Enterprise Software Buyers Prefer Consumption and Outcome-Based Pricing

Austin, Texas, USA, October 17, 2025

With No Single Pricing Approach Dominating Buyers’ Preferences, Vendors Should Consider Offering Multiple Pathways for Consuming Generative AI Products and Tools

Building on a trend surfaced in the inaugural Futurum 2H 2024 Enterprise Software Decision Maker Survey conducted last year, enterprise buyers and decision makers continue to prefer generative AI functionality priced on a consumption basis over outcome-based approaches, per user, per month models, or simply embedded as part of the core license.

Futurum’s 1H 2025 Enterprise Software & Digital Workflows Decision Maker Survey reveals 38% of respondents preferred generative AI functionality to be offered as an additional feature or function priced on a consumption basis, compared with outcome-based pricing (31%), per-user, per-month (20%), or included within the core offering (11%).

Figure 1: AI Software/Tools Market (2023–2029; in USD Million)

Keith Kirkpatrick, Research Director, Enterprise Software & Digital Workflows at Futurum, said, “As generative AI functionality increasingly becomes a must-have component of enterprise software, there is a growing preference for linking the cost of the technology to value delivered. Consumption-based pricing, where customers pay for the amount of compute resource consumed, instead of a flat license fee, is often preferred by customers and vendors due to this alignment of objectives, though outcome-based approaches are garnering steam.”

The research reveals several key developments shaping the AI pricing landscape:

• Consumption pricing was preferred by more than half of respondents during the 2024 survey, likely due to an increase in preference for outcome-based pricing approaches.
• License-inclusive pricing of generative AI is more difficult for organizations that do not own compute resources and cannot control or absorb those costs.
• There is a lack of consensus on the “best” pricing approach for generative AI.
• This lack of consensus is likely due to the wide variety of use cases for generative AI, differing priorities among customers, and varying metrics for gauging the success of generative AI deployments.

“While the findings indicated a preference for linking generative AI costs to value delivered, there is no single industry-wide approach that is likely to be adopted in the near term,” noted Kirkpatrick. “That’s why it will be incumbent upon vendors to consider offering myriad pricing options and approaches to meet the diverse needs of customers, taking into consideration ROI metrics, payback periods, risk tolerance, and contract length.”

Read more in the 1H 2025 Enterprise Software & Digital Workflows Decision Maker Survey Report on the Futurum Intelligence Platform.

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