‘Cybersecurity response is moving slower than AI adoption, creating more issues’
‘Cybersecurity response is moving slower than AI adoption, creating more issues’
Publish Date: 2026-02-27 01:22:00
Source Domain: cxotoday.com
The rapid pace of AI adoption has magnified the structural weaknesses within the cybersecurity industry. Tool sprawl and fragmented security layers have created a huge vulnerability gap and are hindering the ability to deal with emerging threats triggered by rapid AI adoption. According to Gartner, 40% of enterprise applications will be using task-specific AI agents in 2026, which makes visibility more critical than ever.
In an interaction with CXOtoday, Binod Singh, Founder and CEO of Cross Identity, an identity and cybersecurity company, talks in detail about some of these challenges and how they can be addressed. Singh also dwells on the evolving role of Zero Trust architecture in the age of agentic AI, and how and where his company is using AI to negate AI-driven risks. Edited excerpts:
Q. How do you see the Zero Trust architecture evolve in response to the growing use of GenAI and agentic AI?
Zero Trust architecture has seen shifts based on evolving threats and technological advancements. But the most significant shift is happening because of AI. The traditional user-to-app security model is being replaced by a machine-to-machine (M2M) and agent-to-agent (A2A) reality.
The first shift is the rise of non-human identity management. In the past, Zero Trust was essentially focused on verifying human employees. Today, autonomous agents outnumber humans in many enterprise environments. Organizations are moving away from static service accounts or shared application programming interface (API) keys. Agents are now assigned cryptographic identities. Every thought or action an agent takes must be signed and authenticated.
The second major shift is the micro-segmentation at the prompt level. Traditional micro-segmentation is used to isolate networks or workloads. With GenAI, the attack surface is often the data layer itself, not the networks and workload layer. If an agent has access to a vector database, it might accidentally leak sensitive information…
