Group 1 - The emergence of "Agentic Tool Sovereignty" (ATS) challenges the legal control of AI systems by states and providers, as AI agents operate autonomously and can invoke third-party tools across jurisdictions [1][3][12] - AI agents are defined as goal-oriented assistants that facilitate autonomous actions with minimal human input, complicating regulatory compliance under static models like the EU AI Act [1][2][3] - The disconnect between the static compliance model of the EU AI Act and the dynamic tool usage of AI agents creates a responsibility vacuum for both providers and deployers [2][8][10] Group 2 - The legal framework of the EU AI Act assumes a static relationship and predetermined data flows, which is incompatible with the autonomous, cross-jurisdictional tool invocation by AI agents [3][11][12] - The concept of "substantial modification" in the EU AI Act is ambiguous when it comes to runtime tool invocation, leading to challenges in liability and compliance [5][6][9] - The responsibility for data processing is fragmented across the AI value chain, complicating accountability when AI agents autonomously select tools [8][9][10] Group 3 - The EU AI Act's post-market monitoring requirements face structural challenges, particularly in tracking interactions with external tools that may not be disclosed or auditable [6][7][8] - The traditional data sovereignty focus on territorial control is inadequate for AI agents that make autonomous cross-border decisions, necessitating a rethinking of sovereignty concepts [12][13] - The lack of specific guidelines for AI agents and their autonomous tool usage under the EU AI Act creates significant regulatory ambiguity for providers [13][14]