A series of high-profile AI failures heightens public concern and erodes confidence, but skepticism also grows when organizations fail to realize clear productivity gains from AI investments, calling cost and value into question. Weak adoption can cool investor enthusiasm, while economic and political pressures — particularly around workforce replacement — discourage early adoption in government. In response, governments tighten oversight and regulation, slowing the pace of adoption and placing greater emphasis on reliability, transparency and risk management. AI remains in use, but expectations around performance, accountability and public trust rise sharply, with progress defined less by speed and more by assurance, scrutiny and acceptance.
Download the ebook
Agencies reassess existing AI deployments following public scrutiny or regulatory review. New projects move forward selectively, with expanded testing, documentation and audit requirements. High impact uses of AI in areas such as benefits administration, public safety and education operate with clear human oversight, while agencies invest time in rebuilding trust.
See chapters