Big News: Agentic AI is transforming industries, but its adoption is hindered by a significant trust gap. Honestly, this is where most enterprises fail - they can't inventory, scope, or revoke agent identities at machine speed. The math doesn't add up. In my experience, it's not about model capability or compute; it's about identity governance.
I recently spoke with Cisco President Jeetu Patel, who revealed that 85% of enterprises are running agent pilots, while only 5% have reached production. That 80-point gap is a trust problem. The first questions any CISO will ask: which agents have production access to sensitive systems, and who is accountable when one acts outside its scope? (Read also: Revolutionizing Healthcare: Top Tech Trends for 2026)
The 2026 IBM X-Force Threat Intelligence Index reported a 44% increase in attacks exploiting public-facing applications, driven by missing authentication controls and AI-enabled vulnerability discovery. It's a wake-up call for enterprises to reassess their IAM strategies. (Read also: Big News: iOS End-to-End Encrypted RCS Messaging Revolution - Technical Deep Dive)
Breaking the Trust Barrier: A New Era for Agentic AI
Michael Dickman, SVP and GM of Cisco's Campus Networking business, laid out a trust framework that security and networking leaders rarely hear stated this plainly. The network sees what other telemetry sources miss: actual system-to-system communications rather than inferred activity. It's that difference of knowing versus guessing. What the network can see are actual data communications … not, I think this system needs to talk to that system, but which systems are actually talking together.
Dickman argues that agentic AI breaks a pattern that defined every prior technology transition: deploy for productivity first, bolt on security later. I don't think trust is one of those things where the business productivity comes first, and the security is an afterthought. Trust actually is one of the key requirements. Just table stakes from the beginning.
The trust prerequisite that most AI strategies skip is the foundation for cross-domain correlation. The real power comes from the cross-domain views. The real power comes from correlation. Versus just aggregation and deduplication of alerts, which is good, but it's a little bit basic. (Read also: AI in Finance: KPMG Survey Reveals Scaling Challenges and Talent Gap)
Before agents reach production, enterprises must prioritize cross-functional alignment, IAM and PAM governance, platform approach to networking infrastructure, hybrid architectures, and bulletproof trust for the first use cases. It's a matter of guaranteeing trust to the organization, and that will unleash the speed.
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