Making AI operational in constrained public sector environments
View original at technologyreview.comMIT Technology Review - Ai Research Title: Making AI operational in constrained public sector environments Date: 2026-04-16 13:00 Source: https://www.technologyreview.com/2026/04/16/1135216/making-ai-operational-in-constrained-public-sector-environments/ <p>The AI boom has hit across industries, and public sector organ…
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Large language models generate text based on training data with a cut-off date, causing hallucinations for newer information, which can be solved by forcing models to work from verified sources
60% confidenceBy 2027, organizations will use small, task-specific AI models three times more than general-purpose large language models
60% confidenceGovernment organizations don't often purchase GPUs and are not used to managing GPU infrastructure, making accessing GPUs a bottleneck
60% confidenceGovernment agencies must be very restricted about what kind of data they send to the network, which sets boundaries on how they manage their data
60% confidenceIt is easy to use ChatGPT for proofreading but very difficult to run large language models smoothly in environments with no network access
60% confidenceDo not start with a chatbot; start with search, as much of AI intelligence is about finding the right information
60% confidenceToday's AI can provide a completely new view of how to harness data
60% confidence79 percent of public sector executives globally are wary about AI's data security
60% confidenceWhen people in the public sector hear AI, they probably think about ChatGPT, but we can be much more ambitious as AI can revolutionize how government searches and manages large amounts of data
60% confidenceMany people undervalue the operating challenge of AI, and the public sector needs AI to perform reliably on all kinds of data and grow without breaking
60% confidenceThe public sector has a lot of data and doesn't always know how to use it or what the possibilities are
60% confidence
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