Gartner estimates that up to $234 billion in enterprise application software spending will be exposed to “agentic arbitrage” between now and 2030. By the end of the decade, the affected spending could represent approximately 20% of enterprise application software-as-a-service expenditure.

Agentic arbitrage occurs when AI agents complete tasks across several enterprise systems, reducing the need for employees to interact directly with multiple software interfaces. As agents deliver outcomes across applications, software usage may become less closely tied to the number of individual users or licensed seats.

Agentic AI Challenges SaaS Economics

“Agentic AI changes the economics of software,” said George Brocklehurst, Managing Vice President at Gartner. “Agentic systems deliver outcomes directly, bypassing traditional user experience (UX)-heavy applications and making the software invisible. This breaks the link between user growth and revenue growth for many enterprise software vendors.”

Gartner expects enterprise buyers to place less emphasis on purchasing additional tools, features, and dashboards. Instead, organizations will increasingly assess software according to measurable outcomes and its ability to retain institutional knowledge and customer context over time.

Some vendors are already developing agentic offerings capable of autonomous workflow execution and orchestration across multiple systems. Gartner said these deployments can help capture organizational context and support business outcomes, although they currently tend to require significant services involvement.

Why It Matters

The shift creates direct pressure on incumbent software providers built around interfaces and seat-based licensing. Gartner said vendors will need to embed agentic capabilities at the point where work is executed, move from interface-based value to outcome-based value, and retain customer-specific knowledge rather than focusing only on data.

“While this shift is posing an existential threat for vendors who are defending legacy dashboards and seat-based models, it creates a substantial revenue opportunity for vendors who are enabling and developing services and platforms to support agentic cross-domain workflows,” said Brocklehurst. AI-native startups and service providers could act as an agentic layer across existing enterprise systems, helping organizations redesign workflows and directing software spending toward measurable results.