Enterprise software companies are shifting strategies as AI technology reshapes traditional pricing models. ServiceNow, SAP, and Workday are taking distinct approaches to managing the impact of AI agents on their platforms. As AI disrupts the long-standing per-seat licensing model, these companies are redefining how they handle customer data access through different methods. The rise of AI agents is posing challenges, urging enterprises to rethink their consumption and billing practices to maintain revenue streams and leverage AI without losing ground.
How are ServiceNow and SAP Approaching AI Agent Access?
ServiceNow and SAP are both taking significant steps to redefine their interactions with AI technologies. ServiceNow recently introduced Action Fabric at its Knowledge 2026 event, creating a metering system for AI agents accessing their platforms. Amit Zavery, Chief Operating Officer at ServiceNow, describes the new system:
“We’ll charge based on how many operations an AI agent completes,”
providing a new revenue stream by applying a per-use fee. In contrast, SAP is restricting AI agent access through updated API policies, prohibiting agents from interacting outside approved architectures.
Are Customers Responding Well to These Changes?
The responses from customers and stakeholders to these changes vary. ServiceNow’s pricing move was characterized as a “tax” by JPMorgan analyst Mark Murphy. On the other hand, SAP’s policy has faced pushback from its user group and partners for potentially restricting integration options. Christian Klein, CEO of SAP, stated,
“Customers will not pay to access their own data,”
signaling their intent to maintain an open architecture. These approaches highlight differing priorities in balancing revenue with user flexibility.
Traditionally, enterprise software operated on a licensing model that aligned directly with the number of users. Each license corresponded with a specific seat or employee. However, the widespread adoption of AI has altered this dynamic. Instead of predictable seat-based billing, AI-driven consumption models emerge, resembling utility bills that fluctuate based on usage. Industry experts have previously noted that AI is steadily transforming enterprise procurement and deployment methods, potentially disrupting established business models.
The current responses reflect rising pressures on companies dealing with AI’s transformative potential. While AWS CEO Matt Garman warns that traditional vendors may lose market share amidst these changes, Workday sees potential for financial growth by recalibrating its agent-level access fees. These strategies underscore a broader industry trend aimed at managing the unpredictability brought by AI’s advanced capabilities and integrating them into existing business frameworks.
Financial teams need innovative tools to manage a budget affected by changes in AI consumption. New governance tools like ServiceNow’s AI Control Tower are anticipated to offer further control over expenses related to AI usage. Large enterprises are already feeling the strain on AI budgets with consumption-based charging models, forcing them to rethink their AI deployment strategies to optimize costs and efficiency effectively.
As the impacts of AI on business operations become more extensive, firms are experimenting to find optimal methods of adjusting to this new technology landscape. Whether by metering or restricting access, these strategies are significant efforts to adapt and grow financially while providing value to customers. It will be crucial for these companies to assess the effectiveness and acceptance of these new pricing models to maintain a balance between innovation and customer satisfaction.
