Expert warns AI agents could pressure the enterprise software “human user” model at Salesforce and ServiceNow

Salesforce and ServiceNow, two of the most prominent enterprise software providers, face a growing question about the durability of a lucrative business model as artificial intelligence shifts how work gets done inside companies. In a new commentary reported by Benzinga, an expert cautioned that AI agents could lower the need for human software users, potentially changing how buyers measure value and how software vendors monetize usage over time.

The concern is not framed as an immediate collapse of spending on customer relationship management, IT workflows, or business operations. Rather, it highlights a structural risk. If AI agents do more of the action previously performed by human employees inside business systems, software consumption patterns could evolve away from traditional “more users equals more value” assumptions.

For Salesforce, the pressure point would be tied to its core position as a platform for managing customer relationships, sales execution, and related workflows. For ServiceNow, the analogous question would be around how much of IT and operational work still requires human navigation and task execution within ServiceNow-based processes. In both cases, the expert’s broader point is that AI can change the unit of value, even when the software remains embedded in enterprise operations.

The report also frames the issue as a forecasting problem for the market. Investors watching subscription growth and product expansion have to consider not just whether companies adopt AI features, but whether AI adoption alters spending drivers such as user adoption, seat growth, or day-to-day reliance on human-driven workflows inside the platforms.

Company disclosures on this specific “human user reduction” mechanism were not detailed in the commentary itself. The post does not provide company-specific metrics, guidance changes, or evidence of near-term demand erosion from either vendor, which means the debate remains largely scenario-based rather than data-driven in the cited material.

More broadly, the enterprise software sector is built around workflow automation that can be measured in how many people log in, how frequently tasks are executed, and how deeply teams standardize processes. AI agents introduce a competing pathway, where fewer people may be needed to trigger or complete certain work steps, depending on how confidently the agents can execute tasks end-to-end.

Still, there are uncertainties. Even if AI reduces the number of humans who directly interact with parts of a system, companies may continue to pay for the underlying platforms that govern permissions, approvals, auditability, data integration, and exception handling. The commentary does not address how those governance requirements could offset any reduced “active user” effect.

What to watch next is whether Salesforce and ServiceNow provide clearer indicates on how AI productization maps to monetization. That would include any commentary on consumption trends, seat and engagement metrics, and whether enterprise buyers are shifting to AI-delivered task completion while keeping overall platform spending steady.