As part of my 90-day AI challenge, I’ve been diving into how AI is shaping industries—not just by making things faster and more efficient, but by fundamentally changing who holds power, who makes decisions, and how industries evolve.

This week, I read AI in Industry: Real-World Applications and Case Studies (you can check it out here). It provides a solid breakdown of how AI is already being used in industries like healthcare, finance, agriculture, retail, and energy to boost efficiency, improve accuracy, and reduce costs.

That’s all true, and it’s great. But there’s more to AI than just optimizing things. The real question is: What happens when AI doesn’t just improve systems, but disrupts them completely?

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AI in Healthcare: Why Can’t Patients Have These Tools?

The article highlights AI’s role in improving medical diagnostics:

“AI-based scoliosis detection achieved up to 93.6% accuracy, reducing diagnostic time.”

Great, right? It’s a huge leap forward in healthcare. But here’s the thing: We assume AI should help doctors get better at what they already do—but why can’t patients have access to the same diagnostic tools?

Why should the tools that improve doctors’ efficiency stay locked away in hospitals? Sure, we want doctors to be the experts, but at some point, we need to question the outdated belief that patients need to be passive recipients of care.

Patients are already using smartwatches to track heart health, and AI-driven apps are helping people monitor symptoms. The real disruption is when patients don’t just go to the doctor to get diagnosed—they use AI to analyze their own health data and make decisions themselves.

The article highlights how AI helps doctors make better decisions, but it misses the bigger point: What happens when patients take control?

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AI in Finance: Can Fraud Really Be Stopped, or Are We Just Raising the Stakes?

In finance, the article discusses AI’s ability to detect fraud more effectively:

“Several financial institutions that integrated AI-based real-time fraud detection observed a reduction in fraudulent transactions of up to 40%.”

That’s impressive. But here’s the catch—criminals are using AI too.

Banks are using AI to detect fraud by spotting unusual patterns in transactions. But fraudsters can do the same thing. If AI is helping to catch fraud, then criminals are going to train their own AI to bypass those fraud detection systems.

In fact, we’re already seeing deepfake scams and AI-generated synthetic identities making it harder to tell the difference between legitimate transactions and fraud. If fraud detection systems get better, it’s only a matter of time before AI fraudsters learn to evade detection altogether.

The article presents AI as making financial systems safer—but what happens when AI just raises the stakes for both sides? Is AI really making things safer, or are we just entering a new kind of arms race?

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AI in Agriculture: Are We Optimizing the Right Things?

The article also talks about how AI is increasing crop yields:

“AI models increased crop yields by up to 20% through better predictive analytics.”

More food, fewer wasted resources—sounds great, right? But should we be maximizing yield at the cost of everything else?

Industrial agriculture has been pushing for higher yield for years, and AI is making that even more efficient. But in the process, we’re seeing the devastating effects of monoculture farming—soil depletion, loss of biodiversity, and environmental collapse.

What if we didn’t just optimize for crop yield but started using AI to create resilient, sustainable farming practices? Instead of optimizing industrial farms, why not use AI to help small-scale, sustainable farmers—who focus on biodiversity and soil health—to produce better, longer-lasting food systems?

The article focuses on maximizing food production, but it doesn’t ask: What if AI could change the way we farm completely?

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The Bigger Question: AI Isn’t Just About Efficiency

The original article does a great job explaining how AI makes industries more efficient. And, yes, efficiency is important. But the next big step isn’t just about making things faster or more accurate—it’s about how AI changes the balance of power.

• AI is not just making doctors better at diagnosing—it’s about shifting who controls health information.
• AI is not just preventing fraud—it’s escalating a battle between fraud detection and fraud creation.
• AI is not just increasing food production—it’s deciding what kind of agriculture we prioritize.

The real question is: How are we using AI to challenge the systems we’ve built? Efficiency is one thing, but AI’s power lies in the disruption it causes to the status quo.

And that’s what we need to be talking about.