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Trustible's Guide to AI Monitoring

AI monitoring means far more than model performance dashboards. As AI systems move into production, especially GenAI and agentic AI, organizations need new approaches to track risk, behavior, compliance, and change over time. Our guide breaks it all down.

The term 'AI monitoring' is often misunderstood and inconsistently applied across organizations. Engineers think in terms of latency and drift. Security teams focus on access and misuse. Legal and business leaders worry about regulation, vendor risk, and market signals. In reality, effective AI monitoring spans all of these perspectives.

Once an AI system is live, risk continues to evolve. User behavior changes. Inputs and outputs drift. Vendors update models. Regulations shift. Without structured monitoring, organizations are left blind to emerging failures, compliance gaps, and reputational risk.

AI monitoring enables organizations to move from reactive fire drills to proactive governance: detecting issues earlier, responding with clarity, and continuously improving how AI is deployed and managed in production environments.

Trustible's guide for AI governance practitioners provides a shared framework for understanding AI monitoring across deployment types, monitoring categories, workflows, and real-world use cases, covering traditional ML models, generative AI systems, and AI agents alike.

In this guide, we'll cover:

  • What AI monitoring actually is (and isn't)

  • The largest challenges enterprises face today with operationalizing AI monitoring

  • Real-world monitoring user stories
  • Tactical recommendations that your organization can implement

What challenges have peers faced in 2025?

In the 2025 Trustible AI Governance Maturity Index, leaders from over 180+ enterprise organizations believe in the promise of AI to drive business outcomes, but that promise is far from realized - and the challenges to moving from experimentation to tangible ROI are immense. But, governance is the key.

62
%
Of organizations identify as in the early or developing stages of AI governance maturity
8
%
Believe their AI governance tools, training, and stakeholders are prepared to realize their AI strategy
67
%
Have only a partial or informal understanding of how, why, and where AI is deployed within their organization
53
%
Of organizations have high-level goals for their AI strategy, but feel they aren't specific or actionable
72
%

Feel they lack the expertise and capabilities in-house to evaluate their AI risks, their vendors, and models 

56
%
Cite AI governance as Extremely Important to their AI strategy success
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WHO WE ARE

Trustible is a leading AI governance solution provider enabling safe and compliant AI adoption. Our AI governance platform enables enterprises to identify, measure, and mitigate AI risk to accelerate AI adoption.

WHAT WE DO

Where AI Governance Gets Done

Whether you are building internal AI models, leveraging generative AI or using open-sourced models, Trustible™ enables your organization to manage and mitigate AI risk, build trust, and accelerate responsible AI development.

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