Dependable AI Solutions: Assess What's Important
Gather
Nov 27, 2025
The value of enterprise AI isn't about how much content it uncovers; it's whether its answers can be trusted. If the responses are unclear or incorrect, adoption slows down. This practical framework of five metrics helps you measure what matters so your AI becomes a reliable decision-making partner.
Why trust matters now
AI now provides answers, not just links, making correctness and usefulness crucial.
Leaders need proof that AI accelerates confident decision-making.
A clear, repeatable framework builds trust and guides improvements.
The five metrics to measure
Accuracy – Is the answer factually correct and based on authentic sources?
Score guide: 1 = incorrect/fabricated; 3 = mostly correct; 5 = fully correct with verifiable sources.
Starter KPI: ≥90% of sampled answers rated ≥4.
Relevance – Does it directly address the user's query and context (role, permissions, project)?
Score guide: 1 = irrelevant; 3 = somewhat relevant; 5 = precisely relevant with contextual awareness.
Starter KPI: ≥85% rated ≥4.
Coherence – Is it logically organized and easy to comprehend?
Score guide: 1 = confusing; 3 = understandable; 5 = clear and easy to scan.
Starter KPI: ≥80% rated ≥4.
Helpfulness – Did it facilitate the task or decision swiftly (steps, links, next actions)?
Score guide: 1 = not helpful; 3 = somewhat helpful; 5 = clear steps with actionable directives.
Starter KPI: ≥20% reduction in time-to-decision on benchmark tasks.
User Trust – Do employees rely on the AI as a trustworthy source over time?
Score guide: 1 = avoid usage; 3 = cautious usage; 5 = a trusted default assistant.
Starter KPI: Trust NPS ≥30; increasing repeat usage.
Trustworthy AI answers are responses you can depend on for work decisions. Evaluate them using five metrics—accuracy, relevance, coherence, helpfulness, and user trust—and track scores over time. This reveals whether your platform accelerates confident decisions, identifies areas where quality diminishes, and suggests improvements.
Run a lightweight evaluation in 14 days
Create a gold set of 50–100 real tasks across teams.
Define 1–5 scoring rubrics with examples rated 1/3/5 for each metric.
Form a mixed panel (domain experts + everyday users).
Test persona-realistic scenarios with permissions applied.
Gather scores + telemetry (citations, time-to-answer, action clicks).
Analyze by metric and function to identify weaknesses.
Refine and retest the same gold set to confirm improvements.
What good looks like (starting benchmarks)
Accuracy: ≥90% rated ≥4; <1% fabrication rate
Relevance: ≥85% rated ≥4 with correct context
Coherence: ≥80% rated ≥4; <10% require follow-up
Helpfulness: ≥20% faster time-to-decision
User Trust: Trust NPS ≥30; increasing repeat usage
From scores to action: improve fast
Optimize performance: expand/clean sources; enhance connectors; improve retrieval processes.
Boost trust: require citations; display sources; monitor fabrication rates.
Minimize friction: standardize answer templates; provide next-best actions; customize prompts by persona.
Institutionalize learning: conduct weekly quality reviews, utilize a simple dashboard, and set quarterly targets.
Governance & Risk
Integrate these metrics into your AI governance framework for auditable results: policy, monitoring, incident response, and regular reassessment after model or content changes.
FAQs
What's the best way to measure AI answer quality?
Implement a five-metric framework—accuracy, relevance, coherence, helpfulness, and user trust—and evaluate a weekly sample 1–5 for each metric.
How many samples do we need?
Begin with 50–100 tasks across teams; increase sample size for higher-risk functions.
How do we prevent fabrications?
Anchor answers in enterprise sources, mandate citations, tighten retrieval/prompt constraints, and review flagged cases weekly.
Do automated checks replace human review?
No. Combine task-oriented human scoring with automated signals (citations present, latency, guardrails) for a comprehensive view.
Next steps
Request a Glean Performance Review. We will assess your current AI answer quality against these five metrics and provide a targeted optimization plan.
