AI and agents are redefining SaaS: end of the monopoly on interfaces, room for agile, agent-ready backends focused on sovereign data.
Corporate information systems have accumulated, decade after decade, a profusion of tools and interfaces, more or less ergonomic. Each business need has given rise to a dedicated application, each process to its own portal, each team to its specific environment. Result: routes are fragmented to accomplish simple everyday tasks.
With the rise of AI, and of agents in particular, this mode of interaction will be disrupted. No more favorites to HRIS, ERP, CRM or knowledge base. Tomorrow, a natural language assistant will make it possible to ask all the useful questions about your job and the company’s ecosystem, and to obtain contextualized answers.
But these agents won’t just respond. They will act. Directly on the IS. Apply for leave, declare real expense reports (source), publish a report on trends in a targeted market, carry out very operational tasks… These actions will be delegated to a constellation of specialized agents, orchestrated by MCP servers capable of guaranteeing reliable and audited processes.
Is SaaS dead?
No, but he must mutate. The SaaS model as we know it, centered on interfaces that we use in a browser, will become less prevalent. These interfaces, often fixed and designed for generic uses, no longer meet the requirements for agility, customization and operational efficiency that companies expect today.
Value will shift to robust and agile backends, designed to automate and make business processes more reliable. They will be exposed via APIs and controlled by specialized agents capable of interacting in natural language, and delegating tasks to specialized microservices.
This paradigm shift does not mean the disappearance of SaaS, but the end of its monopoly as an interaction layer. Certain tasks will be delegated, and human–machine interactions will become more natural. Managing change will be made easier: even if our generation grew up with these interfaces, there is nothing natural about them. The boundaries between applications will gradually blur until, hopefully, they disappear. In this new landscape, the SaaS publishers who survive will be those who have been able to pivot towards agent-ready architectures, focused on usage, modularity and interoperability.
And the data in all this?
The nerve of war when it comes to AI, data is the jewel of the company: strategic, critical and often confidential. In an uncertain geopolitical context, IT players are looking for trusted alternatives to limit exposure to exogenous risks linked to international political developments (customs duties, suspension of services, control of data, etc.).
Agentic engines that manipulate this sensitive data must be able to run in controlled environments, in order to guard against these risks. However, the capabilities, features and scale offered in Europe are not comparable, at this stage, to those available in the United States or China. Hence the relevance, more than ever, of a hybrid or even multicloud strategy in a logic of dynamic arbitration, based on the criticality of data, regulatory requirements and business imperatives.
The classification of workloads according to the criticality of the data makes it possible to build a data and AI platform adapted to the different needs of the company, by intelligently arbitrating between sovereignty, performance and costs. It is this granularity, this ability to modulate infrastructure choices according to the context, which will make the difference in the years to come.
The era of intelligent agents does not signal the end of SaaS, but the end of its monopoly as an interface layer. The companies that succeed will be those that design agent-ready backends, strengthen their data governance and adopt pragmatic hybrid architectures.
The key: more efficiency, less friction and an in-depth transformation of business processes that is truly focused on usage. With, perhaps, the birth of a new principle of AaaS: Agent as a Service.
