Lessons From Combat: What Navy SEALs Can Teach Us About AI Transformations
There are many Navy SEALs who have made second-careers writing management books and giving speeches at Fortune 500 companies. Whether it’s the self-discipline promoted by former SEAL Jocko Willink, or the dedication to teamwork embedded in the culture of the armed forces, many teachings can be transferred to the world of business. There is one lesson, though, that stands out for managers contemplating an AI transformation.
When navigating an urban environment, special forces operators can be heard saying “Slow is smooth and smooth is fast.” What they mean is that the squad needs to be moving at the ideal pace. They must maintain a speed that is slightly over a walk, but not quite a jog or a run. Maintaining this speed allows for a complete 360-degree threat assessment and quick pivots and updates to their strategic plan. When thinking about how to proceed in the uncertain environment of AI, the same concept applies.
To apply the Navy SEALs strategy in business requires brave leadership. Often management teams are caught up in the hype and fear their company will get left behind. This causes them to make blind investments in AI that do not align with company values and do not provide an adequate return on investment. Instead of charging ahead at full speed and risking casualties, a more measured approach is better.
Companies can use a 3-step approach to move forward slowly and smoothly- resulting in quicker advancement in AI capabilities than their competitors.
Step 1: Create a Plan
Creating a plan for AI implementation is about more than just AI. It’s about dissecting your business model and taking a deep look at structural weaknesses and where improved decision making could lead to better customer experiences, increased revenue, and reduced costs. This exercise does not need to mention AI or other technologies, but it must be honest, realistic, and exhaustive. AI has the ability to completely revamp business models if management allows it. This will only happen for companies who put in the initial hard-work up front.
Step 2: Experiment & Transform
Once the planning and internal reflection occurs, the company should have an idea of the action needed to begin their AI implementation efforts. For the majority of companies, this looks like a digital transformation. This involves transferring legacy systems and paper processes to the digital world and creating unified data sources that can be used for future AI applications. These digital transformations are often long, frustrating, and full of failures. Companies must lean-in to the failure and be willing to dust themselves off and keep going.
Many companies who encounter failures and hurdles during their digital transformation react by putting their AI strategy on hold. Management believes that they should wait until everything is digitized and the company has a perfect database with all the data available. Rather than focusing wholly on the digital transformation, companies should begin experiments and small test-cases for AI applications. By building and testing with experiments, companies can improve their internal AI capabilities and grow their data science team from the inside. These companies will be several steps ahead when the new shiny database finally comes to life.
Step 3: Grow & Scale
With the digital transformation complete and several AI experiments under their belt, management can finally move ahead with large scale AI implementation. This is the time where the technology can truly affect the operations and profitability of the company. They have the data in a format that allows for large scale application and may already have several ideas and test-cases ready to bring to market.
By moving at the ideal pace, management can avoid getting stuck standing still or ploughing forward too quickly. Slow movement puts you out of business as competitors begin capitalizing on AI implementation. Moving too quickly puts company money at risk as large investments are lost. When the world is screaming to innovate and get moving on AI, management would be best served to remain calm and remember, “Slow is smooth and smooth is fast.”