Answer
Concrete examples make this easier to evaluate than the general category. AI can help document legacy RPG or COBOL programs by generating plain-language summaries of what a subroutine does, which speeds up onboarding without touching production code. It can power an internal search or chatbot layer over existing runbooks and knowledge base articles so support staff find answers faster. It can summarize job log errors and system alerts to help a support team triage what needs attention first, and it can generate a natural-language query layer over Db2 for i reporting views, as long as that layer only has read access and cannot alter data.
The common thread across safe pilots is that a human stays in the approval loop for anything with real consequences, the AI tool works against a defined, access-controlled data source rather than open production systems, and there is an audit trail showing what the tool was asked and what it returned. Buyers should ask any AI vendor exactly what access their tool requires, whether it can write to Db2 for i or only read from it, and how prompts and outputs are logged and retained, before treating a demo as evidence the tool is safe for production use.