Running pre-GPT Srandard Operating Processes in a post-GPT world.

If you listed every business in America in order, 99 out of 100 would be in the ‘small business’ category. Collectively, they employ over 61 million people. Their owners know their industries better than anyone. They run their business with spouses and lifelong friends, serving customers who’ve been with them for decades. And yet, over 60 per cent of these businesses run on tech stacks that have barely changed since the early 2010s, while their founders carry iPhones running GPT models released last Thursday. The future may be in their pockets, but it has yet to reach their operating playbooks.

Over the past year, I’ve sat across from hundreds of founders in boardrooms in Sunnyvale, quiet suburbs of Washington DC, summits in San Francisco, and in the seemingly obligatory casino hotels of Las Vegas, where, for reasons known only to conference organizers, every conference appears to be held.

“Trusted relationships build businesses.”

The other day, I was invited as a guest to a lunch meeting hosted by an association of about 80 business owners who run self-funded, multi-generational family businesses. Every three weeks, all 80 members gather at a private club on Park Avenue for a three-course meal to share their business priorities for the month and the introductions most relevant to their current goals. Not once did AI or technology come up in the conversations.

Instead, there were green pens on the tables embossed with the motto: “Trusted relationships build businesses.” There were stacks of notepads at the center of the dining table for recording “promises” of introductions to come. Now, during lunch, if each of the 80 attendees received just four new introductions, that’s over 300 new connections made collectively in that room before my espresso arrived…

Four hours after lunch, I was downtown at one of the city’s newest restaurants for an entrepreneur happy hour. And it couldn’t be more different. Within earshot, conversations ranged from fintech infrastructure, AI-enabled rollups, a century-old meat factory rolling out a new line of pea-protein sausages and founders turning New York’s vacant warehouses into sushi pop-ups. Almost every conversation was ultimately about one question—how to use technology and AI to solve problems quickly and at scale.

Two worlds in business. One city.

Family-owned businesses have mastered the art of building businesses that last with loyal customers, stable margins and a playbook honed over decades. Technology startups, by contrast, thrive on speed, data and solving complex problems through rapid iteration and scaling globally.

Now, imagine these two worlds meeting at the same table for a proper conversation. Take the foundation of a profitable, decades-old business, its customer relationships, brand equity, and operational know-how, and rebuild the engine with the most advanced technology available today. The question isn’t if it would become more durable, but by how much? What could it grow into with technology-enabled and AI-driven workflows?

There are many ways to capture this opportunity, but one model has been proving it for decades: and that is the search fund model for entrepreneurship. First launched at Stanford in 1984, it was designed to bring new leadership and technology into established family-owned small businesses.

Since then, search funds have created more than $10 billion in value in the U.S. by transforming family-owned small businesses into technology-enabled leaders. Entrepreneurs in this model have turned a paper-based compliance firm for investment advisers into a SaaS platform now used by more than 2,600 firms nationwide. They’ve scaled a New Jersey process-manufacturing software company from a regional player into a 400-person global enterprise, expanding to dozens of countries through cloud migration and product modernization. And one of the earliest search funds took a regional roadside assistance provider with fewer than 50 employees and built it into a global tech-care giant with 23,000 employees, operations in roughly 20 countries, and nearly 300 million customers worldwide.

That kind of leap once required years of capital-intensive investments. Today, the barrier to deploying technology has all but disappeared. If you can imagine an app and draw it on a napkin, it can be built in hours, not months. At a recent hackathon co-hosted by Lovable and Clay, I saw students and early-stage founders building web applications in under an hour for projects that would have taken a full day’s work just two years ago. You can build from scratch using these accelerated processes or integrate AI directly into existing workflows.

For small businesses, there has never been a more opportune moment to modernize operations and build with technology and AI at the core. In just the past two years, models like GPT, Gemini, and Claude have evolved from simple chat interfaces into agentic systems capable of executing multi-step processes with minimal human oversight. And this is only the early innings—by 2030, OpenAI projects AI agents could be tackling problems as complex as drug discovery. The potential productivity gains are equally compelling:

1. 60 percent time savings: Across a wide set of work tasks, generative AI can cut average completion times by more than 60 percent. For technical work, savings can reach 70 percent.

2. Up to 40 percent efficiency gains: Core processes such as supply chain management, document processing and compliance reporting are routinely seeing double-digit improvements when AI-enabled.

For the companies ready to move forward, this is the moment to take decades of know-how and match it with AI that can scale it in months.

The tools are here, the cost has never been lower, and the window is wide open—for now.