Data and analytics have long been central to B2B pricing. Even with traditional analytical AI continuing to drive value (though it still is yet to be fully adopted), new advances in AI are now poised to reshape how pricing decisions are executed. Pricing is moving from human-led processes supported by analytics to AI-orchestrated systems capable of using analytical insights at greater scale and consistency with human oversight. The value of this shift is not theoretical. While these are still early days, the signs are encouraging. In one recent transformation, for example, a $15 billion B2B distributor built agentic capabilities onto its analytical AI foundations that included a price adviser and discount manager. This program delivered more than 50 basis points of margin improvement on top of the 200 basis points traditional AI already delivered before agentic AI, compressing value realization from years to weeks. That level of promise has fueled enthusiasm for gen AI and agentic AI. Our new survey of more than 400 B2B pricing executives and decision-makers finds 65 to 85 percent of organizations expect to adopt gen AI or agentic AI in pricing over the next one to three years, up from just 10 to 30 percent today. 1 If executed well, this shift could enable smarter, more precise pricing at a scale and speed that would be difficult to achieve with humans alone. Successfully driving this change has the potential to meaningfully affect a business’s profit and loss given the outsize role strong pricing practices already play. On average, a 1 percent price increase translates into an 8.7 percent increase in operating profits, assuming no loss of volume. 2 This AI opportunity—propelled by customers’ own efforts developing AI for their procurement—is creating an important case for change. Despite high aspirations, value from gen AI and agentic AI has been limited in pricing so far. Leaders will need to understand that results do not come from technology alone; results will require redesigned workflows that are optimized for humans and AI, strong data foundations, improved models, continuous investment in AI models, and effective change management. These realities should remain front of mind amid the promise of this next phase of analytical AI. This article examines where pricing organizations stand today, what pricing leaders expect and hope to realize from adopting agentic AI, and the concrete actions required to enable a generational shift for the pricing function. Why pricing is agentic AI’s next frontier Analytical AI has already increased the rigor and precision of pricing, embedding data science into how decisions are informed. Yet execution remains largely human-intensive: Teams still spend significant time assembling inputs, interpreting signals, and translating recommendations into action across complex workflows. 1 Perspectives in this article were informed by the November 2025 McKinsey Agentic AI in Pricing Survey of more than 400 pricing executives and decisions-makers across sectors and regions at companies with annual revenues ranging from less than $500 million to more than $25 billion. 2 Walter Baker, Dieter Kiewell, and Georg Winkler, “ Using big data to make better pricing decisions ,” McKinsey, June 1, 2014. B2B pricing: Navigating the next phase of the AI revolution 2