For decades, being an expert was a competitive advantage. You spent years developing knowledge, understanding an industry and accumulating experience that other people didn’t have. Customers paid for access to that expertise because acquiring it themselves was difficult, expensive or time-consuming.

Today, a business owner can ask AI to analyze a market, explain a financial concept or develop a marketing strategy, receiving information that previously might have required a specialist.

Knowing all the answers used to make you the smartest person in the room. Today, it might just make you the most expensive search engine. The uncomfortable question for entrepreneurs who sell expertise is this: If customers can access much of what you know, what exactly are they paying you for?

The value of knowledge is changing

This isn’t simply a prediction about where AI might take us. We’re already seeing how knowledge-based work is changing. Microsoft’s 2025 Work Trend Index found that 81% of leaders expected AI agents to be moderately or extensively integrated into their companies’ AI strategies within 12–18 months. Meanwhile, the World Economic Forum’s Future of Jobs Report 2025 identified analytical thinking as the most important core skill for employers, with creative thinking, resilience and technological literacy also featuring prominently.

These findings point toward an important distinction. Technology is becoming increasingly capable of producing information and completing tasks, but businesses still need people who can evaluate that information, connect it to commercial realities and decide what should happen next.

Consider a consultant who has spent 20 years becoming an expert in a particular industry. That knowledge hasn’t suddenly become worthless, but if much of their value proposition involves explaining information that AI can now provide in seconds, customers may reasonably question what they’re paying for. The premium is shifting from possessing knowledge to applying it.

What 25 years in business taught me about expertise

I founded my international public relations agency, NettResults, in 1999. At the time, one of our advantages was having specialist knowledge of the Middle East technology market. International companies entering the region needed to understand the media landscape, local business practices, cultural differences and how to communicate effectively with unfamiliar audiences. We had that knowledge, along with relationships that took years to develop. Clients couldn’t simply search for much of the information or replicate those relationships overnight.

Today, AI can explain the regional media landscape, identify publications, research competitors and help develop communications strategies in minutes. Information that once took considerable time and experience to assemble is increasingly accessible, but that doesn’t mean our expertise has become less valuable. Knowing which publications cover technology is useful. Knowing which journalist is likely to care about a particular story, how regional sensitivities might affect its reception and whether the story should be pitched at all requires something different. It requires experience, relationships, context and judgment — and those are much harder to automate.

The next advantage is connecting the dots

One limitation of traditional expertise is that we tend to organize it into disciplines. Marketing people understand marketing, financial people understand finance, and technology specialists understand technology. But business problems rarely arrive neatly labeled, and solving them often requires looking beyond the area where the symptoms first appear.

I recently worked with a business owner who believed he needed to hire more people because his company was struggling to keep up with demand. On the surface, it was a staffing problem. But as we examined the business, we discovered that inefficient processes, unclear responsibilities and the owner’s involvement in too many everyday decisions were creating much of the pressure. Hiring more employees might have increased capacity, but it wouldn’t necessarily have solved the underlying problem. The better approach was to examine workflows, clarify accountability and identify where technology could remove unnecessary work before adding more people.

What initially looked like a hiring decision was actually a combination of operational design, leadership and technology. AI can help analyze each of those areas, but the entrepreneur’s opportunity is to connect them, recognize which information matters and make decisions that account for the whole business. The business owner who understands enough about technology, psychology, finance, operations and customer behavior to connect those disciplines may create more value than someone who knows everything about just one of them.

That doesn’t mean specialists are becoming unnecessary. Deep expertise remains essential, particularly when decisions carry significant financial, legal or operational consequences. But expertise without the ability to apply it in context becomes easier to commoditize.

Conduct an expertise value audit

If your business sells knowledge, advice or specialist services, I recommend examining how your value proposition is changing. This doesn’t require an expensive consultant or a six-month strategic review. Start by asking four questions about what your customers actually buy from you and where you create value that they cannot easily reproduce themselves.

1. What do customers currently pay us to know? Identify the specialist knowledge, information and capabilities that underpin your products or services.

2. What could AI now provide them directly? Be realistic about which parts of your offering are becoming easier, faster or cheaper for customers to access independently.

3. Where does our judgment create value? Look for the decisions, relationships, interpretation and experience that produce better outcomes than information alone.

4. How should we reposition what we sell? Consider whether you should be charging for access to knowledge, time spent delivering it or the commercial outcomes your expertise helps customers achieve.

This exercise isn’t about abandoning your expertise. It’s about making sure you’re not building tomorrow’s business around yesterday’s competitive advantage.

Stop selling answers. Start selling outcomes.

For entrepreneurs, the opportunity isn’t to compete with AI on how much information we can produce. That’s a competition we’re unlikely to win. Instead, we need to become better at asking the right questions, connecting information across disciplines and making decisions that create measurable value for customers.

AI can increasingly tell people what is possible. Experienced entrepreneurs and professionals help determine what is sensible, commercially viable and worth doing. The future doesn’t belong to people who simply know the most. It belongs to those who know what matters, what to do about it and are prepared to take responsibility for the result.

For decades, being an expert was a competitive advantage. You spent years developing knowledge, understanding an industry and accumulating experience that other people didn’t have. Customers paid for access to that expertise because acquiring it themselves was difficult, expensive or time-consuming.

Today, a business owner can ask AI to analyze a market, explain a financial concept or develop a marketing strategy, receiving information that previously might have required a specialist.

Knowing all the answers used to make you the smartest person in the room. Today, it might just make you the most expensive search engine. The uncomfortable question for entrepreneurs who sell expertise is this: If customers can access much of what you know, what exactly are they paying you for?