I’m a CEO who turned a ‘boring’ air filter business into a $260 million company, and AI will help blue-collar, everyday people just like me

In my teenage years, around the 1990s, I ran a small business creating websites for local companies. Back then, building a website was a laborious process involving slow dial-up internet, manual HTML coding, and frequent layout issues due to minor errors. To earn $2,000 in a summer, I had to dedicate almost all my waking hours, with my income directly tied to my personal output speed.

Around the same period, my grandfather offered me enduring advice: concentrate on developing products or services that people genuinely require. He had a lifetime of experience running a practical business and serving actual customers, and he had little tolerance for fads that didn’t address a clear need.

Years later, as I explored various business concepts, I presented them to him. Some were quite flashy, and one even involved sneakers. He listened attentively. Then, I mentioned my interest in air filters. His demeanor changed; he became more engaged. Air filters made sense. They are a necessity. While not glamorous, they are important. His reaction confirmed I was on the right track.

Today, I lead , a domestic manufacturing company valued at $260 million, which produces and distributes air filters nationwide. Reflecting on my journey, that early experience taught me a crucial lesson that many overlook: individual effort has limited scalability, whereas leverage has compounding effects.

This is why I believe many business leaders are misinterpreting the true economic implications of AI.

Most executive discussions surrounding AI tend to focus on potential risks, regulatory hurdles, or cost-saving measures. While these are valid considerations, they fail to grasp the broader transformation underway. AI’s primary role is not to displace workers or reduce staff numbers, but rather to redefine who has access to leverage.

For the majority of American history, leverage was primarily accessible to those who could afford to hire large teams, secure significant capital, or develop sophisticated software. Everyone else was essentially trading their time for money. This dynamic is now shifting, and the individuals who stand to benefit most will not be programmers.

Consider the typical small service business owner today. A plumber, HVAC technician, or local manufacturer dedicates a substantial amount of time to tasks unrelated to their core expertise. These include scheduling appointments, issuing invoices, following up with clients, and forecasting demand. While these tasks are not inherently difficult, they create operational friction that ultimately limits business growth.

AI does not diminish the need for skilled labor in these businesses; instead, it alleviates the administrative burden associated with it.

A plumber who utilizes AI to manage dispatching, generate estimates, handle customer communications, and conduct follow-ups is no longer constrained by paperwork or missed calls. This allows the business owner to serve more clients with the same team, reduce stress, and operate a more efficient business. The core work remains the same, but the potential for scale increases dramatically.

This is precisely why I believe AI holds greater significance for plumbers than for programmers.

Within the tech industry, AI often enhances existing scalable processes. However, in physical businesses, it fundamentally alters the economic equation. It empowers a single, capable operator to manage a level of complexity that previously required multiple layers of staff or external service providers. Growth is no longer solely dependent on hiring more people as revenue increases; it’s achieved by systematically removing operational bottlenecks.

We have experienced this transformation firsthand at Filterbuy. We did not implement technology to replace our factory floor employees. Instead, we used it to streamline scheduling, improve demand forecasting, minimize errors, and accelerate decision-making processes. The value derived was not solely from automation, but from equipping our team with superior tools and removing obstacles.

This is where I believe many AI discussions falter. They prioritize novelty over practical implementation, focusing on visionary presentations rather than the realities of daily operations. In non-tech sectors, the true opportunity lies not in creating something flashy, but in quietly eliminating the friction that hinders the progress of well-run businesses.

This perspective has significant implications for executive leadership.

The unproductive question is, “How can we use AI to reduce costs?”

A more beneficial question is, “How can we leverage AI to enhance the effectiveness of our workforce?”

If a company has 100 employees, the objective should not be to reduce that number to 80. Instead, the aim should be to enable those 100 individuals to perform at a higher level. This is where sustainable value is generated. Companies that successfully achieve this will not necessarily appear dramatically different externally; they will simply operate with superior efficiency compared to their competitors.

We are entering an era where AI is transitioning from a topic of discussion to a fundamental component of infrastructure. It will not be confined to separate strategic documents; it will be integrated into the very fabric of how work is accomplished. Scheduling will become more precise, decisions will be made more rapidly, and fewer tasks will be overlooked.

I have dedicated my career to focusing on physical goods and what are often termed “boring” businesses, because that is where genuine economic value is created. AI represents the first tool I’ve encountered that can significantly shift leverage towards individuals operating within this domain.

The internet provided us with access to information. AI is now granting us access to operational leverage. For leaders who are willing to apply it to where the actual work takes place, rather than where it appears most impressive, the potential for growth is substantial. The companies that will ultimately succeed will not be the ones making the most noise about AI, but rather those quietly utilizing it to run more effective businesses.