Avy Punwasee is a Partner at Revenue Management Labs. We help companies develop and execute pricing solutions to maximize profits.
It sounds like something out of a Black Mirror episode: a pricing algorithm that knows exactly what you’re willing to pay and adjusts accordingly. Only, it’s not the future. It’s already happening.
Thanks to rapid advances in AI and machine learning, companies are now making pricing decisions that go well beyond cost or competition. These tools can increasingly gauge your perception of value, online behavior and price sensitivity, then tailor prices to you as an individual. It’s dynamic, data-driven and for many businesses, incredibly effective. But for some consumers, it’s a little unsettling.
As discussed in a recent episode of The Pricing Guys podcast, the bigger question isn’t the power of AI and the opportunities it can create. It’s whether it’s making pricing teams smarter or simply more dependent on the technology.
Pricing’s Intelligence Paradox
AI has become a powerful tool in pricing. It can analyze data at scale, identify patterns humans might miss and simulate hundreds of pricing scenarios in seconds. But as more of the work is handed over to AI, there’s a risk that pricing professionals engage less with the fundamentals. Are we using AI to sharpen our thinking, or are we outsourcing it completely?
There’s a fine line between support and overreliance. When the strategy behind pricing decisions is vague, we start to lose clarity—and with it, control.
The Ethics Of Perfect Personalization
AI-driven personalization can push pricing to a new level. It can infer what a customer is willing to pay based on their purchase history, the device they’re using, where they are, and even the time of day. This opens the door to highly individualized, value-based pricing. But where does smart strategy end and unfair treatment begin?
Picture two customers seeing different prices for the same item. One pays more simply because they usually spend more online, or because they’re browsing on a newer iPhone. From the AI’s perspective, it’s a pricing opportunity. From the customer’s point of view, it might feel like discrimination.
The more targeted and opaque pricing becomes, the more it risks eroding trust. Customers don’t want to feel like they’re being profiled. They want to feel understood.
Smarter AI, Smarter Teams
None of this is a case against AI. We’ve seen firsthand how it can transform pricing strategy when it’s used with care. The key is thoughtful implementation.
Here’s what that looks like:
• Treat AI as a co-pilot, not a substitute. Pricing teams need to understand what’s driving the output and be ready to challenge it when necessary.
• Be transparent about how value is determined. Customers are more likely to accept differentiated pricing if they understand why it exists.
• Keep humans in the loop. Ask for feedback to help refine the model and ensure decisions remain aligned with business goals.
• Set ethical boundaries. Just because you can price to the individual doesn’t mean you always should. Make long-term trust a priority over short-term gains.
Final Thought
The ability to pinpoint what someone is willing to pay is a powerful capability. But like any powerful tool, it needs to be used wisely. When applied with care, AI can help us become more strategic, more effective and more responsive. When overused or misunderstood, it can lead to passivity and blind spots.
We’ve got the tools. The real question is whether we’re still sharpening the skills to use them well.
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