digital-footprint-analysis-tm
A practical consulting framework (Digital Footprint Analysis™) for discovering and managing ‘shadow AI’ inside organizations. It prescribes data collection (e.g., 30-day network and authentication logs), detection approaches (pattern recognition, risk prioritization), reporting artifacts (shadow AI inventory, risk heatmap, time-compression metrics), and an implementation timeline of quick wins (0–14 days), mid-term adjustments (15–30 days), and strategic outcomes (30+ days). The document also includes policy guidance (dynamic permissions, 30-day review cycles), recommended tooling (Wireshark, Splunk, Power Automate), and author bios for Peter Swain and Betsy Tong (ADAPT co-architects).
Questions this document answers
30-day network traffic logs and authentication data.
Every 30 days.
Quick Wins (0–14 days); Mid-Term Adjustments (15–30 days); Strategic Outcomes (30+ days).