Net AHT: Rethinking Contact Center Metrics for AI-Hybrid Operations
As contact centers increasingly integrate AI agents alongside human representatives, traditional metrics are becoming obsolete. One critical metric that needs urgent reconsideration is Average Handle Time (AHT), currently measured as (Talk Time + Hold Time + After-Call Work) divided by total calls.
This conventional formula worked well in purely human-operated environments, but it’s now creating blind spots in AI-hybrid operations. When AI agents handle a significant portion of calls and automate most after-call work, the traditional AHT calculation no longer provides meaningful insights into operational efficiency or cost savings.
The Problem with Traditional AHT
The fundamental issue is that traditional AHT treats all calls equally, regardless of whether they’re handled by humans or AI. This approach:
- Undervalues AI efficiency: AI-handled calls often require different time investments and resources
- Masks true cost savings: The dramatic reduction in after-call work through AI automation isn’t properly captured
- Provides misleading benchmarks: Comparing AHT across different AI adoption levels becomes meaningless
Introducing Net AHT (nAHT): A Hybrid Approach
To address these challenges, I propose a new metric: Net AHT (nAHT) or Hybrid AHT (hAHT). This weighted average approach accounts for the reality of mixed human-AI operations:
Formula:
This formula captures the weighted average time per call across both channels, reflecting savings from AI routing and AI-assisted human interactions.
Calculating True Cost Efficiency
Beyond time savings, we need to understand the financial impact. The effective cost per call in a hybrid environment becomes:
Formula:
Real-World Example
Consider a contact center handling 100,000 monthly calls with 40% AI automation:
Assumptions:
- Human calls: 60,000
- AI calls: 40,000
- Talk time: 4 minutes
- Hold time: 0.5 minutes
- After-call work: 1.5 minutes (pre-AI) → 0.5 minutes (post-AI)
- AI processing time: 1.2 minutes
- Human agent cost: $0.50/minute
- AI agent cost: $0.05/minute
Results:
- Traditional AHT (human calls only): 6.0 minutes
- Net AHT (hybrid): 3.48 minutes
- Cost per call: $1.52 (down from $3.00 for human-only)
This represents a 49% reduction in cost per call and a 42% improvement in time efficiency.
Why This Matters
The shift to nAHT isn’t just about better measurement—it’s about strategic decision-making. This metric helps contact centers:
- Accurately assess ROI from AI investments
- Optimize resource allocation between human and AI channels
- Set realistic performance targets for mixed operations
- Benchmark against industry standards more effectively
Implementation Considerations
While these calculations demonstrate potential savings, real-world implementation requires careful consideration of:
- Call complexity distribution: Not all calls are suitable for AI handling
- Customer satisfaction impact: Faster doesn’t always mean better
- Training and transition costs: Moving to hybrid operations requires investment
- Quality assurance: Maintaining service standards across channels
The Future of Contact Center Metrics
As AI adoption accelerates, traditional metrics will continue to lose relevance. The industry needs new frameworks that accurately capture the value of human-AI collaboration. Net AHT is just the beginning—we’ll likely see similar evolution in metrics like First Call Resolution, Customer Satisfaction scores, and agent utilization rates.
The contact centers that adapt their measurement frameworks today will be better positioned to optimize their AI investments and demonstrate clear value to stakeholders tomorrow.
This analysis represents a framework for thinking about hybrid contact center metrics. Actual savings will vary based on call types, AI sophistication, and implementation quality. I’ll be exploring additional AI-driven savings metrics in future posts.
This was written by me and posted on my blog earlier.