Armor, a global provider of cloud-native managed detection and response (MDR) services protecting more than 1,700 organizations across 40 countries, has issued new guidance urging enterprises to urgently establish formal AI governance policies. According to the company, organizations that deploy artificial intelligence tools without structured oversight are introducing dangerous blind spots into their security posture, while simultaneously increasing the risk of data exposure, regulatory violations, and AI-specific attack vectors.
As businesses accelerate the adoption of AI across departments such as customer service, marketing, development, and operations, Armor’s security teams are observing a widening gap between innovation and control. While AI promises productivity and automation benefits, unmanaged usage is quietly expanding enterprise attack surfaces beyond what traditional security frameworks were built to monitor.
“If your organization is not actively developing and enforcing policies around AI usage, you are already behind,” said Chris Stouff, Chief Security Officer at Armor. “You need clear rules for data, tools, and accountability before AI becomes a compliance and security liability. The result is an expanding attack surface that traditional security controls were not designed to address and a compliance liability that many organizations do not yet realize they are carrying.”
Cyber Technology Insights: World Wide Technology Unveils ARMOR: A Collaborative AI Security Framework with NVIDIA AI
The AI Governance Gap Becomes an Operational Threat
As AI tools embed themselves deeper into everyday workflows, Armor emphasizes that the absence of governance frameworks now represents a material operational risk. Most notably, the company highlights that many organizations lack visibility into how employees interact with AI platforms and what types of data are being shared.
One of the most urgent concerns involves data loss prevention gaps. Employees routinely input sensitive corporate data, intellectual property, source code, and customer information into public AI tools. However, many of these interactions bypass traditional DLP controls, exposing organizations to silent data leakage and policy violations.
At the same time, shadow AI adoption continues to rise. Business units frequently deploy unapproved AI tools without IT or security oversight, creating unmonitored data flows that often surface only after an incident or during compliance audits. Furthermore, Armor notes that many enterprises treat AI policies as standalone initiatives rather than embedding them into governance, risk, and compliance (GRC) programs. As a result, organizations struggle to demonstrate responsible AI use to regulators, customers, and auditors.
Adding to the challenge, emerging regulations such as the EU AI Act and sector-specific mandates in financial services and healthcare are placing new compliance expectations on organizations expectations many are not yet prepared to meet.
Cyber Technology Insights: stackArmor, a Tyto Athene Company, Partners with Tenable Cloud Security and Carahsoft
Healthcare Faces Elevated Stakes
While AI governance is critical across all sectors, Armor stresses that healthcare organizations face especially high risk. Health systems increasingly rely on AI for clinical documentation, diagnostics support, and operational efficiency. However, this rapid adoption intersects directly with HIPAA and other healthcare regulations.
“Healthcare organizations are under enormous pressure to adopt AI for everything from administrative efficiency to clinical decision support,” Stouff added. “But the regulatory environment has not caught up, and the security implications are significant. Organizations need clear policies that address what data can be used with which AI tools, how outputs are validated, and who is accountable when something goes wrong.”
In healthcare environments, even accidental exposure of protected health information to AI services can trigger breach notifications, regulatory scrutiny, and legal liability. Moreover, reliance on AI-generated outputs introduces new questions about accuracy, oversight, and accountability.
Armor Introduces a Five-Pillar AI Governance Framework
To help enterprises close the AI governance gap, Armor has outlined a structured framework built around five core pillars. First, organizations must establish a comprehensive AI tool inventory, identifying both approved and shadow tools and classifying them by risk. Second, enterprises need clearly defined data handling policies that specify what categories of information can be used with each AI service.
Third, Armor recommends embedding AI oversight into existing GRC programs to ensure audit readiness. Fourth, organizations should deploy monitoring and detection capabilities to identify unauthorized AI usage and potential data exfiltration. Finally, employee training and accountability programs must reinforce responsible use, clarify risks, and define consequences.
Through this approach, Armor aims to help enterprises adopt AI confidently while maintaining transparency, regulatory alignment, and a defensible security posture.
Cyber Technology Insights: ArmorCode Unveils AI Code Insights: Transforming Code Security with Deep Context
To participate in our interviews, please write to our CyberTech Media Room at info@intentamplify.com
