Topic starter
05/07/2026 6:56 pm
TL;DR: The rise of the Internet of Agents moves AI risk beyond human-to-machine workflows into AI-to-AI systems that can act independently, call external APIs, and propagate failures across a network, according to Lakera. Security now has to govern containment, traceability, visibility, accountability, and actionability before agentic scale outpaces existing controls.
Editorial analysis by NHI Mgmt Group, based on content published by Lakera: “The Rise of the Internet of Agents: A New Era of Cybersecurity”.
Key questions
Q: What breaks when an AI agent can act across multiple business systems?
A: Traditional helpdesk controls break because they assume a human can be held at the centre of the workflow.
Q: Why do agentic AI systems create more security risk than standard chatbots?
A: Agentic systems can turn model output into action, which means a bad instruction can affect code flow, tool use, and downstream state.
Q: How should teams govern AI agents that can reach APIs, events, and memory?
A: Teams should govern those agents as runtime identities, not as isolated integrations.
Practitioner guidance
- Define runtime agent boundaries Set explicit limits on which tools, data sets, and downstream agents each autonomous system may reach during execution, and require those limits to be reviewable by identity and security teams.
- Map delegated actions to ownership Assign a human owner for every agent workflow that can initiate external actions, and ensure accountability remains visible when the workflow crosses systems or vendors.
- Instrument agent audit trails Capture prompts, tool calls, outputs, and downstream handoffs so investigators can reconstruct how an agent reached a decision and where propagation began.
Bottom line: The article argues that the Internet of Agents changes cybersecurity from user-centric protection to runtime governance of interconnected AI identities.
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05/07/2026 7:19 pm
Agent-to-agent trust is a new governance boundary: The internet of agents breaks the assumption that AI only acts in response to a human request and then stops. Once agents negotiate and execute with other agents directly, the trust boundary moves from the user interface to the runtime relationship between identities, tools, and downstream services. Practitioners should treat agent-to-agent interaction as a distinct governance surface, not just a more complex chatbot workflow.
A question worth separating out:
Q: What is the difference between agent observability and agent containment?
A: Observability tells you what an agent did, while containment limits what it is able to do. Both matter, but observability without containment only helps after a failure, whereas containment reduces the chance that a compromised or misdirected agent can spread its impact.
👉 Read our full editorial: The internet of agents is forcing a new security model