7 Best AI Security Software for Compliance and Risk Teams

The best AI security software for compliance and risk management teams produces audit evidence, not just alerts. Look for tools that log every AI interaction with attribution and map controls to frameworks such as the EU AI Act and NIST AI RMF. They should also export records auditors accept. Most programs need two layers: a governance system of record and a data-layer evidence source.

This guide covers seven tools across those two layers. It groups them by the job they do instead of ranking them, because a governance platform and a data-layer tool answer different audit questions.

What Compliance and Risk Teams Need From AI Security Software

Security teams ask whether AI use is under control. Compliance and risk teams ask a harder question: can we prove it? An auditor, regulator or board member wants a record of which AI tools were in use, what data they touched, who or what was acting and what the organization did about it.

Two kinds of software supply that proof. Governance platforms keep the system of record: the AI inventory, risk assessments, policies and framework mappings. Data-layer security software observes AI use and enforces policy, which produces the logs that back those records up. A register without logs is a claim. Logs without a register are raw material. Compliance programs need both, and shadow AI is the reason the observing layer matters: a register cannot list tools nobody registered.

Scope matters here. This guide covers software that governs how people and agents use AI with company data. Tools that use AI to detect threats and tools that harden models against attacks such as prompt injection solve different problems. Our explainer on what AI security software does covers that split. If you want a ranking built around data protection, read the top AI security solutions guide. For a layer-by-layer view of tool types, see the AI security tools buyer's guide.

How We Evaluated These Tools

Forcepoint publishes this guide. We evaluated our own product against the same criteria as every other vendor, and no vendor paid to be included. We drew on public product documentation, vendor announcements and independent coverage. This guide was last reviewed in November 2026.

Each tool was assessed against six questions a compliance team would ask:

• AI inventory. Does it find sanctioned tools, shadow AI and agents, and does it keep the inventory current?
• Attribution. Does it record whether a person, an agent or an agent acting for a person took each action?
• Framework mapping. Does it map controls and evidence to the EU AI Act, NIST AI RMF and ISO 42001?
• Evidence export and retention. Can an auditor get records without manual evidence gathering?
• Enforcement. Does it act on violations or only document them?
• Integration. Does it hand off to GRC and SIEM workflows?

Several products here launched or expanded in 2026. Where a capability comes from a vendor's own announcement, the entry says so. Ask for a live demonstration before you rely on any of them.

AI Security Software for Compliance Teams at a Glance

Seven Tools by Layer, Best Fit and Evidence Produced

Evidence Layer: Software That Records and Controls AI Activity

These tools sit where AI activity happens or where the data lives. They produce the logs, inventories and enforcement records that back up a governance program.

1. Forcepoint AI Security

Forcepoint AI Security reached limited GA on Oct. 13. It covers sanctioned AI, shadow AI and AI agents under one policy framework through three components: AI Detection and Response (AIDR), Shadow AI Discovery and Control and the AI Agent Gateway.

What it records. AIDR connects through APIs to Microsoft Copilot, ChatGPT Enterprise, Claude Enterprise and AWS Bedrock. Security teams see prompts, responses and file uploads and downloads, and they can quarantine or delete a sensitive conversation, so the record shows the response as well as the event. Shadow AI Discovery and Control gives a risk-ranked view of unsanctioned AI apps and websites by tool, user and department. The AI Agent Gateway sits between agents and SaaS MCP servers, inspects each agent-to-tool interaction and logs every action for compliance.

How policy carries over. Existing Forcepoint DLP policies extend to AI with no reconfiguration, so the classifications that govern email and endpoint activity also govern AI interactions.

Best for. Regulated organizations, especially those already running Forcepoint DLP, that need one policy and one record across sanctioned AI, shadow AI and agents.

Limits. Availability is limited to qualified customers and partners, and existing customers complete a one-time onboarding. The agent gateway supports MCP connectors for Salesforce, Atlassian and Microsoft 365 in this release. Forcepoint AI Security supplies evidence and enforcement. It does not replace a risk register or assessment workflow, and model-layer defenses such as prompt injection blocking stay with Forcepoint's partnership with F5.

2. Microsoft Purview

What it records. Microsoft documents that prompts and responses for supported AI apps land in the unified audit log, and that retention policies and eDiscovery apply to those interactions. Compliance Manager adds regulatory templates for AI covering the EU AI Act, ISO/IEC 23894, ISO/IEC 42001 and NIST AI RMF 1.0.

Best for. Organizations standardized on Microsoft 365 and Copilot that want audit and assessment tooling inside the stack they already run.

Limits. Coverage runs deepest inside the Microsoft ecosystem, so confirm how it handles AI tools outside it. The premium AI templates also depend on your Compliance Manager licensing.

3. Varonis Atlas

Varonis announced general availability of Atlas on March 17, 2026. It builds on the Varonis Data Security Platform, so AI findings carry data sensitivity and access context.

What it records. Varonis describes continuous AI discovery that includes shadow AI, AI security posture management, runtime guardrails and compliance reporting. Its activity monitoring captures prompts, responses, agent actions and data access. Varonis says Atlas maps AI systems to frameworks such as the EU AI Act and NIST AI RMF.

Best for. Teams that want AI inventory and posture tied to data access context, particularly organizations already running Varonis.

Limits. Atlas is a 2026 launch, and the capabilities above come from Varonis announcements and affiliated coverage. Ask for a demonstration against your specific frameworks and evidence needs.

4. BigID

BigID launched two agent governance capabilities on Aug. 4: Agentic Access Control and Intent-Based Activity Monitoring. The first scopes what an agent can reach based on data sensitivity and task scope. The second checks agent behavior against declared intent.

What it records. Together they give compliance teams a policy and a monitoring check for agents, grounded in BigID's data discovery and classification. BigID also extended its Data Access Governance to AI agents in March.

Best for. Privacy and compliance programs already using BigID that want agent governance on the same data inventory.

Limits. Both capabilities are recent and vendor-described. Ask for production references and a sample of the evidence the monitoring produces.

System of Record: Platforms That Document and Assess AI Risk

These platforms keep the register, the assessments and the framework mappings. Their center of gravity is documentation, assessment and policy. Several now add runtime features, so check how far each one reaches before you rely on it as proof of what AI did.

5. Credo AI

What it covers. Credo AI's site lists policy packs for the EU AI Act, NIST AI RMF, ISO 42001, SOC 2 and HITRUST, with automated evidence generation and audit-ready documentation. It includes an AI registry for agents, applications, models and vendors, and approval workflows for governance reviews.

Best for. Compliance-led teams that govern many internally built and third-party AI systems.

Limits. Credo AI documents and assesses governance. Confirm what it enforces at runtime and which data-layer tools feed its evidence.

6. IBM watsonx.governance

What it covers. IBM says watsonx.governance uses factsheets to log and monitor model facts automatically. Its compliance accelerators provide a prebuilt library of AI regulations, frameworks and obligations that teams import into the platform.

Best for. Large enterprises in regulated industries that need model risk management and lifecycle documentation.

Limits. The platform centers on the model lifecycle. Confirm how it covers employee use of third-party AI tools and the data flowing into them.

7. OneTrust AI Governance

What it covers. OneTrust tracks models, datasets, agents and vendors in a central inventory with ownership and lifecycle status. It offers EU AI Act, NIST and ISO 42001 templates and workflows for risk tiering by use case, system or component.

Best for. Privacy-led programs already running OneTrust that want AI assessments in the same workflows.

Limits. OneTrust runs on assessments and workflows. Ask how enforcement works in your environment and what data feeds the evidence.

How the Two Layers Work Together

Auditors rarely ask for a tool. They ask for a plan and proof the plan ran. The table shows which layer answers which question and what breaks when one is missing. For a deeper look at the evidence side, see what ISO 42001 auditors check beyond the policy and how to produce audit-ready AI logs.

Which Layer Answers Which Compliance Question

Where to Start

Start with the layer that closes your biggest gap. These starting points reflect common situations, not a fixed rule.

Where to Start by Situation

Questions to Ask Every Vendor

• Can you export a sample evidence record for one AI interaction, showing the actor, tool, data class and policy outcome?
• Which AI tools, connectors and agent paths fall outside coverage today?
• Does each control block before an action completes or remediate after it?
• Which frameworks does the product map to, and which mappings are templates versus custom work?
• How does evidence flow into our GRC and SIEM tools?

AI Security Software for Compliance FAQs

What is AI security software for compliance teams?

It is software that records and controls how people and AI agents use AI with company data, then produces evidence for audits. It differs from AI governance platforms, which document policy, risk and ownership, and from AI-powered threat detection, which uses AI to find attacks.

Do compliance teams need both an AI governance platform and AI security software?

Most do. A governance platform documents policy, risk and ownership. Security software observes use and enforces policy. Auditors ask for the plan and proof it ran, so each layer covers the other's blind spot. Smaller programs can start with one and add the other as scope grows. Our guide to an AI compliance strategy covers how to sequence the work.

Does ISO 42001 certification require specific software?

No. Certification is voluntary, and the standard asks for an AI management system rather than a particular product. It also does not satisfy EU AI Act obligations on its own.

Can AI security software make an organization compliant with the EU AI Act?

No. Software supplies controls, documentation and evidence. Compliance depends on how the organization governs AI, what it documents and how it meets its legal obligations. Vendors describe framework mapping and evidence features, so verify what each one produces against your own requirements and with legal counsel.

Secure AI Use With Forcepoint

Forcepoint AI Security gives compliance and risk teams the evidence side of the stack. AI Detection and Response records sanctioned AI activity, Shadow AI Discovery and Control inventories unsanctioned tools and the AI Agent Gateway logs agent actions, all under one policy framework built on Forcepoint AI Data Security. It is in limited GA for qualified customers and partners.

Explore how Forcepoint supports compliance readiness across AI and data channels.