I’m going to start with the AI story that I think is bigger than the one getting the attention. Don’t worry, I’ll cover both.
Delta Air Lines is set to implement artificial intelligence in determining the maximum price customers are willing to pay for flights, aiming for AI to influence 20 percent of its ticket prices by the end of 2025. This approach follows a successful limited test and reflects a significant shift from static pricing, with Delta’s president, Glen Hauenstein, emphasizing the need for careful control of this new pricing strategy. Currently, Delta uses AI to influence three percent of its ticket prices, with plans to expand this significantly. The technology, provided by travel firm Fetcherr, acts as a “super analyst,” analyzing customer behavior and market conditions in real time. Privacy advocates have raised concerns over this personalized pricing strategy, with critics suggesting it may feel invasive as it attempts to gauge customers’ willingness to pay.
Why do we care?
Dynamic pricing isn’t new (think Uber surge pricing or Amazon’s price adjustments), but this isn’t about adjusting to supply and demand anymore. This is AI attempting to predict the psychological breaking point of each customer and tailor pricing in real time.
For businesses serving end customers, it raises critical questions:
- What’s the customer perception risk? While businesses may see higher margins, customers may feel manipulated or penalized for loyalty (why was my ticket $50 higher than the person next to me?). That’s a trust erosion problem that MSPs will also face if AI-enabled pricing tools trickle down to SMB platforms.
- Data ethics and privacy are about to become operational concerns. The AI requires massive customer behavioral data ingestion to work. IT service firms will need to guide clients through the regulatory and reputational minefield of “personalized pricing.”
This is a test case for a broader business trend where AI won’t just automate tasks—it will directly set revenue models.
Regulators will be watching industries experimenting with AI-driven pricing. Dynamic models that probe individual willingness to pay could trigger antitrust investigations or consumer protection action. MSPs advising clients on AI adoption need to bake in compliance and oversight considerations from day one.
For IT service providers, it’s a glimpse of the future demand for AI strategy consulting. SMBs will start asking: “Can we do this?” The right answer isn’t a knee-jerk “yes.” Instead, providers must help clients weigh the business upside against customer trust and compliance risks. From an IT services angle, MSPs should avoid overhyping these tools to clients. Without robust data pipelines, most SMBs will never achieve Delta-level predictive pricing—and trying to may damage their customer relationships.
This also highlights a new strategic differentiation opportunity: helping businesses use AI responsibly, not just profitably. Those MSPs and vCIOs who can advise on ethical AI use, transparency, and customer communication will have a competitive edge as these tools proliferate. Delta may grab headlines, but the bigger story is how AI shifts the very definition of value in pricing—and whether businesses can keep their customers’ trust while exploiting it.