AI in Strategic Decision-Making: can a sailing crew use AI to outsmart competition? The answer turns out to be ‘yes’
“We knew that if we wanted to win, we had to be smarter—not just faster,” said Peter Burling, skipper of Emirates Team New Zealand. “AI gave us insights we couldn’t get on our own.”
Using AI in strategic decision making in sports is no longer a futuristic dream. It’s a reality.
Here’s an example:
In the 36th America’s Cup, Emirates Team New Zealand pioneered a groundbreaking approach. They developed a digital twin strategy—an AI-driven virtual sailor. This system could simulate countless race scenarios without human limitations.
“It was like having an extra crew member who never slept,” recalled one of the engineers. “The AI was running tests even while we were having breakfast.”
The impact was immediate. The team could test designs and strategies 24/7. What used to take months now took days.
The AI system analyzed wind conditions, sail angles, and opponent tactics—constantly refining their approach.
“It wasn’t just about speed,” said Blair Tuke, a key crew member. “AI helped us make better decisions, faster.”
This strategic use of AI in decision-making didn’t replace the sailors. It enhanced them.
The result? A decisive 7-3 victory over Luna Rossa Prada Pirelli.
5 lessons from the world of sailing to use AI in your strategic decision making
If AI can revolutionize sailing, what can it do for your business?
Let’s dive in this great example and discover how we all can use AI for better decision making in our business.
Lesson 1: AI Doesn’t Change Your Strategy—It Changes How You Create It
AI does not replace strategic thinking. It transforms the strategy creation process. Many companies focus too heavily on fully autonomous AI strategies. They miss simpler opportunities in key areas like data analysis, identifying patterns, and reducing biases. In other words: successful companies use AI to enhance, not replace, the core business strategy principles.
Winning with AI: America’s Cup Case
In the 2021 America’s Cup, Emirates Team New Zealand combined traditional sailing expertise with AI technology. They ran AI simulations analyzing past races, wind patterns, and hydrofoil performance.
For example, their AI system identified a new foil design that significantly improved stability and speed. They rigorously tested this in over 50 simulation scenarios before implementation. AI improved their boat design and tactical decision-making, turning what would have been educated guesses into solid, tested advice.
“The technology that our design team produces is mind-blowing! We have a room full of PhDs and rocket scientists, but they’re also extremely practical.” — Grant Dalton, CEO of Emirates Team New Zealand
Actions You Can Take Today:
- Map Your Strategy Process: as with the sailing team, you can carefully map out your existing strategy process. Identify which stages can benefit from AI-driven data analysis to enhance accuracy, efficiency, and insight in your decision-making. Remember: keep it small.
- Test Your Strategic Assumptions: similar to how the sailing team used simulations, you can apply AI tools to systematically test your strategic assumptions. This helps ensure your strategic decisions are based on solid, data-supported insights rather than intuition alone.
- Educate Your Leadership on AI: just like the sailing team invested in integrating AI knowledge for everyone on board, you should actively educate your team members on AI fundamentals. This ensures that decision-makers recognize and effectively utilize AI’s strategic potential.
Lesson 2: Winning Strategies Are Scenario-Based and Adaptive
Traditional business strategy cycles span years. With AI, you can drastically shorten your strategy cycle, making even real time adjustments. Generative AI can rapidly create and evaluate various scenarios, helping you to manage your strategic options dynamically. And I don’t have to tell you that flexibility in strategic planning is crucial as markets and technologies evolve more quickly than ever before.
Winning with AI: America’s Cup Case
The sailing team used scenario’s as well. The AI system simulated thousands of race scenarios, considering wind changes, competitor tactics, and hydrofoil performance in different sea conditions. Real-time scenario analysis enabled them to adapt swiftly during races, changing their approach based on AI-predicted outcomes. This scenario-based adaptability provided a significant competitive advantage over teams that stuck to rigid strategies.
“The crucial moment came when [the AI bot] started beating the sailors… That was the moment when we thought, OK this is going to be useful.” — Dan Bernasconi, Chief Designer of Emirates Team New Zealand
Actions You Can Take Today:
- Identify Key Uncertainties: just as the sailing team pinpointed critical uncertainties, you can identify the major unknown factors impacting your business. Use AI-driven scenario modeling to explore and prepare for these uncertainties comprehensively.
- Develop Flexible Decision Frameworks: similar to the sailing team’s approach, create adaptable strategies that can quickly respond to AI-generated insights. Establish frameworks that allow dynamic adjustments, ensuring agility in your decision-making process.
- Run Small-Scale Scenario Tests: as Team New Zealand tested numerous scenarios, you can utilize AI to simulate various market or operational conditions. Regularly run small-scale tests to evaluate potential strategies and responses, enabling you to act decisively in changing circumstances.
Lesson 3: AI Increases Strategic Flexibility But Introduces New Risks
Integrating AI into strategic decision-making allows for faster, data-driven choices. It also introduces new challenges such as ethical concerns and cybersecurity threats. Blind trust isn’t good. AI-driven decisions should always be checked and validated by real people. This human judgment ensure reliability and accountability. To do so, we need to develop governance frameworks.
Winning with AI: America’s Cup Case
AI-driven simulations gave Team New Zealand the capability to make rapid tactical decisions. There were risks as well. To manage these risks, the team adopted a human-in-the-loop approach. AI recommendations were consistently validated by seasoned sailors, balancing high-speed AI insights with real-world expertise and instincts. This approach ensured that their strategy remained fast yet accurate and reliable.
Dan Bernasconi, Chief Designer of Emirates Team New Zealand, highlighted the importance of human expertise in the design process:
“Good design is having a clear understanding of the problem you’re trying to solve; being open to exploring as wide a realm of solutions as you can; focusing on the best options; and then thoroughly optimising the chosen solution.”
Actions You Can Take Today:
- Assess AI-Related Risks: just as Team New Zealand carefully validated their AI recommendations, you can perform thorough AI risk assessments. Evaluate ethical issues, biases, and cybersecurity risks associated with your AI systems to ensure safe and fair outcomes.
- Implement Transparent and Explainable AI: following the sailing team’s practice of maintaining clear and understandable AI recommendations, adopt AI solutions that offer transparency. Ensure your AI systems clearly communicate the rationale behind their decisions, making it easier for human experts to validate and trust AI-driven insights.
- Establish Clear AI Governance Policies: similar to how the sailing team integrated clear protocols for validating AI suggestions, your organization should create rules for AI use. Outline responsibilities, decision-making authority, and ethical standards to effectively manage AI’s strategic implementation and reduce risks.
Lesson 4: AI in Strategic Decision-Making requires a New Way of Learning
Successful companies use AI not just as an analytical tool but as a system for continuous learning and improved decision-making. AI can uncover patterns humans often overlook and supports ongoing optimization. The goal is not just generating insights but enabling better decisions. This is key. Read it again! Also, we should shift from a fixed mindset to a growth mindset. This will help to become comfortable learning from AI-driven experiments and using them to our advantage.
Winning with AI: America’s Cup Case
Team New Zealand viewed AI as a dynamic learning partner, not a static tool. Their AI system continuously refined its predictions based on past races and training sessions. Each iteration helped improve their boat’s responsiveness and crew coordination, significantly enhancing their overall performance. This openness to innovative ideas allowed the team to constantly evolve their methods.
Actions You Can Take Today:
- Encourage AI-Driven Experimentation: just as Team New Zealand embraced continuous experimentation, your organization should launch small AI-driven pilot projects. Use these experiments to integrate AI into your decision-making processes, learning from each iteration.
- Measure AI Impact: follow the sailing team’s approach by tracking and evaluating the outcomes of AI insights. Regularly measure how AI-driven decisions affect your business and adjust strategies accordingly to maximize results.
- Foster a Learning Culture: similar to the approach taken by Team New Zealand, actively train your teams to interpret and leverage AI-driven insights effectively. Cultivate a culture of ongoing learning, helping employees confidently make informed strategic decisions.
Lesson 5: AI Transformation Is a Cultural Shift, Not an IT Project
Many organizations underestimate the cultural shift that comes with AI. Implementing AI affects how people work, make decisions, and drive innovation. Successful AI adoption requires more than just technology. It needs a culture that values learning and experimentation. Leaders must treat AI adoption as a strategic and organizational transformation, not merely a technology upgrade.
Winning with AI: America’s Cup Case
The sailing team’s success required a team-wide cultural shift. The sailors learned to trust AI-generated insights, combining them with their experience rather than relying only on intuition. This transition to data-driven decision-making was critical.
Grant Dalton emphasized this cultural transformation, stating clearly, “We’re a technology organization that goes sailing.”
Actions You Can Take Today:
- Engage Leadership in AI adoption: similar to the sailing team, make sure your leaders visibly champion AI-driven changes. They should actively support and communicate the strategic value of AI to ensure successful adoption.
- Clearly Communicate AI benefits: follow the sailing team’s example by transparently addressing employee concerns about AI. Emphasize how AI enhances rather than replaces human roles, helping employees see AI as a supportive tool for their work.
- Create AI Change Agents: identify and empower internal advocates within your organization. These AI change agents can drive enthusiasm, address resistance, and promote AI-driven innovation across your teams.
Your challenge is similar to using AI in strategic decision-making in sailing. You should focus on leveraging AI-driven insights to strengthen, not replace, human expertise to boost your business strategy and outwit your competition.
Are you ready?
