Key takeaways
- Agentic AI is evolving from isolated tools into an interconnected agentic web that transacts across organizations
- Risks shift from single-system safety to ecosystem-level economic and systemic dynamics
- Market manipulation, collusion, chokepoints and shadow agents can emerge at machine speed
- Legal liability ambiguity and cross-border fragmentation may distort incentives and slow adoption
- Governance must be embedded into infrastructure through policy-as-code, verifiable identity, red teaming and guardian oversight systems
The next phase of AI will move beyond smarter models and into autonomous agents interacting across organizational boundaries, and when agents form interconnected networks, an “agentic web,” the risk landscape fundamentally changes. A recently released white paper, Economic and Systemic Considerations in Agentic Web Systems, argues that when agents form interconnected networks, an “agentic web,” the risk landscape fundamentally changes.
Rather than individual agent risks such as goal hijacking or privilege abuse, attention shifts to market dynamics: negotiations at machine speed, chokepoint power in discovery layers, shadow agents evading oversight and correlated behaviors that can amplify shocks across sectors.
The paper frames agent interactions in a five-stage economic transaction lifecycle: registration, discovery, negotiation, settlement and monitoring. This lifecycle lens can help organizations understand where systemic incentives and failures, are most likely to emerge.
Learn more in this article, authored by Heather Domin (Vice President and Head of Office of Responsible AI and Governance, HCLTech), Pradyumna Chari (Postdoctoral Associate, MIT Media Lab), Ramesh Raskar (Professor and Associate Director of MIT Media Lab), and Grace Davin (Enablement Leader, Office of Responsible AI and Governance, HCLTech).
