The conversation surrounding artificial intelligence (AI) in federal information technology is evolving beyond rudimentary applications like chatbots and task automation. In a recent podcast produced by Scoop News Group, Mia Jordan, a public sector strategist at Salesforce and former Chief Information Officer at the Departments of Agriculture and Education, emphasized that the fragmented digital frameworks currently employed by government agencies hinder their operational effectiveness. Jordan argues that this disjointed approach represents not merely an inconvenience, but a structural vulnerability that obstructs agencies from fulfilling their missions to their fullest potential.
This inefficiency is largely attributed to what Jordan terms “swivel servants”—government personnel who must manually navigate between disconnected systems. She pointed out that employees frequently switch between various applications more than 1,000 times each day, a repetitious cycle that not only drains productivity but also heightens the risk of human error. This fragmentation creates challenges, particularly for agencies involved in rapid response or complex procurement, as critical information often resides outside official systems of record. As a result, leaders may find themselves making high-stakes decisions based on incomplete or outdated data.
To tackle this issue effectively, Jordan advocates for a fundamental reevaluation of how work is structured within federal agencies. Instead of simply adding new AI tools as band-aids, she suggests that agencies should cultivate an environment where AI agents operate seamlessly within a unified, secure platform that coordinates tasks across departments. In this paradigm, AI transitions from being a separate layer to becoming an integral part of a cohesive work environment. The key to this transformation lies in establishing a shared operating layer that integrates disparate tools into a streamlined workflow, enabling agencies to automate routine tasks like summarization, approvals, and task assignments directly within their daily operations.
Despite the evident advantages of moving toward this more integrated model, federal IT leaders remain cautious about modernization strategies that necessitate expensive “rip-and-replace” overhauls of legacy systems. Jordan proposes a more pragmatic approach through zero-copy data architectures, which allow AI to access insights from multiple systems without the risks or costs associated with physically transferring or duplicating sensitive data. By utilizing zero-copy architectures, agencies can realize the benefits of a more integrated enterprise while preserving the integrity of their existing data silos. “We’re going to blur the lines a little bit now… because information and data can be shared and become a lot more meaningful to more people,” Jordan noted.
Ultimately, the transition toward an agentic enterprise approach aims to reduce the operational friction that hampers mission execution. By transforming fragmented digital landscapes into coordinated platforms, agencies can ensure that data, workflows, and AI-driven support operate in harmony. This shift allows leadership to devote less attention to the mechanics of transferring work between various systems and more focus on achieving mission outcomes. Jordan encapsulates this shift by asserting that the true promise of the agentic enterprise lies in its ability to provide clarity: “When work happens in a unified environment, leadership can focus more on the outcomes… because the work is now in a single space.”
This interview is part of FedScoop’s Agentic AI Advantage podcast series, sponsored by Salesforce. For further insights into Agentic AI in government, additional expert perspectives are available through the podcast series.
This video podcast was produced by Scoop News Group for FedScoop and underwritten by Salesforce.
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