In two earlier posts I argued that SaaS is being disrupted rather than killed, and that the per-seat revenue model is on its way out. The dramatic decline in market capitalization of SaaS vendors over the past 9 months, sometimes referred to as the SaaS-pocalypse, is partly about investors pricing in the fear that SaaS applications will recede behind an AI agent layer. This would make the SaaS applications become invisible “featureware,” with the agent capturing the user relationship, the workflow, and, eventually, the budget.
This post will show that enterprise buyers now expect their software vendors to supply the agents, and to serve as the trusted source of data and context for custom-built and third-party agents. This is the natural next progression for SaaS vendors and represents an attractive market opportunity.
To avoid confusion, here are IDC’s AI-related definitions. An AI assistant is conversational and works as a tool for a human. An AI agent is autonomous, uses other tools, and carries memory and context across tasks. An agentic workflow is a business process that an agent executes end-to-end with limited human intervention.
SaaS vendors are faced with a dual threat, hence SaaS-pocalypse
The first threat is that organizations will simply write their own applications instead of buying standard SaaS applications. This threat triggered the dramatic devaluation of SaaS stock in February as Anthropic released its Code capabilities. Conversations with CIOs in enterprises partly validate this fear. While they are not contemplating creating core accounting, HRIS or workforce management applications, they might build rather than buy auxiliary applications in areas such as planning, performance management, compensation management, logistics planning, etc. Application areas where customer requirements vary widely and where legal complexity is low are moving gradually from buy to build.
The second threat is that agentic overlays will increasingly handle the user interaction while AI agents access SaaS applications via API interfaces to carry out transactions on behalf of the human user. The implication is key price justifiers of SaaS applications, such as the interface, the feature breadth, and the brand gradually disappears from the users. This also implies that the per-seat user pricing stop making sense, when users are no longer the primary users of SaaS applications.
AI agent adoption is already past the tipping point
In IDC’s April 2026 Future Enterprise Resiliency and Spending survey of organizations with 500 or more employees, 74% had already deployed at least one agent, 15% were piloting, and only 1% reported no use and no plans. The same respondents expect the number of agent types in production to roughly triple, from 24 in March 2026 to 62 by 2027. Buyers are not evaluating whether to enter the agentic era. They are deciding which parts of their operation to hand over first, and operational and core business data are their top target.
The big question is who will deliver these AI agents. Most organizations have deployed standard AI tools and run pilots, but few have redesigned core processes to use AI at scale. The survey results shows that most organizations deploy ready-made agents wherever they can, rather than build their own.
Where Vendor-Supplied Agents Win
IDC distinguishes four kinds of agent by who builds them and how the buyer obtains them. In-application agents come packaged inside the application and the buyer simply adopts them. Low-code / no-code agents are configured by the buyer in a visual builder the vendor provides. Standalone agents are third-party products the buyer implements alongside existing applications. Custom-built agents are assembled by internal teams using full-stack orchestration frameworks.
The survey data, which focuses on AI agent quantities as opposed to spend, points in one direction. The two types that vendors supply directly, in-application agents and low-code or no-code builders, are growing fastest in numbers and from the largest installed base. Custom-built agents show the slowest growth, because the orchestration they require is more difficult and require more inhouse skills to build. Buyers prefer to adopt or configure an agent that already understands their data and respects their permissions over building one from scratch.
SaaS applications as trusted data and context for custom-built agents
IDC also sees a massive demand for custom-built AI agents, especially for core business processes that are unique to an industry or an organization. Standalone products and custom-built agents will operate inside the same enterprise, and they will need data and context that lives inside your application.
A custom-built or third-party agent that accesses data “from anywhere” still needs a place where the data is correct, the process is compliant, the permissions are enforced, and the transaction is guaranteed to execute. A SaaS vendor can offer vetted business processes, governed data, and audit trails for custom AI agent consumption. This is, in IDC’s view, a key future role for today’s SaaS applications.
What the AI-pivoted SaaS application looks like
The interface stops being a single screen and becomes several modes serving the same processes: the traditional UI, a conversational UI, a flow-of-work UI embedded where the user already operates, and machine interfaces so external agents can call the application directly and safely.
The AI-pivot requires SaaS vendors to rethink the workflow from the ground up, which touches the full stack: foundation models, an embedding layer, a vector database, retrieval-augmented generation, an orchestration layer, guardrails, monitoring, and version management. The vendor also has to give buyers an agent toolkit of their own, so that the low-code and no-code configuration buyers increasingly demand happens inside the vendor’s governed environment rather than outside it.
European vendors carry an additional set of requirements that, handled well, become a selling advantage. Compliance with GDPR, NIS2, and the EU AI Act (still there despite the recent delay), data residency and sovereign cloud guarantees, genuine multi-language model performance, and transparency in how the AI reaches a decision are all conditions of sale to compliance-sensitive European buyers.
SaaS is not dead, and the incumbents are not doomed. But the asset that justifies a vendor’s existence is shifting from the screen the user looks at to the agents the vendor supplies and the governed data those and other agents rely on. Your customers already expect you to be their agent supplier. The only question is whether you are ahead of that shift or reacting to it.
So what do you actually do with this? There are three concrete moves software vendors need to make in the near term. They are specific, they are sequenced, and the window to move first is closing. I will walk through all three in a focused 25-minute webcast, grounded in IDC survey data from more than 1,000 enterprise organisations: where your customers sit on the AI maturity curve, why vendor-supplied agents will dominate enterprise deployments through 2030, and which ERP and SaaS processes are attracting the most AI investment right now. Secure your spot here.