INTEGRATED AI GOVERNANCE

AI Risk Is Already in Your Organization

Most compliance teams can’t fully account for AI usage across their business.

Built into your existing GRC workflows, SAI360 gives you centralized AI governance without adding new tools — so you can see risk sooner and stay ahead of compliance pressure.

AI SYSTEM INVENTORY
AI Inventory
SCANNING
Detected AI Tools
Team Status Risk

The AI Risk You Can’t See Is The One That Exposes You

AI doesn’t wait for your governance program. It’s already embedded in tools, teams, and vendors across your organization.

Shadow AI Is Spreading Fast

Your teams adopted 3 new AI tools last month. Your compliance team found out about zero of them. Every day without visibility is a day of unmanaged risk.

  • 40% of AI tools in enterprises are unapproved (Gartner, 2024)

Your Vendors Quietly Added AI

That CRM you approved 3 years ago? It now has AI features processing customer data. Your original risk assessment is obsolete. Your vendors’ AI is your liability.

Regulators Aren’t Waiting Either

The EU AI Act, NIST AI RMF, ISO 42001 — the regulatory landscape is solidifying. “We’re working on it” won’t satisfy an auditor asking for your AI inventory in 2026.

  • EU AI Act fines: up to €35M or 7% of global revenue

59%

of compliance pros can’t identify all AI in their org

73%

of organizations have no formal AI governance program

17mo

until EU AI Act high risk provisions take effect

AI Governance Shouldn’t Live In A Separate Tool

Most organizations try to solve AI governance by adding more point solutions or tracking risks in spreadsheets. Both fail at scale.

Spreadsheets

  • No real-time visiblity into AI usage

  • Can’t enforce policies automatically

  • Not audit-ready or defensible

  • Siloed from risk and compliance workflows

  • Can’t scale beyond a handful of AI systems

Standalone Tools

  • Purpose-built for AI governance

  • Yet another silo disconnected from GRC

  • Duplicate risk data across systems

  • No built-in compliance training

  • Separate vendor, separate budget, separate rollout

SAI360 AI Governance

  • AI governance inside your existing GRC program

  • Connected to risk, compliance, vendor, and training

  • Audit-ready documentation from day one

  • Built-in responsible AI training for all teams

  • Live in weeks, not months

From AI Inventory To Audit-Ready In Weeks

Get visibility fast, assign ownership, and build a defensible process in weeks, not months.

Discover

Identify every AI system — approved, shadow, and vendor-embedded — across your entire organization in a centralized inventory.

Week 1-2

Assess & Assign

Risk-score each AI system, assign ownership, and map to the regulations that apply. No ambiguity about who owns what.

Week 2-3

Govern in Workflow

Enforce AI policies through the GRC workflows your teams already use — risk management, vendor reviews, incident tracking, compliance.

Week 3-4

Prove & Improve

Maintain audit-ready evidence. Report to the board. Update controls as regulations evolve. Continuous governance, not a one-time project.

Ongoing

Built Around The Frameworks Buyers And Regulators Recognize

Not security standards repurposed as AI frameworks. These are the standards built specifically for governing AI.

Already certified to ISO 27001, SOC 2, or NIST CSF? SAI360 connects your AI governance program directly to your existing security and compliance certifications — no duplicate effort.

AI Governance Across The SAI360 Platform

Govern AI using the same systems you already trust for risk, compliance, and training.

Risk
Management

IT
Risk

Third-Party
Risk

Regulatory
Compliance

 Incident
Management

Compliance
Training

Bring AI Under Governance Before Regulators Ask Questions

Book a 30-minute demo to see exactly what AI governance looks like inside SAI360.

  • Built into existing workflows

  • Connected across risk domains

  • Aligned to regulations like the EU AI Act

  • Fast to implement

  • Live Demo. Real Product. No Slide Deck.

Frequently Asked Questions

AI governance is the framework organizations use to oversee how AI systems are developed, deployed, and used. It ensures AI operates responsibly, complies with regulations, and aligns with company policies. Effective governance helps organizations manage risks like bias, data misuse, and regulatory violations while enabling safe AI innovation.

An AI governance framework defines the policies, processes, and controls organizations use to manage AI responsibly. Frameworks typically address transparency, accountability, risk management, and compliance. Many organizations align their AI governance programs with established standards such as the National Institute of Standards and Technology AI Risk Management Framework, which provides guidance for identifying, assessing, and mitigating AI risks.

AI risk management is the process of identifying and mitigating potential risks associated with AI systems. These risks may include algorithmic bias, privacy concerns, regulatory violations, model inaccuracies, or operational failures. Effective AI risk management combines system inventories, risk assessments, monitoring, and governance workflows to ensure AI is used safely and responsibly.

AI regulations are evolving rapidly across multiple jurisdictions. One of the most significant emerging laws is the European Union Artificial Intelligence Act, which introduces risk-based requirements for AI systems. Other global frameworks and standards are also shaping how organizations manage AI risk, requiring stronger oversight, documentation, and accountability.

Responsible AI refers to designing, deploying, and managing AI systems in ways that are ethical, transparent, and aligned with organizational values. It typically includes principles such as fairness, accountability, privacy protection, and explainability. Governance programs help organizations operationalize responsible AI practices through policies, training, and monitoring.

As AI adoption grows, organizations often struggle to track AI systems, enforce policies, and prove compliance. AI governance software provides centralized oversight by inventorying AI tools, managing risk assessments, documenting decisions, and maintaining audit-ready evidence that demonstrates responsible AI management.

Shadow AI refers to AI tools or systems used by employees without formal approval or oversight from IT, risk, or compliance teams. These tools are often adopted independently to improve productivity, but they may fall outside established governance policies. Without visibility into shadow AI, organizations may face risks related to data exposure, regulatory compliance, and lack of accountability.

SAI360 provides a centralized system of record for AI governance. Organizations can inventory AI systems, assign ownership, evaluate risk, enforce policies, monitor compliance, and maintain audit-ready documentation that demonstrates responsible AI oversight.

An AI system inventory is a centralized catalog of all AI tools used across an organization—including internally developed systems, vendor solutions, and shadow AI tools. It helps organizations understand where AI is being used, who owns it, and what risks or approvals are associated with each system.

Yes. AI governance solutions help identify AI tools being used across departments—even those adopted informally. Detecting shadow AI allows organizations to assess risks, apply governance policies, and bring these systems into formal oversight processes.

AI risk assessments evaluate potential concerns such as model bias, privacy exposure, regulatory compliance, and operational impact. Organizations can assess each AI system, monitor risk levels over time, and document mitigation actions to ensure responsible deployment.

SAI360 aligns with widely recognized frameworks such as the NIST AI Risk Management Framework. Its governance lifecycle includes four stages: governing AI ownership and policies, mapping AI systems and use cases, measuring risks and performance, and managing incidents or remediation.

Training helps employees understand responsible AI use and reinforces governance policies across the enterprise. Role-based training programs ensure teams know how to use AI safely, recognize risks, and follow organizational guidelines.

AI governance typically involves collaboration between risk management, compliance, legal, IT, data science, and business leaders. Assigning ownership for each AI system ensures accountability and clear oversight across the organization.