Shadow AI
AI use can spread faster than enterprise visibility and review.
Managed AI Security
Your AI environment. Governed, secured, and managed.
Artificial intelligence is entering the enterprise faster than most organizations can govern it. MAISSP helps identify AI use, understand the risks, establish controls, and manage governance and security over time.
Governance boundaryUse · Data · Access · Vendors
ENTERPRISE
AI
AI
An emerging category
From managed IT, to managed security, to managed AI risk.
As AI becomes part of ordinary enterprise operations, organizations need a durable management layer across governance, security, data, vendors, people, and change.
01
MSP
Manage enterprise technology and operations.
02
MSSP
Manage the security of enterprise technology.
03 · Emerging
MAISSP
Manage security and governance across the enterprise AI environment.
The exposure
AI risk enters through many doors.
The challenge is not one model or one application. It is the distributed environment around adoption.
Sensitive data
Prompts, files, and outputs may expose regulated or proprietary information.
Vendor risk
Models, platforms, and embedded AI create changing third-party dependencies.
Agentic access
Agents can act across systems with identities, tools, and delegated authority.
Policy gaps
Traditional technology policies rarely address how generative AI is selected, used, and reviewed.
Ownership gaps
Security, legal, data, procurement, and business teams share an unclear boundary.
Rapid change
Capabilities, usage patterns, and guidance evolve faster than annual controls.
Management pillars
One management layer for enterprise AI risk.
Inventory
Know what AI exists across employees, systems, vendors, workflows, and business teams.
Risk
Understand how each use case can affect data, operations, customers, and the business.
Governance
Define policies, ownership, approvals, decision rights, and accountability.
Security
Assess data, access, model, application, vendor, and agent-specific exposure.
Vendors
Assess AI-enabled suppliers, upstream model dependencies, integrations, and change.
Oversight
Maintain governance as deployments, risks, and organizational needs change.
Services
Assess. Govern. Secure. Monitor. Respond.
Professional and managed services designed to strengthen internal ownership—not replace it with software.
Assess
Establish the current state, identify material gaps, and prioritize a practical roadmap.
ExploreGovern
Define accountable operating models, policies, intake, review, and exception processes.
ExploreSecure
Evaluate AI applications, data flows, vendors, access paths, and agent capabilities.
ExploreMonitor
Operate recurring reviews, inventory updates, risk tracking, and control follow-through.
ExploreRespond
Prepare ownership, escalation, evidence, and response playbooks for AI-related events.
ExploreStart here
Build a clear picture of your AI risk environment.
The MAISSP AI Governance & Security Assessment establishes an initial inventory of AI use, identifies governance and security gaps, evaluates material risks, and provides leadership with a prioritized roadmap.
Request an assessmentCore deliverables
- AI Inventory
- AI Risk Register
- Governance Gap Analysis
- AI Vendor Review
- Employee AI Policy Review
- Security Recommendations
- Prioritized Remediation Roadmap
- Executive Report
Lifecycle methodology
Governance that follows the life of AI.
A repeatable lifecycle turns one-time review into an adaptive management process.
1Discover
2Classify
3Assess
4Control
5Monitor
6Improve
Our approach is informed by NIST AI RMF, the NIST Generative AI Profile, OWASP guidance for generative AI and LLM applications, and ISO/IEC 42001 principles. References indicate alignment of thinking, not certification, endorsement, or affiliation.
Built for cross-functional ownership
A shared risk needs a shared operating model.
Executive Leadership
Gain a clear view of ownership, priorities, dependencies, and decisions.
IT & Security
Connect AI exposure to architecture, access, data, and the existing control environment.
Risk & Compliance
Apply consistent classification, review, documentation, and treatment decisions.
Legal & Governance
Clarify policy, accountability, vendor considerations, and defensible oversight.
Operations
Put practical guardrails around the AI-enabled workflows that run the business.
AI & Data Teams
Enable useful adoption with architecture-aware, proportionate governance.
Start with clarity
Build a governed path for enterprise AI.
Start with a clear view of current use, ownership, exposure, and priorities.