Netskope details survey findings on balancing AI speed and security

Netskope’s survey of 100 North American financial services IT leaders finds that organizations are adopting AI quickly, yet most say they cannot accelerate deployment without harming security or operational integrity. The reported gap adds urgency for CISOs and CIOs to operationalize governance as AI use expands.

Research Overview

The blog summarizes results from a survey of 100 IT leaders in financial services across North America. Netskope uses the responses to describe adoption momentum and the obstacles leaders associate with AI governance.

Respondents are asked about the ways their organizations are adopting AI and the extent to which they believe they can scale while maintaining security and operational integrity. The blog frames the governing question as shifting from whether to use AI to how to govern it before security impact occurs.

Key Findings

Survey results report that 62% of organizations have adopted managed third-party AI applications. The same responses indicate that 54% are building private internal AI applications.

According to the blog, 26% of organizations are experimenting with autonomous AI agents, and many organizations use more than one approach. Only 1 in 100 respondents believe they can accelerate AI adoption without compromising security or operational integrity.

Technical Breakdown

The blog describes three “potholes” that hinder progress, beginning with shadow AI, defined as employees using consumer AI tools that the organization has not approved. It reports that 56% of IT leaders are concerned about sensitive financial data leaking into public models without detection.

The survey also cites data sprawl and compliance risk as a concern for 43% of leaders. The blog adds that 53% are worried about losing visibility into how AI makes decisions, referencing regulator expectations for explanation of automated calls.

Operational Impact

Infrastructure is described as the primary barrier to addressing the concerns raised by the survey, with 60% of leaders pointing to legacy architecture as the roadblock to AI product launches. The blog reports additional barriers, including insufficient investment cited by 31% and fragmented, siloed security tools cited by 21%.

The blog states that progress should not be slowed, but that security architecture supporting AI adoption needs to catch up with adoption pace. It argues for integrating visibility into governance rather than treating it as separate from existing security capabilities.

Leadership Perspective

The blog attributes successful scaling to treating AI governance as an extension of the security stack rather than as a standalone initiative. It states that bolting on standalone AI monitoring tools to disconnected point products adds blind spots.

It also describes using an approach that incorporates AI visibility into a control plane so security teams can handle AI activity with similar discipline to regular network traffic. The blog uses zero trust as the example framework for continuous verification of users, devices, and AI applications.

The Netskope survey describes rapid AI adoption in financial services alongside limited confidence in scaling without security or operational integrity compromises. It emphasizes governance execution, visibility, and architectural alignment as adoption expands, and this “Blog Signals brief” is a fact-based summary of the vendor blog.

Blog post, originally published by Kevin Cornejo at netskope.com.