Aha! AI usage history is only available for 90 days. After that window, teams lose access to historical reporting data and cannot review longer-term trends in adoption, usage patterns, or changes over time.
Teams cannot analyze AI usage over longer periods such as quarterly, half-year, or annual reviews.
It is harder to measure adoption, demonstrate value, and report on ROI to leadership.
Lost historical data limits planning for enablement, governance, budgeting, and license decisions.
Product and operations teams cannot identify longer-term trends, seasonality, or the impact of training and rollout efforts.
Longer term AI reporting is incomplete or requires manual exports and separate storage.
Extend AI history reporting beyond 90 days so teams can retain and analyze historical AI usage data over longer timeframes.
Provide flexible reporting ranges such as 6 months, 12 months, and custom date ranges.
This would help organizations track adoption, measure business value, support governance, and make better long-term decisions about AI usage.