I’m a CEO and have run 18 Ironman races, and AI racing ROI is no different
I’ve spent two decades competing in Ironman triathlons, grueling one-day competitions totaling more than 140 miles. I have spent more time leading high-growth companies than… Google and Dropbox To Fresh Works.
You could say I’ve been running with Need for Speed my entire adult life. If there’s one thing these experiences have taught me, it’s that most companies are getting it wrong in the AI race.
Recent data from Bain & Company shows this 95% Of American companies use generative AI in some form, but only 5% of companies see significant value from their investments in artificial intelligence.
I believe this happens because many business leaders, like novice athletes, treat AI like a sprint – chasing speed, hype, and short-term gains, while expecting long-term sustainable results. In both racing and business, success depends on self-control, building endurance, and maintaining focus on the long game.
The Iron Man AI Playbook
Over the course of 18 Ironman races, I’ve learned that the real key isn’t strength or speed, it’s structure. Whether you’re training for race day or leading a company through the shift to AI, you need a set of principles to keep you grounded and disciplined during uncertain (and sometimes stressful) times. The three I stand by are:
- Play to your strengths
- Widely uncomplicated
- Consistency over chaos
As CEO, these principles have guided me in building, scaling, and leading through one of the most revolutionary transformations the SaaS industry has seen in decades.
Play to your strengths
In my first few Ironman races, I tried to keep up with the veteran swimmers. Big mistake. I burned too much too soon and paid for it the rest of the way. Ultimately, I learned that performance—in racing or business—isn’t about keeping up with someone else’s speed. It’s about knowing your strengths, then moving towards the goal and trusting your racing plan.
The same lesson applies when developing an AI strategy. Every company wants to imitate the playbook of the Googles or OpenAIs of the world. But not every company has to do this, and that’s not a bad thing. As much as I admire my former colleagues at Google, we’re not trying to imitate them. Our race is different. Our landscapes, resources and goals are not the same.
The leaders of the AI race are the ones who know who they are and who they are not. Not every organization needs to become an AI research lab, developing new models and infrastructure from scratch. The best leaders will use AI to amplify the strengths of their business, such as improving customer experiences, streamlining processes, and increasing efficiency, without losing focus on what makes them popular with customers.
One of our clients, a tour bus operator known for exceptional customer service, faced a similar crossroads – how to grow without sacrificing the personal touch they were known for. By introducing artificial intelligence to handle routine tasks, the company freed up service agents to take on sales roles, transforming their service center from a cost center to a profit center. Revenue from the service team now exceeds total operating costs.
Widely uncomplicated
“Uncomplicated” is a strong word. For me, this means rejecting complexity. In racing and driving, it often creeps in disguised as preparation—a new tool here, a new idea there—until we realize we’re making things harder on ourselves. I learned this firsthand, both in the boardroom and on the bike.
It’s easy to overstate the complexity of triathlon logistics, especially when a bike is involved. One year, I decided to upgrade to high-tech inner tubes for my tires to increase my speed. But the first time I tested the new tubes during a training ride, one of them exploded, puncturing the tire. It was a humbling reminder that shiny tools don’t guarantee success. In fact, they often slow us down.
I’ve seen the same mistake in investing in AI. Leaders turn to big-name software with bold promises, only to encounter lengthy implementations, steep learning curves, and features that don’t match how teams actually work. Within organizations, software complexity builds up in fragmented systems, siled teams, and low morale due to tools that slow them down rather than help them succeed.
To truly scale with AI, leaders must remove complexity. This means choosing platforms that fit the organization, adopting tools thoughtfully with clear goals, and investing in people as much as technology so teams can use AI with confidence. This approach to uncomplicatedness makes room for clarity, speed, and growth.
Consistency over chaos
While non-complexity is about clarity of design, consistency is about discipline of execution.
When I exercise, there are plenty of mornings when snoozing my alarm sounds more appealing than jumping in the pool or going out for a long walk. But success in endurance sports – and this AI race – comes from showing up every day with relentless effort and focus.
This same mindset is especially important for leaders looking for ROI from their AI investments. At a time when there’s a new AI company on the block almost every day, it’s easy to get distracted. Consistency means staying the course. Once you identify the right platforms and use cases that align with your strategy, stick with them. Set clear goals and integrate AI into your daily workflow. Measure, improve and iterate. It takes time, but results will come.
Over a year ago, our sales team identified prospecting as the biggest bottleneck in their daily workflow. Before AI, nearly three-quarters of the process — from identifying target companies to searching for contacts and writing personalized emails — was manual and time-consuming. The team wanted to spend less time on busy work and more time communicating directly with customers. By introducing automation and fine-tuning over time, the team achieved a 10x ROI in just three months.
It’s easy to confuse motion with momentum. But the companies that actually win the long game will focus on results, unite teams around shared priorities, and remain consistent as everyone strives for the next big thing. Just like in Ironman training, progress comes not from one heroic effort, but from a hundred sustained efforts.
The long game of artificial intelligence
Unlike Iron Man, AI has no finish line. The AI race is long, unpredictable, and constantly changing. There’s really no roadmap – just the discipline that you can play to your strengths, simplify your path, and keep showing up every day.
Leaders who learn to embrace this uncertainty are the ones who make their organizations faster, more innovative, and more resilient. Tomorrow, pick one process, one team, or one customer interaction to avoid AI complexity and start there.
Progress comes from asking the right questions, being present consistently, and having the patience and courage to continue learning as the course develops.
In both racing and business, success comes when you stay your course. Over time, this is how you build stamina and win the long game.
The opinions expressed in Fortune.com reviews are solely those of their authors and do not necessarily reflect the opinions or beliefs luck.
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