The Tool Desk
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What Vermont means by AI as a “power tool”
Vermont Chief Data and AI Officer Josiah Raiche describes a power tool as something a trained person operates within a process designed by people. The point is to let employees focus on outcomes while keeping them responsible for how the tool is used and what happens next.
“The operator is well trained, and then a good power tool lets you zoom out from mechanics and think about outcomes,” Raiche told StateScoop on October 2, 2026. He called the framing “an inherently kind of limiting opinion about how to use AI,” emphasizing that the technology belongs within a human-created process rather than operating on its own.
Where Vermont employees are using AI
Finding and fixing software vulnerabilities
Vermont has roughly 1,100 state applications, according to Raiche’s account to StateScoop. That figure describes the application estate, not a count of applications analyzed or repaired. The state was training developers to use AI to inspect source-code segments, model possible attack paths, generate Python checks and identify vulnerabilities that developers can remediate.
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Raiche said about 100 developers had completed training, with another 50 expected, and that several dozen applications had been patched. He described using AI to group similar vulnerabilities and help generate fixes, which developers then check to ensure the changes do not disrupt front-end behavior. These are figures and outcomes reported by Raiche, not independently audited results.
Helping agencies build task-specific tools
Vermont’s agency “pathfinders” are employees trusted by colleagues and leadership who receive early training and roughly a three-month head start to build practical tools before wider team training. The intended benefit is to surface useful applications from employees’ day-to-day work, rather than relying only on centrally selected projects.
In a half-day cross-agency workshop, participants used ChatGPT-style tools, an internal chatbot, prompt frameworks and custom GPT skills. Raiche described a Corrections commissioner and a Department of Financial Regulation participant building a tool to evaluate securities offered in Vermont. The account does not establish that this prototype was deployed or used to make final decisions.
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Flagging possible ballot errors for staff review
Raiche described a Secretary of State’s office request involving hundreds of ballots and a spreadsheet of roughly 3,000 candidates. An AI skill flagged likely errors and uncertain cases. Staff then reviewed every ballot, checking the flags and looking for errors the system might have missed.
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Raiche said the work took three hours and avoided expected overtime. This is a state-reported example, not an independently validated study of accuracy or savings; staff, not the AI, checked the ballots.
What guidance and oversight underpin the approach
Vermont’s AI governance work predates the 2026 examples. The state established an AI task force in 2018; StateScoop reports that the task force recommended a statewide AI code of ethics in a 2020 report. The Vermont AI Council’s September 30, 2025 update lists a Code of Ethics (2023), Guidelines for AI Implementation and Data Management (2024), and Employee Use of Generative AI (2024).
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The implementation guidelines establish impact assessment, risk management, mitigation and monitoring, as well as a standard usage notice for AI systems used in decision-making. The employee-use guidance sets acceptable-use expectations for state employees. The Council’s stated principle is that “AI Systems should be used in a human-centered way that recognizes the dignity and value of all persons and their contributions to society.”
The Agency of Digital Services’ AI Division and Council 2024 Report says Vermont envisions responsible AI as a “power tool for information workers.” It recommends training in standard AI patterns and job-specific tools, and says workers should understand what systems can and cannot do.
What the reported adoption figures show—and do not show
In its September 2025 update, the Vermont Agency of Digital Services and AI Council reported 300+ employees trained as AI Change Agents and 500+ weekly active users of ChatVT. Those figures indicate training and use of the state’s chatbot, but they do not by themselves establish improved service outcomes or productivity.
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The 2026 examples add task-level accounts from Raiche, including developer training, patched applications and ballot-proofing time. The sources cited here do not provide independent evaluations of the pilots, measured accuracy or a general estimate of time or cost savings. Vermont’s examples illustrate how it says employees are applying AI; they are not proof that the same results will recur across agencies or tasks.
How Vermont is leveraging AI across government, one “power tool” at a time
The practical pattern is to train employees, let agencies identify bounded tasks, use AI to assist with parts of a workflow, and keep people responsible for reviewing consequential output. Vermont’s guidance names assessment, risk management, mitigation and monitoring as governance mechanisms. Whether the approach produces reliable gains at scale will depend on evidence about accuracy, service outcomes and oversight—evidence not established by the reported examples.
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