Trust Maturity Model
A five-level maturity model for AI trust and reliability. Assess where you are, define where you need to be, and build a roadmap to get there.
From ad-hoc to optimizing — a clear path forward
Where are you on the trust journey?
Most organizations know they need to improve AI trust and reliability, but they don't know where they stand or what to prioritize. The Trust Maturity Model provides a common language and clear progression.
No common language
Teams talk past each other about AI risk, reliability, and governance. No shared framework for assessment.
Unclear priorities
Everything seems urgent. Without a maturity model, it's hard to know what to tackle first.
No benchmarks
How do you compare to peers? What's the industry standard? Without benchmarks, progress is hard to measure.
"You can't improve what you can't assess. The Trust Maturity Model gives you a clear picture of where you are."
Five levels of AI trust maturity
Each level builds on the previous. Most organizations start at Level 1-2. Regulated industries typically need Level 3-4.
Ad-Hoc
No systematic trust practices. AI reliability is addressed when problems occur. No formal governance or monitoring.
Reactive
Monitoring exists but is implemented after incidents. Some documentation and basic alerting. Response is still reactive.
Proactive
Continuous evaluation and monitoring. Pre-deployment testing. Drift detection. Some automation. Clear ownership.
Managed
Governance framework in place. Automated evaluation pipelines. Policy enforcement. Audit trails. Human-in-the-loop controls.
Optimizing
Self-improving trust systems. ML-driven detection. Continuous optimization. Industry leadership. Innovation in trust practices.
What we assess
The Trust Maturity Model evaluates your organization across six dimensions of AI trust.
Detection & Monitoring
Sandbagging detection, hallucination monitoring, drift detection, behavioral analysis. How well do you see what your AI systems are doing?
Evaluation & Testing
Pre-deployment evaluation, continuous testing, benchmark coverage, test automation. How rigorously do you validate AI behavior?
Control & Steering
Runtime behavior control, steering vectors, guardrails, intervention capability. How well can you control AI behavior in production?
Governance & Policy
Ownership model, policy framework, human-in-the-loop controls, accountability. How mature is your AI governance?
Audit & Compliance
Reasoning capture, audit trails, regulatory alignment, reporting. Can you demonstrate compliance to regulators and auditors?
Team & Culture
Skills, training, awareness, incident response capability. Does your organization have the human capability for AI trust?
What you get
The Trust Maturity Assessment delivers actionable insights, not just a score.
Current state score
Maturity level (1-5) for each dimension. Clear picture of where you stand today.
Gap analysis
Specific gaps between current state and target state. What's missing and what's the risk?
Prioritized roadmap
Sequenced improvement plan based on your goals, constraints, and risk profile.
Industry benchmark
How you compare to peers in your industry. Are you ahead or behind?
Trust Maturity Assessment
Full Assessment
$30K
2 weeks. Comprehensive evaluation across all six dimensions. Stakeholder interviews, system review, gap analysis, prioritized roadmap, executive presentation.
Quick Assessment
$10K
3 days. Rapid evaluation focused on critical gaps. Self-assessment validation, high-level roadmap, key recommendations.
Continuous Assessment
$5K/quarter
Ongoing quarterly assessments to track progress, update benchmarks, and refine roadmap. Includes executive reporting.
Where does your organization stand?
Start with a Trust Maturity Assessment to get a clear picture of your current state and a roadmap forward.