In the earlier discussion on Agentic AI for pricing, one of the foundational strategies highlighted was: low price for targeted market entry or to take market share. 

Most distributors don’t deliberately choose where to deploy low pricing—they drift into it. Discounts emerge in response to competitive pressure, not as part of a defined market entry or share plan. Often, sales teams confuse a “job” price with a market price. The outcome is predictable: price goes down, but share doesn’t necessarily follow. Agentic AI can help gain share and stop the race to the bottom. 

Agentic AI reframes this strategy by making low price a deliberate, targeted action rather than a reactive one. This targeted approach gives management a tool to prevent unwanted low prices from seeping into the market. 

The first step is identifying where market entry through pricing is actually viable. This typically includes: 

• Customer segments that are more responsive to price than to relationships  

• Products that are more influenced by “job” pricing, with a clearer understanding of the prevailing market price  

• Product categories where substitution is accepted and differentiation is minimal  

• Demand pockets where pricing can accelerate initial adoption  

These insights don’t come from a single dataset. They emerge from combining multiple data sources—ERP transaction data, customer buying patterns, regional demand shifts, and competitive inputs where available. When connected, these data patterns reveal where lowering price has the highest probability of converting into new business, allowing strategic sales models to be identified. Alternatively, they highlight when a low price is not valid in the market. 

Sales execution then brings discipline to strategy. Opportunity models identify where share can be gained, while response models estimate whether pricing changes will influence buying behavior. The objective is not to reduce price broadly, but to apply it selectively—only where it creates measurable, positive impact. 

This is where Agentic AI extends the model into execution. Pricing agents continuously monitor these signals—tracking demand changes, competitive movement, and sales velocity—and refine recommendations in real time. They operate within management guardrails, ensuring that entry pricing aligns with inventory, the market, and growth priorities. 

What changes with Agentic AI is not the strategy itself—it is the precision and consistency with which it is executed. Low prices become a focused mechanism for entering specific markets and managing the broader market, rather than a reaction to competitive pressure. 

The real question is: where are you lowering price today without a clear path to capturing share? Written by George Connolly, Operating Partner, and Prashant Mishra, Chief AI and Data Officer at AAXIS.