HubSpot shifts AI agents to outcome-based pricing, charging only for completed results

Look what the Easter Bunny brought Hubspot customers - a shift to outcome-based pricing for Customer and Prospect Agents

HubSpot has announced that it is switching two of its Breeze AI agents: Customer Agent and Prospect Agent to an outcome-based pricing model. Why these AI agents and why the change? With outcome-based pricing, the customer only pays when the agent achieves a defined outcome, such as resolving a support issue, qualifying a lead or booking a meeting, or completing a defined job start-to-finish. Today, HubSpot announces that its Breeze Customer Agent and Breeze Prospect Agent will now be charged using an outcome-based pricing model starting April 14. According to HubSpot, companies are facing increasing pressure to justify agentic AI spend and prove ROI, and one of the best ways to help them is to charge based on outcomes. The company believes that AI should be measured in outcomes not output, but most agents aren't priced this way because they can't promise consistent results. In HubSpot's case: One of the primary reasons HubSpot is able to shift these two agents to a pricing model based on task completion is because the agents are built into the HubSpot platform where they have access to the customer and business context needed to deliver reliable performance. For example, these agents can access contact data, relationship history, and other business information. The Customer Agent delivers a 65% conversion rate and 39% faster resolution times across 8,000 plus HubSpot customers. This pricing change means customers shift from paying $1 per conversation to $0.50 per resolved conversation. With the Breeze Prospecting Agent, HubSpot says that customer activations are up 57% quarter over quarter. It moves from a monthly recurring charge for every contact enrolled to $1 per lead recommended for outreach (so you only pay when a prospect is qualified and handed over to the sales team). HubSpot says this pricing change allows customers to move faster, experiment more, and trust that spend is tied to real results. As AI agents continue to grow in use among organizations of all sizes, pricing has become an interesting conversation because no one has figured out how to do it consistently. Research from paid.ai found that 75% of vendors adding AI agents have no systematic approach to pricing them. A few approaches include: The research notes that outcome-based pricing yields the highest margins with low churn, while usage-based pricing is the most vulnerable to commoditization. Although HubSpot is one of the first software vendors to shift at least one of its agents to an outcome-based pricing model, it isn't the only one. Intercom's Fin AI agent uses outcome-based pricing, charging $0.99 per outcome. It defines two types: Zendesk is another company that moved to outcome-based pricing to align its costs with value for the customer. According to the paid.ai research, most customer support agents are moving to outcome-based, while only 20% of RevTech (AI SDRs and AI AEs and Marketing Agents) are following this pricing model. The research notes that one AI SDR company charges $200 per attended meeting and sees 94% gross margins. Then there are vendors who charge using a hybrid model. For example, Intercom includes Fin AI Agent with its helpdesk, which it charges per seat. So, you have that combination of outcome-based when Fin is engaging with customers, and the per seat cost for help desk agents. Of course, HubSpot is similar in that you still pay for the HubSpot platform, then pay for the use of the AI agents within the platform. Other agents in the HubSpot ecosystem still work on a credit model where you buy credits to consume agents and other AI features. Outcome-based pricing for AI Agents is an emerging model that makes sense in some situations. If the vendor and customer can work together and clearly define what "success" looks like, then outcomes can work. It's also essential that the vendor providing the agent can directly influence the results from the agent. If they have no control or influence, then the vendor can't be sure if the agent is providing the results needed. Businesses that use AI agents with outcome-based pricing need to ensure they know how success is measured and that the agent is auditable to prove the outcomes were truly achieved. And while outcome-based pricing makes sense for agents like the Customer Agent and Prospect Agent, someone on the customer side needs to be responsible for monitoring the results to ensure the billing is accurate, which can possibly lead to more effort than when working with a different pricing model. HubSpot is definitely taking the right approach to pricing these two agents going forward. It will be much easier for customers to prove the ROI of using these agents. Proving the ROI of other agents is trickier because there is no way to define clear outcomes (the outcomes vary based on what the agent does). However, you can see how it may become challenging for both HubSpot and customers to track each agent they use, how they are paying for it, and how they define and track outcomes.

HubSpot flips AI pricing on its head with outcome-based Breeze agents - SiliconANGLE

HubSpot flips AI pricing on its head with outcome-based Breeze agents Inbound marketing and customer relationship management platform HubSpot Inc. today announced it's changing how customers pay for artificial intelligence with the introduction of an outcome-based pricing model for two of its core AI tools that ties cost directly to results rather than usage. The company is shifting its Breeze Customer Agent and Breeze Prospecting Agent to the new pricing structure from April 14, marking a shift away from traditional per-seat or per-interaction fees that dominate much of the AI market today. With the updated model, customers only pay when the agents successfully complete assigned tasks. HubSpot first introduced its Breeze in September 2024, pitching the offering as an embedded AI layer across its customer platform. Breeze offers a chat-based copilot, automated AI agents and a customer intelligence system that helps marketing, sales and service teams work more efficiently using their own data. The service allows users to generate content, automate workflows, engage leads and handle customer support through specialized agents. With the changes, pricing for the Customer Agent will drop from $1 per conversation to 50 cents per resolved conversation. According to HubSpot, the tool resolves about 65% of customer interactions and reduces resolution time by 39%, suggesting a growing level of reliability that supports the move to performance-based billing. The Prospecting Agent is also receiving a price overhaul, moving from a recurring monthly charge based on enrolled contacts to $1 per qualified lead recommended for outreach. HubSpot argues that outcome-based pricing has been difficult for most AI vendors to offer because many systems lack the consistency required to guarantee results. The company is differentiating its approach by embedding its agents within its Smart CRM platform and providing them with access to customer data, relationship history and business-specific context. The integration allows its AI to deliver more predictable outcomes compared to generic models that operate without insight into a company's internal data. "Businesses are being asked to make big bets on AI right now. Too often, that means paying for potential rather than performance," said Jon Dick, chief customer officer at HubSpot. "Outcome-based pricing removes that risk. You pay when it works, full stop. Customers can move faster, experiment more and trust that their spend is tied to real results."