Agencies face many challenges when it comes to data sharing. For example, there is no solid validation process when it comes to searching and sharing information. With data sharing challenges, it’s difficult for agencies to assure what data was used when building the solution. This is especially important when using external Artificial Intelligence (AI) models. When agencies implement these external AI solutions, knowing what data was used helps to reassure that no bad actors or data disrupted the model.Concepts, such as federated AI, offer a possible solution for validating data. Federated AI helps agencies to share data through algorithms by maintaining a central location for each of the agencies’ data. Most importantly, the raw data never leaves the agency’s security perimeter, which allows agencies to know that the data they are working with are still valid.These were the key themes in the third part of our The Evolution of Artificial Intelligence in Government podcast series, hosted on Government Technology Insider, where Kal Voruganti, Senior Fellow and Vice President at Equinix; and Scott Andersen, Distinguished Solution Architect at Verizon, discussed this topic further.