Armor Founder and CEO Chris Drake highlighted the growing challenge facing Chief Information Security Officers (CISOs) at GovWare 2026, emphasizing the need to balance rapid AI adoption with business security and continuity. While delaying AI implementation can weaken an organization’s competitive position, security leaders remain responsible for safeguarding customer confidence, fulfilling contractual obligations, and maintaining reliable operations. As employees increasingly adopt AI tools in their daily workflows, these technologies are often introduced without formal security reviews. During his Tech Talk Spotlights presentation, “Once Again. AI Puts CISOs Between a Rock and a Hard Place,” Drake advocated for an approach that allows AI to perform valuable business tasks autonomously within clearly defined policies. He stressed that CISOs must establish the safeguards governing AI adoption while retaining the authority and supporting evidence needed to ensure compliance and enforce security requirements.
“With the cloud, the CISO at least got a say. With AI, nobody asked. Banning it doesn’t work, and ignoring it is how the breach report gets written.”
-Drake
Drake contrasted AI with the cloud transition, when security could assess a provider and influence which applications and data left the corporate environment. AI can arrive inside existing browsers, productivity tools, and employees’ machines without that checkpoint. Depending on permissions, an agent can read files, send data, and take actions. The risk can travel over an allowed connection even when the firewall works as configured.
After decades spent defending the perimeter, organizations must now examine the AI agents running on employees’ machines. Drake highlighted specific local virtual machine visibility gaps: Anthropic documents that host endpoint detection and response (EDR) cannot inspect activity inside Cowork’s local VM, while Docker documents that processes inside its local sandbox microVMs are invisible to the host. EDR alone cannot provide complete oversight; platform telemetry and network controls remain important. An employee clicking “Allow” does not settle whether the business approved the data access or processing.
Drawing on his conversations across APAC, Drake described the pressure on CISOs who report to the CIO or CTO sponsoring an AI rollout. He urged them to gain trust and lead the decision: agree on the business outcome, define what earns a yes, and demand evidence that the controls and business result work. CISOs also need a written mandate to approve, restrict, or pause AI use; a named executive who owns each risk exception and its expiration date; and an escalation path to the risk committee. These are decisions about the conditions for AI adoption, not approval of every routine AI action.
Suppliers extend that exposure. A vendor’s use of another AI provider to process an organization’s data introduces fourth-party risk. Organizations need evidence of the providers involved, where data is processed, what is retained and which contractual protections apply. Protiviti’s February 2026 AI Pulse Survey found that 47% of large organizations reported incomplete visibility into employees’ use of AI tools. A useful, approved AI path can reduce the incentive to work around security, while discovery and supplier oversight remain essential.
Drake said data classification has moved from nice-to-have to must-have. Organizations must know what their data contains, who owns it and how it may be used. Classification, ownership, permitted use and auditability provide the basis for rules that systems can enforce automatically.
“AI cannot safely use data you cannot govern.”
-Drake
Once that foundation is established, organizations should own the routing policy. Use approved external models when data policy permits and private execution when required. Task complexity, model capability, business needs and cost then guide the choice among permitted options. AI can complete authorized work automatically, with records of the data accessed, policy decisions, models, routes, actions and outcomes. Those receipts let the organization reconstruct what happened without making a person approve every step.
Armor, a provider to regulated industries since 2009, faced the same challenge. Drake said the company was concerned about sending customer data through public AI services where the controls and audit evidence could not meet its customer commitments. It built a governed AI platform for its own operations, now Sovereign AI, and runs its business on it.
Drake closed with the principles behind Sovereign AI: know the data, preserve model choice, own routing policies, control actions and demand full auditability. Give the whole company useful, approved AI so employees have less reason to turn to shadow AI. He called for powerful agents and their credentials to run in governed, isolated, auditable environments, with scoped access, rather than on employees’ laptops.
Sovereign AI is the governed AI work platform for the whole company, built by Armor. One control layer for every model, every team, and every dollar, inside your walls, under your rules. Armor has spent 17 years securing regulated industries, protecting over 1,700 organizations across 40+ countries held to the highest compliance bars in the business. Sovereign AI is what that experience looks like as a product.
Since 2009, more than 1,700 organizations in 40+ countries have relied on Armor to protect regulated data in the public and private cloud. AI is the next risk, so Armor built Sovereign AI to bring that same protection and compliance to how organizations use AI in the workplace: a fully governed platform that lets them leverage AI without creating undue risk to their data and their regulatory obligations.
