Turning curiosity into advantage

This is the third and final installment in our series exploring how small businesses and solopreneurs are using AI to rethink hard work, protect momentum, and sustain growth over time. 

In Part 1: Redefining hard work in the AI era, we looked at shifting from hustle to leverage. Part 2: Scaling without burnout, showed how AI helps maintain momentum without adding stress. This final chapter focuses on what keeps that momentum compounding over time: curiosity. 

There’s a common assumption that the small businesses getting the most value from AI are the most technical. The ones building custom stacks, chasing every new tool, or mastering complex workflows. 

The research tells a different story. 

The SMBs seeing real results aren’t trying to “solve AI.” They’re experimenting with it in small, repeatable ways. They test ideas, refine workflows, and learn as they go without waiting to feel ready or perfectly informed. 

In other words, advantage doesn’t come from sophistication. It comes from use. 

One of the clearest signals from the research is this: progress isn’t driven by knowing more about AI. It’s driven by using it more thoughtfully. 

From the Zoom + Upwork study: 

• 59% of small businesses say growth wouldn’t be possible without AI 
• Among solopreneurs, that number rises to 64% 

What’s notable isn’t just the adoption, it’s the relationship. The businesses seeing growth aren’t treating AI as a technical hurdle to overcome. They’re treating it as a working partner they learn alongside. 

That shift from mastery to application changes everything. 

AI adoption is often framed as a one-time decision: early adopter or laggard. In practice, the most effective founders don’t think that way. 

They’re not waiting to feel confident. They’re learning in motion. 

Experimentation becomes an operating mindset, with small prompts, quick trials, and lightweight tests that are easy to repeat or reverse. Each one builds familiarity, judgment, and confidence. 

Over time, the gains of experimentation compound into something beyond technical expertise: into intuition

The research reinforces this. Founders who treat experimentation as ongoing, not something to “graduate from”, develop a clearer sense of when AI helps, where it doesn’t, and how it fits their way of working. 

As one solopreneur put it: 

There’s a paradox at the center of AI adoption. 

Nearly everyone agrees AI is essential. In fact, 98% of respondents say it’s important to their business. And yet, most teams rely on only a handful of tools. 

This isn’t a limitation. It’s an advantage. 

Constraints sharpen judgment. When you work with fewer tools, you’re forced to understand how and when to use them well. You stop chasing novelty and start building instincts. 

Instead of asking, “What else should I try?” the question becomes, “How can this help me think, decide, or move faster right now?” 

That clarity is hard to replicate, and it’s exactly what makes curiosity so powerful. 

Each small experiment builds more than output. It builds confidence, decision speed, and a better sense of what matters and what doesn’t. Over time, that creates an edge that’s difficult to copy, because it’s embedded in how the founder thinks, not which tools they use. 

One founder described how this plays out in practice: 

Another shared how AI has become essential to their development work: 

In both cases, the value isn’t automation alone. It’s shared learning, faster iteration, and better decisions over time. 

Couch + Cork hosts wine tastings over Zoom for clients around the world. Before AI, each event took hours of behind-the-scenes work, transcribing notes and creating custom takeaways for clients. Now that they’re using Zoom AI Companion, summaries and insights help them save 8-12 hours each month on administration tasks.  

For this experiential operation, experimentation didn’t change what made the business special. It preserved it. 

Curiosity doesn’t require a big bet. It works best when it’s fast, reversible, and grounded in real work. Here are five simple ways to test and learn this week: 

1. Marketing 

Use AI to pressure-test your positioning before launch. Share your audience, product details, and draft messaging, then ask: Does this land clearly? What assumptions am I making? What might confuse customers? This allows you to refine early and avoid costly pivots later. 

2. Customer communication 

Feed AI examples of past responses and client profiles to create a small library of replies by inquiry type. You’ll save time on repetitive questions while maintaining consistency and quality. 

3. Proposals 

Use AI to generate first drafts based on past successful proposals, client context, and project requirements. Turn hours of drafting into minutes of editing, without losing your voice. 

4. Decision support 

Before committing to a decision, ask AI to challenge your thinking. Where are the blind spots? What alternatives are you overlooking? It’s advisory-level input without the overhead. 

5. Operations 

Create a lightweight repository of FAQs, workflows, and internal knowledge. Train AI tools on this material so routine tasks start at 80–90% complete, helping your existing team scale output without increasing headcount. 

In this series, we’ve explored how small businesses and solopreneurs are putting AI to work in the real world.  

• Part 1 reframed what hard work means in the AI era 
• Part 2 showed how founders protect momentum without burning out 
• Part 3 revealed how curiosity turns that momentum into a lasting advantage 

The common thread isn’t the technology. It’s the mindset. How you approach work, learning, and experimentation determines whether AI is simply a tool or a true growth partner. 

Read our State of Solopreneurship blog for additional insight into how solo businesses are evolving and how Zoom is supporting the rapidly growing solopreneur economy. For more insights and real-world examples of how small businesses are rethinking work, growth, and momentum in the AI era, explore the full Zoom & Upwork study.