In my article last week, I shared how AI became the first technology to arrive for everyone at once. There was no generational head start, no insider culture to learn, just everyone starting as beginners together.
This is what makes AI different from past technology waves. Professionals who see AI’s value will lead real change. Recent Thomson Reuters data reveals that organizations with clear AI strategies are twice as likely to see revenue growth from AI adoption. Yet only 22% of organizations have a visible AI strategy.
Think about it: Who is better equipped to use AI than someone who already knows which questions to ask? Who else has the background needed to get great results with AI?
Now, let’s look at some examples relating to fresh produce when experience makes a difference:
- A transportation director with 25 years in produce logistics already knows that strawberries from Watsonville, CA ship differently than those from Plant City, FL. But she can use AI to review years of temperature data, transit times, and arrival conditions to predict quality issues before they happen. Her experience tells her which patterns matter, and AI can process them much faster.
- A quality control manager with decades of experience learning the standards for Walmart, Whole Foods, and Wegmans quickly sees how AI can help operationalize customized specs and analyze service levels for each retailer.
- A Chief Marketing Officer with years of experience reviews SKU rationalization and identifies patterns others might miss. She knows that removing the wrong 12-count pack could hurt sales in Dallas but not affect Portland. She uses AI to analyze sales velocity and to compare promotional lift, seasonal trends, demographic changes, and competition.
Now compare these examples to a recent graduate who might use AI to write emails more quickly. That’s helpful, but limited. An experienced professional uses AI to tackle complex problems they’ve been working on for years.
Why Experience and Confidence with AI Matter
AI doesn’t take away the need for judgment. In fact, it makes good judgment even more important.
This is the opposite of how most new technology gets adopted. With social media, younger employees taught senior staff how to use it. With AI, it’s different. Both groups are learning together, but experience often gives people an edge in getting good results with AI.
Young professionals are comfortable with technology. Experienced professionals are usually better at solving complex business problems. With AI, though, knowing which questions to ask is more important than just knowing how to use the tools.
Here’s an example:
- An operations director with twenty years of experience handling weather events, labor shortages, and transportation problems isn’t worried about being replaced by AI. He’s excited that AI can finally help him test scenarios he could only imagine before.
This confidence helps people adopt AI faster and use it in more advanced ways. While some worry about AI taking jobs, experienced professionals are using it to tackle work they never had time or data for before.
A Technology That Rewards Experience
This isn’t about age. In the era of AI, experience isn’t being replaced—it’s being amplified. For the fresh produce industry, where relationships, quality, and trust matter more than technology, that’s great news.
This time, the revolution isn’t led by digital natives. It’s led by people who know exactly which problems need to be solved.
After three decades helping fresh produce companies adapt to changes from digital marketing to social media, I can say this: AI is different. For once, those of us who remember fax machines aren’t playing catch-up. We’re teaching AI what makes a good strawberry program, what leads to a successful melon deal, and why an August tomato program needs different thinking than a February one.
Our experience isn’t being replaced. It’s being amplified.
AI Learning: An Opportunity for Everyone
While experience makes AI more valuable, every professional in the fresh produce industry, from first-year sales coordinators to veteran executives, can build AI expertise. This chance won’t last forever. Those who start learning AI now will benefit from early adoption, while those who wait may struggle to catch up. The best part is that we’re all still early adopters with equal access to AI learning, no matter how long we’ve been in the industry.
The AI Insider 