skills and Jobs:
- Generative AI will increase demand for new skill sets while reducing the need for certain existing tasks, emphasizing reskilling efforts.
- It can significantly boost productivity across sectors by complementing human skills, particularly for newer employees.
Guarding Against Bias
Guidelines and Audits:
- Establish comprehensive guidelines and policies that mandate fairness and transparency in work practices and AI applications.
- Ensure AI models are trained with diverse data sets to reflect a broad range of demographics and reduce bias.
- Regularly review AI systems to detect any biases, examining both the algorithms and the outcomes they generate.
Engagement and Training
- Incorporate feedback from a wide array of stakeholders to understand the impact of AI decisions from multiple perspectives.
- Implement training programs that raise awareness about AI biases among employees, particularly those in decision-making roles.
Action Points for Board Members
Adopt a Strategic revisit including AI :
- Growth Modeling and Insights: Invest in advanced growth modeling to identify key value drivers and gain insights into factors impacting performance. Leverage AI and predictive analytics to forecast demand, identify emerging trends, and uncover new growth opportunities.
- Technology Roadmap Alignment: Create a clear roadmap that aligns data initiatives with long-term business objectives. Ensure technology adoption is prioritized based on potential ROI and relevance to the organization’s strategic vision.
- Regular Reviews: Schedule consistent reviews of technology initiatives to ensure they remain aligned with changing market conditions, emerging technologies, and evolving business goals.
Build an Agile Workforce:
- Training and Development: Invest in upskilling and reskilling programs that empower board, leadership team and employees to better utilize AI and data-driven tools in their roles. Focus on building a culture of continuous learning where innovation is encouraged and recognized.
- Cross-Functional Teams: Encourage the formation of interdisciplinary teams to promote knowledge-sharing and diverse perspectives. This approach enhances collaboration, drives creativity, and ensures data initiatives are integrated across the organization.
- Change Management: Implement change management strategies that help employees understand the benefits of new technologies and alleviate concerns about workforce reductions.
Align Digital Initiatives with Clear ROI:
- KPIs and Metrics: Establish clear key performance indicators (KPIs) to measure the effectiveness of digital transformation efforts. Metrics should include financial, operational, and customer-centric measures that directly tie back to overall business goals.
- Portfolio Management: Treat digital initiatives like a portfolio, continually assessing each project’s performance and re-allocating resources to those providing the highest ROI.
- Value Chain Analysis: Evaluate how digital transformation impacts the entire value chain, ensuring all digital projects contribute meaningfully to customer satisfaction and profitability.
Overcome Cultural Barriers:
- Data-Driven Decision Making: Promote a mindset where data is integral to decision-making. Encourage leaders and employees to rely on data insights rather than intuition alone.
- Leadership Commitment: Establish buy-in from board and leadership by demonstrating the tangible benefits of AI and data initiatives through pilot projects or early successes. This commitment will trickle down and help drive cultural change across the organization.
- Transparent Communication: Foster trust through transparent communication of digital transformation goals, addressing employee concerns and emphasizing the role of technology in future-proofing the business.
Conclusion
Board members are crucial in navigating disruption by focusing on growth initiatives, fostering data-driven cultures, and adopting scalable frameworks. The private equity digital playbook, combined with generative AI research and strategies from industry leaders like Moderna, Klarna, and JPMorgan, offers a roadmap to harness AI and data for growth while future-proofing businesses.
References;
- Alix Partners Disruption Index, Finding a a profitable Path to Growth, by Alix Partners
- Leveraging Digital, Data and AI technologies to increase Enterprise Value, How PE Firms Are getting it right, BY INSEAD Zimmerman, Evengeio et al
- Moderna and Klarna Case from own and Open AI announcments
- Generally Faster: The Economic Impact of Generative AI by Andrew McAfee, MIT and Visiting Fellow, Technology & Society at Google
- CB Insights AI strategies for 11 of the world’s largest companies
- GPTs are GPTs: An Early look at labor market impact potential of Large Language Models by OpenAi and University of Pennsylvania
- Dynamic Board Capabilities: Developing Board Practices that Impact Renewal and Performance, By KTH, INSEAD and Digoshen
- Insights from ongoing research and latest program “Boards Oversight of Responsible AI for Value Creation” by Boards Impact Forum and Digoshen
- Webinar: A Manager and an AI walk into a Bar: Does ChatGPT make Biased Decision Like we Do? by INSEAD
- Patriarchical AI: How ChatGPt can Harm a Womans Career by LSE
- Women Leading the Conversation in the Boardroom; Innovation and AI by NACD California
- Interview with Silo AI CEO Peter Sarlin in Dagens Industri 240506
- OECD Updated AI Principles by OECD 240503
Updating Research and Book on AI Leadership for Boards
Professor Robin Teigland, Chalmers University of Technology , Fernanda Torre, affiliated with House of Innovation at Stockholm School of Economics and Digoshen Founder Liselotte Engstam, are updating the research and book – AI Leadership for Boards the future of corporate governance. Do you have any perspectives or input we should ensure is integrated, do let us know and message us at LinkedIn or via Website.
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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
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.
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