Winning the AI Marathon

A Guide to Leveraging AI for Organizational Success

A rapidly developing field, generative artificial intelligence (AI) is often misunderstood and misused, especially in the workplace. However, when implemented appropriately, AI can instigate worthwhile discussion and drive meaningful connection. As organizational development consultants, we can use AI to help with research and data analysis, because doing so allows us to spend more time on the human interaction component of our work, which is arguably the most essential element.

As someone who loves marathons, I can’t help but compare the process of using AI to running a race. Like a marathon, using AI is all about preparation, pacing, and reaching the finish line. And, just like marathoners, organizations need a solid strategy to succeed. So, lace up your running shoes—here’s a step-by-step guide to crossing the AI finish line!

Set the Course: Focus on Goals and Outcomes

Before you start using AI, you need to pick your race. Are you optimizing customer service, boosting employee engagement, or spearheading another sprint in your organization? Start with the end in mind. Your goals are your finish line—know where you’re heading and determine how you’ll know when you’ve reached the end. Imagine that your goal is to improve employee engagement by 15% in six months. That’s your marathon. Your outcome is the medal waiting for you at the finish line.

Warm-Up and Stretch: Ensure Your Data is Accurate

Running AI without good data is just as painful as running a marathon without warming up (speaking from experience on both perspectives). Clean and accurate data is your warm-up, ensuring you don’t pull a muscle (or, in this case, end with skewed results). It is essential to check the quality of the data you’re feeding AI before you start running.

For example, to improve employee engagement, you might start by collecting employee surveys and feedback. But before utilizing AI, check for missing data or potential biases. Think of this as stretching—once you’ve prepared your data, you’re less likely to face hurdles down the road.

Choose Your Running Shoes: Determine Which AI Tool to Use

AI tools are like shoes—there’s no one-size-fits-all. You’ll need to find the right pair of running shoes to fit your goals. In other words, are you looking for AI that can analyze feedback or predict trends? Choosing the right AI tool will make the entire race smoother.

In your race to improve employee engagement, you might select an AI tool that specializes in analyzing text data from surveys. Like shoes built for distance, not speed, this tool is designed for the long haul required to analyze hundreds of employee responses.

Start the Race: Run the AI Analytics

And we’re off! You’ve prepped, you’ve warmed up, and now you’re hitting the track with AI. As AI analyzes your data, it will highlight patterns to help you navigate to the finish line. The data is like a course map, revealing twists, turns, and inclines along the way. But it’s up to you to interpret the route and avoid any misleading detours. After AI’s initial analysis, it’s time to refine the results and adjust your strategy to stay on course.

Now, let’s say the AI tool uncovers a surprising insight while analyzing survey results: employees in mid-level management feel unsupported in their career growth. Just like hitting that perfect stride in a marathon, AI has given you a boost by pointing out exactly where the engagement issue lies.

Teamwork on the Track: Incorporate the Human Element

Even the best runners don’t go at it alone; they have coaches, supporters, and pacers who help them along the way. In the world of AI, humans are the ultimate pacers. AI’s insights are powerful, but human judgment and creativity lead to practical, real-world solutions.

For that reason, as you refine your employee engagement plan, you might reach out to upper management to gather more data. It’s like getting your second wind in a marathon! You’ll bring key stakeholders together to collaborate on programs that address mid-level managers’ concerns. While AI pointed you in the right direction, it’s the human touch—collaborative meetings and brainstorming sessions—that turns insight into action.

Cross the Finish Line: Implement and Track Progress

The hard work is almost done, and the finish line is in sight; and yet, it’s crucial to stay focused on the goal. In a marathon, it’s easy to let exhaustion or distractions throw you off course, but you must keep your eyes on the prize. This means rolling out your project with precision, ensuring every component is in place and functioning as intended. Regularly track the results, much like checking your pace and timing as you near the race’s end. Adjust your strategy if unexpected obstacles arise or new opportunities to enhance your outcomes present themselves.

Case in point: as you roll out new career development programs for mid-level managers, you’ll continue to track improvements in engagement. It’s like sprinting to the finish line. You’re close to hitting that 15% increase, but you’ll keep adjusting to ensure you finish strong and meet your goals.

Whether you’re chasing down business goals or marathon personal records, the key to success when using AI is the same: preparation, teamwork, and proper use of resources. But remember, it’s not all about the technology; it’s about how you, the runner, navigate the course and adjust as needed.

Stay tuned for next week’s installment of this three-part series, which will explore the pros and cons of AI in the workplace.

About the Author:

Giuseppe (Joey) Nespoli, MSOD, CVS, has 20 years of experience designing and facilitating on-target, impactful workshops and trainings for a wide range of audiences and industries. He employs a variety of techniques, multimedia design, and technical equipment, bringing his unique blend of warmth and humor to influence and enhance collaboration in meetings and workshops. His passion for serving others has inspired his research into how hybrid workplaces and generative AI can better support his clients.