AI agent adoption to expose infrastructure, security gaps in 2026

IT Brief United Kingdom reports that the rapid enterprise adoption of AI agents in 2026 is predicted to expose critical bottlenecks in data infrastructure and security, with industry executives forecasting consolidation around a few dominant frameworks and significant challenges in identity protection and specialized talent.

According to Redis VP Manvinder Singh, the primary constraint will shift from model reasoning to "serving them the right context at the right time," necessitating unified "context engines" to replace the fragile patchwork of disparate databases and caches currently used for agent memory and retrieval. Simultaneously, Singh expects the "agent framework wars" to crystallize around two or three dominant, open platforms, like LangGraph or offerings from hyperscalers, that foster extensive third-party ecosystems.

On the security front, Rubrik's David Rajkovic warns that AI agents act as a "force multiplier" for both capability and risk, with compromised agent identities potentially unleashing damage at machine speed, making identity and access controls a critical 2026 battleground.