I’ve spent two decades competing in Ironman Triathlons, grueling, single-day events that total over 140 miles. I’ve spent even longer leading high-growth companies, from Google and Dropbox to Freshworks.

You could say that I’ve been operating with a need for speed my entire adult life. And if there’s one thing these experiences have taught me, it’s that most companies are pacing the AI race all wrong.

Recent data from Bain & Company shows that 95% of U.S. companies are using generative AI in some form, yet only 5% of firms see meaningful value from their AI investments.

I believe this is happening because, like rookie triathletes, many business leaders treat AI like a sprint – chasing speed, hype, and short-term wins, while expecting long-term, sustainable results. In both racing and business, success hinges on pacing yourself, building stamina, and staying focused on the long game.

The Ironman playbook for AI

Over my 18 Ironmans, I’ve learned that the real key isn’t strength or speed – it’s structure. Whether training for race day or leading a company through AI transformation, you need a set of principles to keep you grounded and disciplined through uncertain (and sometimes fatiguing) times. The three I stand by are:

1. Play to your strengths

2. Uncomplicate to scale

3. Consistency over chaos

As a CEO, these principles have guided me in building, scaling, and leading through one of the most disruptive shifts the SaaS industry has seen in decades.

Play to your strengths

In my first few Ironman races, I tried to keep up with the veterans in the swim. Big mistake. I burned too much too soon and paid for it the rest of the way. Eventually, I learned that performance – in racing or business – isn’t about matching someone else’s speed. It’s about knowing your strengths, then pacing with purpose and trusting your own race plan.

The same lesson applies in setting an AI strategy. Every company wants to mimic the playbooks of the Googles or OpenAIs of the world. But not every company should — and that’s not a bad thing. As much as I admire my former colleagues at Google, we’re not trying to emulate them. Our race is different. Our landscape, resources, and goals aren’t 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 their business’s strengths, such as improving customer experiences, streamlining operations, and driving efficiency, without losing focus on what makes them beloved by customers.

One of our customers, a tour bus operator known for exceptional customer service, faced a similar crossroads – how to grow without sacrificing the personal touch that they were known for. By introducing AI to handle routine tasks, the company freed up service agents to take on sales roles, shifting their service center from a cost center into a profit center. Revenue from the service team now exceeds its total running costs.

Uncomplicate to scale

“Uncomplicate” is a powerful word. For me, it means rejecting complexity. In racing and leadership, it often sneaks in disguised as preparation — a new tool here, a new idea there — until we realize we’re making things much harder for ourselves. I’ve learned that firsthand, both in the boardroom and on the bike.

It’s easy to overcomplicate triathlon logistics, especially when it comes to the bike. One year, I decided to upgrade to higher-tech inner tubes for my tires to increase my speed. But the first time I tested the new tubes during a training ride, one blew out, resulting in a flat tire. It was a humbling reminder that the shiniest tools don’t guarantee success. In fact, they often slow us down.

I’ve seen the same mistake in AI investment. Leaders go for the big-name software with bold promises, only to face long implementations, steep learning curves, and features that don’t match how teams actually work. Inside organizations, that software complexity compounds into fragmented systems, siloed teams, and deflated morale from tools that slow them down instead of helping 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 confidently. This approach to uncomplication makes space for clarity, speed, and growth.

Consistency over chaos

While uncomplicating is about clarity of design, consistency is about discipline of execution.

When I’m training, there are plenty of mornings when snoozing my alarm sounds much more appealing than jumping in the pool or getting out for a long run. But success in endurance sports – and this AI race – comes from showing up every day with relentless effort and focus.

That same mindset is especially important for leaders seeking ROI from their AI investments. In a time where 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, commit to them. Set clear goals and integrate AI into daily workflows. Measure, refine, and repeat. It takes time, but the results will come.

Over a year ago, our sales team identified prospecting as the biggest bottleneck in its daily workflows. Before AI, nearly three-quarters of the process – from identifying target companies to researching contacts and writing personalized emails – was manual and time-consuming. The team wanted to spend less time on busywork and more time connecting directly with customers. By introducing automation and fine tuning over time, the team achieved 10x ROI in just three months.

It’s easy to confuse motion for momentum. But the companies that actually win the long game will focus on outcomes, align teams around shared priorities, and hold steady when everyone else chases the next big thing. Just like in Ironman training, progress doesn’t come from one heroic effort, but from a hundred consistent ones.

The long game of AI

Unlike an Ironman, AI doesn’t have a finish line. The AI race is long, unpredictable, and constantly changing. There really isn’t a roadmap – only the discipline to play to your strengths, uncomplicate your path, and keep showing up every day.

The leaders who learn to embrace this uncertainty will be the ones who make their organizations faster, more innovative, and more resilient. Tomorrow, pick one process, one team, or one customer interaction to uncomplicate with AI and start there.

Progress comes from asking the right questions, showing up consistently, and having the patience and courage to keep learning as the course evolves.

In both racing and business, success comes when you stay your own course. Over time, this is how you build endurance and win the long game.