Information governance has long been a challenge for government agencies. They manage vast volumes of data, much of it held as paper records or stored as unstructured data, such as forms, PDFs, emails, and other formats — all of them notoriously difficult to search, classify, and analyze. These challenges are compounded by the prevalence of ROT: redundant, outdated and trivial information. While none of this is new, the increasing adoption of AI solutions has raised the stakes.
For AI to deliver value, agencies don’t need to introduce a slew of new processes. Instead, they should double down on core information governance and records management practices. That begins with understanding what information they have and where to find it, then applying metadata to make it searchable. Otherwise, agencies run the risk of putting AI to work without a full picture of their data, said Fred Pulzello, Senior Consultant at Iron Mountain Government Solutions.
“Information governance needs to be addressed prior to AI [deployment],” Pulzello said, “and it will need to be adapted for upcoming AI capabilities, which are just getting bigger and better all the time.”
In this video, Pulzello and Ronald Sodano, also a Senior Consultant with Iron Mountain Government Solutions, discuss how agencies can integrate information governance disciplines in their AI strategies. Topics addressed include:
- Developing a governance framework for addressing unstructured data
- Improving the consistency of data management across different formats
- Leveraging physical records in AI initiatives
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