tech
How to stop holding AI agents back
Developers of agentic AI have been making some big claims. The promise has been of autonomous systems that can do everything, from booking our flights and keeping an eye on competitors in real time to handling entire procurement cycles , all without needing an actual human to hit “confirm.” And while the technology needed to achieve most of these marvels already largely exists, the infrastructure necessary to make it work reliably at scale still leaves much to be desired.
TL;DR
- Agentic AI promises autonomous systems but faces infrastructure challenges.
- Gartner predicts over 40% of agentic AI projects will be canceled by 2027 due to costs, unclear value, and inadequate risk controls.
- The current web structure resists automated access through personalized results and anti-automation measures like CAPTCHAs.
- Oxylabs' Web Openness Index shows low scores for anti-automation friction and structured data interoperability.
- Within organizations, AI agents struggle with data that is not cleaned, tagged, or structured.
- Latency is another critical issue for agents needing to provide timely information.
- Reliable agent infrastructure requires consistency, currency, and compliance.
- The web was not designed for agents, and their necessary context is often inaccessible or unavailable.
- Solving these data quality and infrastructure problems is crucial for AI agent advancement.