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Manual legislative tracking, checking legislative websites by hand, reading bill text directly, and keeping a spreadsheet of status, gives a team full control and full understanding of exactly what they're looking at, because a person read every word themselves. Its cost is time: it scales roughly linearly with the number of states and bills a team needs to cover, which breaks down quickly for any team operating beyond a handful of states.
AI-driven tracking scales far further with the same headcount, catching bills and hearing mentions a manual process would likely miss simply due to volume, and freeing time for the strategy and relationship work manual tracking crowds out. Its tradeoff is that a team is trusting a system's classification and transcription accuracy, rather than having personally verified every item.
In practice, the strongest approach combines both: AI handles the volume monitoring and first-pass classification, and a person reviews and applies judgment to what surfaces, rather than choosing one extreme or the other.
See what AI catches that manual tracking would miss.
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