Five Key Metrics to Ensure AI Agents Operate Safely in UAE

Sid Bhatia, area VP and GM META at Dataiku/Image: Supplied

The UAE has emerged as a regional leader in artificial intelligence (AI) adoption, with an Emirates NBD report predicting AI will contribute over $96bn to the UAE's GDP by 2031. A significant portion of this growth is expected to come from AI agents, which operate independently and adapt dynamically, unlike traditional AI systems.

The Challenge of Evaluating AI Agents

AI agents present unique challenges due to their non-deterministic nature, making traditional pass/fail metrics insufficient. Businesses must adopt a comprehensive evaluation framework to ensure reliability, safety, and ROI. Sid Bhatia, Area VP and GM META at Dataiku, outlines five critical metric categories:

1. Task Outcomes

• Measure accuracy, reliability, and compliance of outputs.
• Track task completion rates, error frequency, and retries.
• Incorporate human reviews and industry benchmarks.

2. Business Value

• Assess user satisfaction via Net Promoter Score (NPS) or surveys.
• Compare time savings against baselines.
• Use A/B testing to evaluate agentic vs. traditional workflows.

3. Effectiveness

• Evaluate quality of reasoning and workflow optimization.
• Monitor tool usage and step efficiency.
• Visualize "agent trails" to trace decision-making.

4. Governance

• Ensure compliance, transparency, and auditability.
• Record policy violations, bias, or undesired outputs.
• Implement red-teaming and automated safety tests.

5. Live Performance

• Track latency, uptime, and error rates.
• Monitor costs per interaction and model drift.
• Conduct stress testing during peak usage.

Building Trust in Agentic AI

Bhatia emphasizes that these metrics form a trust-building framework, aligning AI performance with business goals. Collaboration between IT, compliance, and business teams is crucial to identify risks and success criteria.