Joanna Wells explores the hidden risks behind AI pricing. Businesses may be underestimating how quickly automation can accelerate margin leakage. It can also worsen pricing inconsistency and weak governance.
This episode examines how years of discounts, overrides, rebates, and pricing workarounds create hidden margin leakage. These issues quietly build dysfunction inside pricing systems. The episode also explores why AI may amplify these problems instead of fixing them.
TIME-STAMPED NOTES:
[00:00] Introduction: Why AI Pricing Could Become a Major Margin Leakage Risk
[01:40] Why AI Cannot Fix Broken Pricing Foundations and Margin Leakage
[02:56] The Industrial Business Case Study and Hidden Margin Leakage
[05:27] How AI Automates Pricing Dysfunction and Margin Leakage at Scale
[07:30] Why AI Pricing, Governance, and Margin Leakage Are Connected
[09:44] Conclusion: The False Confidence AI Creates Around Margins
Why AI Pricing Could Become a Major Margin Leakage Risk
[00:00] This week, I was reading a BCG article. It was about AI pricing and why AI pricing is not always plug-and-play. Honestly, it made me think, and I began to see clearly one of the biggest commercial risks businesses are blindly about to walk into.
[00:20] Right now, a lot of businesses are looking at AI pricing and thinking, “Yes, finally, this will fix all our pricing pains and headaches, like margin pressure, discount leakage, inconsistent pricing across channels, customers and products, pricing complexity in our systems, and all that commercial mess and millions of customer records sitting in our pricing system or our ERP.”
[00:48] But honestly, I think many businesses are about to discover the exact opposite. Because if a business really has all these margin leakage issues and pressures, weak governance, and poor pricing logic, then AI may not actually reduce margin erosion. It is probably going to accelerate it, and I do not think enough leadership teams fully understand that risk yet.
[01:16] Hello, and welcome to the Pricing College podcast. I’m Joanna Wells, Founder and Director of Taylor Wells Advisory, and we help businesses improve margin through better pricing strategy by fixing how pricing actually works commercially and operationally inside the business. This episode is part of our Pricing Transformation Series.
Why AI Cannot Fix Broken Pricing Foundations and Margin Leakage
[01:40] The real problem here is that a lot of businesses are hoping AI helps them avoid doing the hard pricing yards, when actually a pricing transformation takes a lot of hard work and effort. It is not easy to simplify legacy pricing structures or redesign broken processes. Things have to make sense, and you have got to confront years of unmanaged pricing behaviour honestly and bravely.
[02:10] Most pricing problems do not suddenly appear overnight. They build up very slowly over years through things like customer exceptions, tactical discounts, overrides, rebates, legacy systems, the compromises people make when they are doing deals, and the workarounds that are layered on top of other workarounds.
[02:34] Eventually, businesses do reach a point where nobody fully trusts the pricing structure anymore, and nobody really wants to redesign it either when things are such a mess. So now the hope becomes, “Well, maybe AI can somehow fix it for us.” But honestly, that is not how this works.
The Industrial Business Case Study and Hidden Margin Leakage
[02:56] I think it would be good to give you a case example here. We worked with a large industrial business, and the leadership team genuinely believed that they had disciplined pricing and a pricing structure that was sophisticated enough to move directly into an AI pricing integration.
[03:19] Now, on the surface, it did look mature. There were matrices and approval workflows, pricing policies, and years of pricing history inside that system. So the executives there were thinking, “Well, basically, we can do this. We just need AI and automation now to really streamline our pricing.”
[03:40] However, once we analysed realised pricing behaviour properly, the reality underneath was completely different. We uncovered things like overlapping pricing structures. There were deep-cooked customer arrangements, tactical rebates that no one fully tracked, overrides outside approved workflows, and a significant amount of hidden margin leakage buried underneath approved pricing.
[04:09] Honestly, nobody could fully explain why certain customers were on certain pricing, or how some net prices were actually being calculated, or how much margin erosion was quietly accumulating over time at a transactional level.
[04:26] The executives of this business were thinking, and quite rightly, that they had a fairly sophisticated pricing capability because, in many respects, it was sophisticated. They believed, however, that it was only being held back by the antiquated ERP that was holding it all together.
[04:46] However, what they did not see was that each and every day it was their teams, and their teams’ experience managing the fallout of the system, that were manually holding it all together.
[05:00] They knew where pricing logic no longer made sense, which customers had been over-discounted for years, where the system needed special handling, and how to work around pricing structures that no longer reflected commercial reality.
How AI Automates Pricing Dysfunction and Margin Leakage at Scale
[05:27] It was the team, the people in that business, that had become the governance system, not the ERP or the pricing system. Honestly, this is exactly where AI pricing becomes dangerous. Because once AI starts automating pricing decisions at scale, it also starts automating the inconsistencies, the overrides, the gaps, the weaknesses, the leakage, and the dysfunction already sitting underneath the business.
[05:52] This is why it is so important to understand that humans can work around broken pricing systems informally, and they are very good at doing that.
[06:04] I think the biggest mistake businesses are making right now is assuming that AI pricing is going to replace commercial thinking. It does not. AI scales whatever logic already exists, and that includes the dysfunction.
[06:21] I strongly believe AI is increasing the need for good teams, commercial thinking, and problem-solving. This is more important now than ever before. Once AI starts making pricing recommendations at scale, commercial risks become much bigger. Weak governance, poor segmentation, inconsistent value logic, and unmanaged discounting become far more damaging commercially.
[06:47] I think businesses are massively underestimating how much margin leakage and pricing inconsistency has already become embedded into normal commercial behaviour because AI has already automated it.
[07:02] Think of AI pricing as being a bit like putting a Formula 1 engine into a car with damaged steering. Sure, the car becomes faster, but the steering is unstable, the brakes are unreliable, and the dashboard cannot tell you that your car is low on fuel.
[07:21] So the problem is not speed anymore. The problem becomes how quickly the business loses control of its number one profit driver.
Why AI Pricing, Governance, and Margin Leakage Are Connected
[07:30] AI pricing is not a technology project. Integrating AI into the business is not an IT integration project. It is a commercial capability project. It is a pricing maturity project. It is a governance project. It is transformation.
[07:51] Because businesses often lack trusted value-based pricing frameworks. Many also lack strong segmentation and clear pricing accountability. Some businesses do not even have clear value logic. In those situations, AI simply automates leakage, overrides, workarounds, and inconsistencies.
[08:10] This is why you cannot automate pricing governance that does not exist. I think businesses are still underestimating how serious this could become commercially. Because once pricing becomes difficult to explain, inconsistent, complex, and disconnected from value, trust starts eroding very quickly.
[08:34] Once customers stop trusting pricing, or your sales team stops believing in or trusting your pricing, margin erosion usually is not far behind. AI can amplify that much faster than businesses realise.
[08:51] I think executive teams are asking the wrong question. They are thinking and asking, “How quickly can we implement AI pricing?” But the better question is, “What pricing leakage and dysfunction are we about to automate at scale?” Because those are two very different conversations.
[09:13] In my professional opinion, I do not think the future belongs to businesses with the fastest pricing engine, the most automation, or the most aggressive optimisation. I think the future belongs to businesses willing to simplify pricing and redesign pricing around real commercial value. Because ultimately, the future of pricing is not just intelligent pricing. It is explainable pricing. It is transparent pricing.
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Conclusion: The False Confidence AI Creates Around Margins
[09:44] I think one of the biggest risks emerging in pricing today is not AI itself. It is the false confidence AI is creating inside businesses.
[09:55] I’m Joanna Wells, Founder and Director of Taylor Wells Advisory. If your business is currently exploring AI pricing, this is probably the moment to stop asking, “How quickly can we automate pricing?”. And start asking, “Are we about to scale pricing problems we never properly fixed in the first place?”
[10:16] Thank you for listening. I’ll see you next week. Goodbye.
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