Hertz's new AI-powered vehicle scanners are making headlines—but not for the right reasons. Customers are being charged $440 for one-inch wheel scuffs, with limited recourse and pressure to pay quickly.
This case perfectly illustrates the difference between AI that serves customers versus AI that extracts value from them.
❌ No human oversight when AI flags damage
❌ Customer service barriers (10-day response times, chatbots that don't connect to humans)
❌ Revenue-focused design with "processing fees" for being inspected
❌ Pressure tactics offering discounts for immediate payment
✅ Scan at pickup AND return to protect customers from false claims
✅ Use AI as a first pass with human review for disputed charges
✅ Focus on transparency by making scan results immediately available
✅ Design for customer value by catching safety issues and reducing wait times
✅ Reasonable thresholds for normal wear and tear
AI amplifies your business model—if you're customer-centric, AI can enhance that. If you're focused on extracting maximum revenue, AI will make that more efficient too.
The technology itself isn't the problem. Ultra-precise damage detection could actually benefit customers if implemented thoughtfully. But when you combine superior technology with poor customer service and questionable fee structures, you get exactly the backlash Hertz is facing.
Question for fellow leaders: How do you ensure your AI implementations genuinely serve customers rather than just optimize for short-term metrics?
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