VectorCertain released its AI Executive Order Group (AIEOG) Conformance Suite on Monday, mapping the U.S. Treasury Department's Financial Services AI Risk Management Framework against its commercial AI governance platform. The analysis found that 97% of the framework's 230 AI control objectives operate in detect-and-respond mode, with virtually no prevention capability.
The finding carries significant economic implications, according to VectorCertain. For every dollar spent preventing an AI governance failure, organizations spend ten dollars detecting it and a hundred dollars remediating it — a ratio the company calls the 1:10:100 rule. The rule is based on data from IBM's 2025 Cost of a Data Breach Report, which found the average global data breach costs $4.44 million, with U.S. breaches averaging $10.22 million. Detection and escalation alone account for $1.47 million per breach, while the average time to identify and contain a breach is 241 days.
For financial services specifically, the average breach costs $5.56–$6.08 million, and detection averages 168 days. Post-breach costs include notification ($390,000), lost business ($1.38 million), and ongoing compliance monitoring. Nearly 38% of financial services customers would switch institutions after a breach, and stock prices drop an average of 7.5%.
VectorCertain's analysis classified each of the framework's 230 control objectives as either detect-and-respond (97%) or prevention (3%). Detect-and-respond controls use language such as "monitor," "detect," and "respond," assuming an AI action occurs first and governance responds afterward. Prevention controls, which require governance determination before execution, use terms like "prevent," "prohibit," and "require authorization before."
Joseph P. Conroy, Founder and CEO of VectorCertain, said the framework was designed for human-supervised AI, where the human serves as the prevention mechanism. However, autonomous AI agents now outnumber human employees 82:1 in the enterprise, according to Palo Alto Networks, and execute actions in milliseconds without human review. "The economics of the Prevention Gap are not subtle," Conroy said. "Every dollar invested in pre-execution governance saves ten to a hundred dollars in detection, response, and remediation."
IBM's 2025 report found that 97% of organizations that experienced an AI-related security incident lacked proper AI access controls. Organizations using AI-powered security and automation extensively saved $1.9 million per breach, with breach costs averaging $3.05 million compared to $5.52 million for those without such tools — a 45% reduction. VectorCertain's prevention architecture, which evaluates governance in 0.27 milliseconds per transaction, is designed to prevent breaches before they occur.
The company's AIEOG Conformance Suite maps all 230 control objectives and 278 CRI Profile cybersecurity diagnostic statements across eight documents totaling 74,000 words. VectorCertain plans to release additional findings this week, including details on legacy hardware gaps and autonomous agent threats.
VectorCertain, based in Casco, Maine, develops the SecureAgent platform, a governance-first AI safety system with 19+ patent applications. The company's MRM-CFS technology enables AI governance deployment on existing hardware without replacement, and the Agent Governance Ledger provides cryptographically chained accountability for autonomous agent actions. More information is available at vectorcertain.com.
