Due to these challenges, it’s not realistic to expect a “plug and play” experience when deploying AI agents for legacy systems. That may work in more modern environments, like public clouds, which tend to be consistent and predictable. But don’t expect things to be so easy in a legacy environment.
This doesn’t mean, however, that integrating agentic AI with legacy systems is impossible. It can be done by targeting bounded use cases, such as custom code analysis or test automation, where the requisite data resources and outcomes are well-defined. This is more feasible than attempting to automate large chunks of legacy system management processes using AI.
It also helps to take advantage of modernized versions of legacy software where possible. For example, in an SAP environment, features like SAP BTP AI Core, SAP Graph or SAP Event Mesh can expose SAP business objects to AI agents in a clean, API-consumable format, making it easier to build the necessary integrations.
