Analyst(s): Keith Kirkpatrick
Publication Date: November 20, 2025
Salesforce, ServiceNow, Microsoft, SAP, Zendesk, Adobe, Oracle, and other major SaaS vendors have incorporated AI functionality into their respective platforms. Just as the way they have implemented generative AI and agentic AI varies, so does the way they charge for these advanced technologies. The successful monetization of AI remains a delicate balancing act between flexibility, feature sets, and costs, all of which continue to evolve.
Key Points:
Major SaaS vendors are taking different approaches to pricing generative and agentic AI services, but some common approaches have emerged:
- Included as part of the core offering, with enhancements available at an additional cost
- Available as a seat-based license, on a per-user, per-month pricing schedule
- Provided on a consumption-based basis, where pricing is directly tied to usage
- Priced on successful outcomes or resolution, with a flat fee per resolution
Overview:
Enterprise software pricing has long been a complex balancing act between vendors’ need to recover costs and drive profits and customers’ desire to extract maximum value and ROI from their investments. This complexity has intensified with the rapid rise of generative AI and agentic AI capabilities, which are increasingly viewed as core drivers of productivity, efficiency, and competitive differentiation. As organizations experiment with ways to integrate AI into both human-assisted and autonomous workflows, SaaS vendors are under pressure to create pricing models that reflect rapidly evolving use cases, shifting consumption patterns, and diverse customer expectations.
Recent research from Futurum underscores the central role of AI in software purchasing decisions. In its 1H 2025 Enterprise Software & Digital Workflows Decision Maker Survey, 40.6% of respondents cited “Generative AI Capabilities” as a top decision criterion, followed closely by “Breadth and Depth of Features/Functionality” at 39.6%. Notably, 37.8% also highlighted agentic AI—despite its early-stage adoption—demonstrating that buyers are actively prioritizing AI-driven functionality in future evaluations.
To meet these expectations, vendors have adopted four primary AI pricing strategies, often blending them to match customer needs. The first approach—seat-license add-ons—applies a predictable per-user, per-month fee. Vendors such as Salesforce and Microsoft commonly use this model to price human-assistive capabilities such as Copilot or Agentforce. While effective for tools tied to an individual user, seat-based pricing becomes less suitable as organizations deploy autonomous agents not linked to human identities.
The second model—consumption- or credit-based pricing—aligns costs directly with usage. This approach supports a wide range of AI scenarios, from sporadic inferencing to fully automated workflows. Salesforce’s Flex Credits, Microsoft’s Copilot Credits, and Adobe’s generative credit system enable vendors to manage compute usage while giving customers the flexibility to pay only for what they consume. HubSpot also employs a credit-based model for advanced AI features, allowing customers to mix and match AI capabilities within a single credit pool.
Outcome-based pricing represents a third strategy, tying cost to measurable business results such as successful resolutions. Zendesk and Intercom have embraced this approach for their AI agents, charging per automated resolution. Salesforce has also signaled interest in exploring outcome-based options in response to customer demand. While attractive to buyers seeking clear value alignment, outcome-based models add complexity around defining success criteria and handling interdependent tasks.
The fourth approach embeds AI directly into the core product at no additional cost, a strategy favored by vendors such as Oracle, Zoho, SAP, and Microsoft (for certain Copilot scenarios). While appealing to customers, embedded AI requires vendors to carefully monitor resource consumption to avoid unplanned compute costs, often using guardrails such as credit caps or rate cards.
Across all models, the market remains fluid, and vendor strategies are evolving quickly. As AI adoption accelerates and workloads shift from human-assistive to autonomous, pricing will continue to mature. Vendors must remain flexible, monitor customer value perceptions, and adapt pricing structures to avoid competitive disadvantage. Ultimately, scalable and sustainable AI pricing will be a critical lever for driving adoption, protecting margins, and sustaining long-term innovation in the enterprise SaaS market.
The full report is available via subscription to Futurum Intelligence’s Enterprise Software & Digital Workflows IQ service—click here for inquiry and access.
For more insights on pricing, please see the related State of the Market Report (subscription required).
About the Futurum Enterprise Software & Digital Workflows Practice
The Futurum Enterprise Software & Digital Workflows Practice provides actionable, objective insights for market leaders and their teams so they can respond to emerging opportunities and innovate. Public access to our coverage can be seen here. Follow news and updates from the Futurum Practice on LinkedIn and X. Visit the Futurum Newsroom for more information and insights.
Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
