AI use cases in information management – where are we today?
Jinfo Blog

By Anja Chemnitz Thygesen

Abstract

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AI is already finding its way into many parts of information management.

But Jinfo's latest poll and further research suggests an important distinction between the breadth of AI use and the depth of its integration into workflows.

Most examples we found are still focused on individual tasks: AI searches, summarises, analyses, categorises or drafts. There are examples where AI performs several connected tasks, and some early workflow automation, but fully connected end-to-end processes are much less common.

That is not necessarily a problem. In fact, it points to a practical way forward: rather than starting by designing autonomous workflows, information teams can build outward from AI tasks that are already proving useful.

Across Jinfo's survey and qualitative research, current use clusters into seven areas:

Figure: Examples of AI use in information management

The examples also show that AI is moving beyond researching and handling information itself. It is beginning to support decisions about the information portfolio - from analysing usage and identifying super-users to reviewing vendor agreements, benchmarking costs and assessing overlap between subscription resources.

As one information manager told Jinfo:

"We use AI to synthesise input from many people about the value (or not) of resources up for renewal so that we can be sure we're spending our money on the right stuff."

The question, then, is not simply:

"What can we use AI for?"

... but how to:

1. identify the tasks where AI is already creating value
2. determine which can become repeatable workflows
3. understand what is feasible given access, rights and governance.

Our new report, "AI use cases in information management – from tasks to workflows", explores how information teams can do exactly that.

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