Executive-grade AI security leadership that identifies exposure, quantifies risk, and drives mitigation—whether you use chatbots, internal copilots, automation agents, analytics models, or "no AI at all."
Remote-first. Vendor-neutral. Built for rapid adoption without disruption.
AI exposure is now an enterprise-wide condition, not a feature-specific decision. Organizations inherit AI risk through employee behavior, vendor platforms, embedded "assistants" inside SaaS products, marketing tools that generate content, CRM automations that draft emails, call-center transcription systems, data enrichment pipelines, and third-party processors that quietly train or route data through models.
Even if your company never shipped a chatbot or built a machine learning team, your organization is still exposed: data is being copied into consumer AI tools, business workflows are being automated by "smart features," and vendors are introducing AI capabilities into products you already rely on. Your liability footprint expands faster than your internal policy and security program can adapt.
ENI6MA's Fractional CAISO (Chief AI Security Officer) service is designed to close that gap with an operating model that produces a clear status report and continuously drives mitigation.
A Fractional CAISO is not a generic compliance consultant and not a traditional vCISO repackaged with new vocabulary. It is a focused executive function responsible for AI security governance across the full lifecycle: data, models, pipelines, human usage patterns, third-party tools, and the operational reality of how "AI" shows up inside an organization.
We bring board-level clarity to AI risk, a practical plan to mitigate it, and a cadence that keeps risk from silently re-accumulating as tools and workflows change.
If you are unsure whether AI even touches your environment, that is the signal to engage. AI risk is most dangerous when it is unmeasured and unmanaged. Schedule an Executive AI Risk Briefing to learn what is already happening inside your organization.
Clear status reports, actionable mitigation plans, and continuous monitoring to keep your organization protected.
Shadow usage, vendor features, and third-party processing create exposure even in organizations that never deployed a chatbot or trained a model.
AI changes weekly. Policies, controls, and monitoring must operate continuously, not as annual reviews.
We deliver a status report executives can act on, then execute a mitigation roadmap with measurable reductions in exposure.
Start with a Status Report. Convert uncertainty into an actionable plan.
Request Status ReportIn 2026, the question is not "Are we using AI?" The question is "Where is AI already operating inside our business processes, and what data and decisions does it touch?" Most companies discover AI exposure through incidents: confidential data pasted into a public assistant, a vendor feature that stores prompts unexpectedly, a contract dispute over generated content ownership, or an automated workflow that behaves unpredictably at scale. What makes AI risk different is that it combines security risk, operational risk, and reputational risk, often triggered by normal employees trying to move faster.
Even organizations with strict cybersecurity programs often lack AI-specific controls: rules for permissible tool use, classification for data that must never enter a model, evaluation gates before a "smart feature" reaches production, and monitoring that detects prompt injection, retrieval leakage, or tool misuse. Traditional security frameworks can be adapted, but they are not automatically sufficient because AI introduces new failure modes: model behavior is probabilistic, data can leak through outputs, and agentic systems can take actions rather than just generate text.
Your exposure is not limited to GPT-like tools. AI includes OCR pipelines, call transcription, document summarization, recommendations, fraud detection, image and video analysis, copilots embedded in productivity suites, and vendor products that quietly run data through models. Add to that the reality that employees use consumer AI tools daily, often with good intent, and you get a risk surface that exists regardless of official policy.
Employees use external tools to summarize docs, draft emails, write code, and analyze data. Without clear controls, confidential information can be disclosed accidentally.
SaaS tools add AI features and change data processing terms. If you don't have a review gate, exposure expands silently.
Hallucinated outputs, biased recommendations, or unsafe automation can trigger customer harm, regulatory attention, or litigation.
Large enterprises typically distribute responsibilities across the Chief AI Officer (AI strategy and adoption), the CTO (technical architecture and delivery), and the CISO (enterprise security controls). This division works until AI becomes operationally embedded everywhere. At that point, critical issues fall between seats: model and data governance without security rigor, security programs without AI-native testing, and product delivery without a unified risk gate. The CAISO exists to own the overlap and make AI security an executive discipline.
The CAIO drives AI adoption, capability, and business transformation. They rarely own security engineering, incident response, or control verification. They need a security partner who can translate strategy into enforceable, measurable protection.
The CTO owns systems and delivery. They can implement controls, but they often lack a dedicated AI risk governance model that spans policies, third-party usage, monitoring, red-teaming, and board-ready reporting.
The CISO owns enterprise security. Many CISOs are now forced to govern AI risk without specialized operating models for model behavior, evaluation, data leakage through outputs, and agentic tooling.
The CAISO coordinates across CAIO/CTO/CISO, creates the AI security governance program, builds operational monitoring capability for AI systems, and produces a continuous risk and mitigation cadence. The CAISO makes AI security measurable, auditable, and actionable.
If you already have a CAIO or CISO, Fractional CAISO is the fastest way to close the gap without reorganizing your leadership team.
Executives don't need more conceptual risk talk. They need a clear status report, a prioritized mitigation plan, and proof that mitigations are working. ENI6MA Fractional CAISO is packaged to deliver tangible artifacts and measurable reductions in exposure while aligning with your existing security program and supporting ENI6MA's broader product posture.
A comprehensive snapshot of where AI touches your organization, including official deployments, shadow usage patterns, and third-party features. We map data categories, decision points, user roles, and operational dependencies.
Deliverable: AI Exposure Map + Executive Summary + Risk Heatmap
A ranked register of AI risks with severity, likelihood, ownership, and mitigation actions. We focus on practical risk reduction, not theoretical completeness.
Deliverable: AI Risk Register + 90-Day Mitigation Roadmap
Policies, standards, and decision rights that match the velocity of AI change. We establish a governance board cadence and clear approval gates for new AI use cases and vendors.
Deliverable: Governance Charter + RACI + Decision Log Templates
For organizations building or integrating AI, we review system design for data leakage, prompt injection, tool security, model supply chain risk, and access boundaries.
Deliverable: Architecture Findings + Control Recommendations + Remediation Backlog
AI security requires operational monitoring and response patterns. We design and run an AISOC-lite function that works alongside your SOC or IT operations to detect, triage, and contain AI incidents.
Deliverable: Monitoring Requirements + Alert Taxonomy + Incident Runbook
Controls must be verified. We build an ongoing cadence for AI security testing, including red/purple style exercises adapted for AI systems and workflows.
Deliverable: Monthly Test Reports + Regression Findings + Remediation Tracking
Employees paste sensitive text into tools to move faster—contracts, customer info, internal roadmaps, code, logs.
Even with good intent, that can violate policies, contracts, and privacy obligations. Mitigation requires policy, controls, training, and tool governance.
A vendor adds an assistant and changes how data is stored, processed, or retained.
Without a review gate, you inherit risk and may breach customer obligations. We implement vendor review gates and contractual language guidance.
AI can reveal sensitive information through outputs even if the inputs seem harmless, especially with retrieval systems and connected tools.
Mitigation requires architecture controls and evaluation, not just "don't do that."
AI is shifting from generating content to acting through tools. That introduces authorization, auditing, and containment requirements.
We implement scoped permissions, action gates, and incident runbooks.
Training data and feedback loops can be manipulated; models can drift in behavior over time.
Mitigation requires provenance controls, evaluation baselines, and continuous regression testing.
When AI touches customer decisions or communications, questions arise: what did it do, why, and what data did it use?
You need logging, governance records, and policy clarity to withstand investigation.
A single high-visibility failure can overwhelm the narrative: unsafe output, biased result, or incorrect automation.
Preparedness is governance + monitoring + tested response, not reactive PR.
Models, plugins, datasets, and dependencies create a supply chain with its own vulnerabilities.
We implement vendor/model due diligence and acceptance criteria.
If any slide feels familiar, you need a status report.
Request the 30-Day AI Exposure Status ReportOur Fractional CAISO engagement is designed for executive clarity and operational progress. We start by establishing facts—where AI is present, what data it touches, and what obligations apply. We then translate risk into a prioritized mitigation plan that fits your organization's maturity and operating tempo. Finally, we run a continuous program that prevents risk from silently returning as teams adopt new tools.
We operate as a leadership layer that aligns stakeholders: the executive sponsor, security leadership, technology leadership, product owners, legal/privacy, and procurement. We do not replace your internal teams; we create a coherent AI security program they can execute and we provide ongoing oversight, testing, and reporting to keep it effective.
Inventory AI touchpoints, data categories, vendors, and workflows. Establish baseline risk posture.
Deliver a ranked risk register, heatmap, and top mitigation actions with clear ownership.
Establish governance cadence, approval gates, standards, and monitoring requirements.
Run governance, AISOC-lite operations, continuous evaluation/red-team activities, and board-ready reporting.
Start with Discovery. You can't mitigate what you haven't measured.
Start DiscoveryThe CAISO framework anticipates a dedicated AI Security Operations Center function working alongside the enterprise SOC. ENI6MA implements an AISOC-lite model that fits remote execution and integrates with existing SOC, IT, or incident response workflows. The goal is operational: detect AI-specific incidents early, triage accurately, contain quickly, and prove that controls work over time.
AI-specific signals: prompt anomalies, retrieval boundary violations, tool invocation patterns, data egress alerts, model behavior drift, vendor feature changes.
We define what you must log and monitor to detect AI incidents and to support investigation.
We create categories that distinguish user misuse, malicious prompt injection, data leakage, tool abuse, and integrity risks.
AI incidents require unique containment steps: disabling tools, changing retrieval scopes, rotating credentials, quarantining datasets, and freezing model changes.
AISOC-lite does not compete with SOC; it augments it with AI-specific expertise and workflows.
We provide plain-language incident summaries and remediation plans suitable for leadership and stakeholders.
If you have additional questions, request a private executive briefing.
Request Executive BriefingAI security improves when testing methods, operational practices, and risk controls are grounded in real-world attacker behavior and shared standards. ENI6MA aligns its Fractional CAISO program with high-quality community and ecosystem efforts, including work associated with SAFE-MCP and the Linux Foundation ecosystem, to support real-time red-team analysis approaches and pragmatic risk mitigation investigations. This helps ensure that our operating model stays current as AI tooling and attack patterns evolve.
Ongoing AI risk cannot be managed purely through policy. We emphasize continuous testing and investigation workflows that reflect real attacker behavior.
Executive programs work when they produce evidence: logs, decisions, risk registers, and mitigation records.
We integrate with your existing SOC and governance processes rather than introducing a parallel bureaucracy.
Sensitive data disclosure through employee usage, vendor processing, retrieval leakage, logging mistakes, and unintended output reveals.
Prompt injection, tool abuse, poisoned data inputs, manipulated evaluation, and drift that undermines reliability and safety.
Over-broad permissions for agents and automations, weak approval gates, lack of action auditing, and insecure tool integrations.
Missing policies, unclear decision rights, inadequate documentation, lack of monitoring, and weak incident readiness—creating regulatory and litigation exposure.
If you want a tailored version of this catalog for your sector and tech stack, request the Executive AI Risk Briefing.
Request Executive AI Risk BriefingChallenge:
Rapid adoption of vendor copilots created unknown data processing paths.
What we did:
Completed exposure mapping, implemented vendor review gates, added policy and telemetry requirements, launched AISOC-lite monitoring for AI events.
Outcome:
Reduced unapproved AI tool usage, improved audit readiness, and established a repeatable approval process.
Challenge:
Employees used consumer tools to summarize sensitive notes; leadership lacked a clear policy and monitoring.
What we did:
Implemented permissible-use policies, tool governance, training, and incident response runbooks tailored to AI usage.
Outcome:
Clear controls, reduced exposure, and improved incident readiness without stopping productivity.
Challenge:
Agents could take actions across systems with unclear permission boundaries and insufficient audit trails.
What we did:
Implemented scoped permissioning, action gates, monitoring, and monthly red/purple testing cadence.
Outcome:
Faster release confidence, fewer security exceptions, and a measurable control regime.
Want a case study relevant to your industry? Ask for a sample engagement plan.
Request Sample Engagement PlanBest for:
Organizations beginning AI adoption or needing immediate executive clarity.
Includes:
Governance setup, status reporting, risk register, and quarterly drills.
Best for:
Organizations running production AI systems or widespread AI-enabled workflows.
Includes:
Monitoring requirements, AISOC-lite operations, monthly security sprint, vendor gates, and monthly executive reporting.
Best for:
Regulated, high-exposure, or agentic automation environments.
Includes:
Continuous testing, deeper architecture reviews, incident advisory coverage, and board-ready reporting cadence.
Engagement sizing depends on number of AI systems, data sensitivity, and vendor footprint. We can scope a monthly retainer that matches your maturity and risk profile.
A clear snapshot of exposure, risk trend, open findings, and mitigation progress.
A monthly decision forum with a documented log and clear ownership.
Continuous refresh as vendors, tools, and workflows change.
A focused monthly sprint to close high-impact gaps.
Evidence that controls work and regressions are detected early.
Runbooks, drills, and updated escalation paths.
If you want predictable, measurable progress without hiring a full-time executive, Fractional CAISO is the model.
Get StartedENI6MA's Fractional CAISO service is designed to support—never contradict—ENI6MA's product posture. Organizations adopt advanced security solutions successfully when they have an executive-level operating model that clarifies risk, aligns stakeholders, and establishes measurable governance and monitoring. Fractional CAISO provides that foundation: a programmatic way to define and verify security outcomes, manage exposure across tools and vendors, and sustain a continuous improvement cadence.
For companies exploring ENI6MA's broader security paradigm, Fractional CAISO creates the organizational readiness layer that accelerates adoption and reduces friction: clearer policies, better telemetry, stronger incident response posture, and an executive narrative that supports investment in durable security controls. Even when an organization is not yet deploying ENI6MA technology, the Fractional CAISO program improves their AI security posture immediately and makes future security modernization decisions more informed and defensible.
AI risk will not wait for your roadmap. Your vendors will add features, your employees will adopt tools, and your workflows will increasingly depend on probabilistic systems. The cost of inaction is not just a breach; it is unmanaged liability, inconsistent decisions, and avoidable incidents. ENI6MA Fractional CAISO gives you a clear status report, a mitigation roadmap, and an operating cadence that keeps risk from returning.
Remote-first delivery. Minimal disruption. Executive-grade artifacts. Continuous mitigation.
If you are preparing for a board meeting, a customer security review, a major AI rollout, or simply want to understand what AI is already doing inside your organization, we can start with a focused briefing and convert it into a practical plan.