Average Handle Time (AHT)

What Is Average Handle Time (AHT)?

Average handle time (AHT) is the average total time a support agent spends actively working on a single customer interaction. It includes talk time, hold time, and after-call work (ACW), which covers tasks like writing notes, updating records, or sending follow-up communications. AHT is one of the most widely tracked metrics in contact centers and customer service operations worldwide.

When combined with resolution rate and CSAT, AHT gives a complete picture of whether your team is fast, effective, or both.

How to Calculate Average Handle Time

AHT = (Total Talk Time + Total Hold Time + Total After-Call Work) / Number of Interactions Handled

For example, if an agent handles 40 calls in a day with 120 minutes of talk time, 20 minutes of hold time, and 40 minutes of after-call work, their AHT is:

(120 + 20 + 40) / 40 = 4.5 minutes per call

Important measurement considerations:

• Channel-specific AHT: Calculate AHT separately for phone, live chat, and email. Chat agents often handle multiple conversations simultaneously, which changes the calculation.
• Exclude bot and IVR time: Only measure time once a human agent (or AI Agent acting as the primary resolver) is engaged.
• After-call work matters: Teams that skip ACW tracking undercount AHT by 15-25%, creating a false sense of efficiency.

Industry Benchmarks

AHT benchmarks vary significantly by industry, reflecting differences in issue complexity and customer expectations:

• Retail: 3 to 5 minutes. High-volume, straightforward interactions like order status and returns.
• Banking and financial services: 4 to 6 minutes. Regulated processes and identity verification add time.
• Telecommunications: 5 to 7 minutes. Technical troubleshooting and account changes extend conversations.
• Technical support (SaaS): 8 to 10 minutes. Complex troubleshooting, screen sharing, and multi-step resolutions.
• Healthcare: 6 to 8 minutes. Sensitive information handling and compliance requirements.
• Insurance: 5 to 7 minutes. Claims processing and policy questions add complexity.
• Cross-industry average: Approximately 6 minutes is considered a balanced target.

Research Insight: According to McKinsey, leading contact centers are shifting from optimizing AHT alone to balancing speed with resolution quality. AI-enabled support is driving this shift by reducing handle time on routine issues while preserving quality on complex ones.

Why It Matters

AHT directly impacts three critical areas of your support operation:

• Staffing and costs: AHT is a primary input for workforce planning. A 1-minute reduction in AHT across 100,000 annual interactions frees up approximately 1,667 agent hours per year, translating to real labor savings.
• Cost per ticket: Agent time is the largest cost component in most support operations. Lower AHT (without sacrificing quality) directly reduces cost per ticket.
• Customer experience: Customers want fast, complete answers. But AHT must be balanced with resolution quality. Rushing a call to hit an AHT target only to create a follow-up ticket is a false economy that increases time to resolution and hurts satisfaction.

The most common mistake teams make is treating AHT as a standalone target. Lower AHT is only valuable when paired with strong first contact resolution and CSAT.

How AI Improves This Metric

Contact center AI reduces AHT through multiple mechanisms:

• Instant resolution of routine issues: AI Agents handle high-volume, low-complexity inquiries in seconds, removing them from the agent queue entirely and reducing overall AHT.
• Real-time agent assist: AI Copilot tools surface relevant knowledge, draft responses, and pre-populate forms during live conversations, reducing the research and after-call work components of AHT.
• Automated after-call work: AI can generate call summaries, update CRM records, and categorize tickets automatically, cutting ACW by 30-50%.
• Smarter routing: AI routes tickets to agents with the right skills and context, reducing transfers and the time agents spend ramping up on unfamiliar issues.

The Maven AGI Advantage

Maven AGI reduces AHT on two fronts. First, Agent Maven resolves 80-93% of issues without a human agent, eliminating those interactions from your AHT calculation entirely. Second, for the tickets that do reach human agents, Maven's AI Copilot provides full context and suggested responses to speed up resolution.

• K1x (FinTech): 80% of issues resolved by AI, meaning human agents focus exclusively on complex cases where their expertise adds value.
• Check (FinTech): 85% accuracy rate, ensuring AI-resolved interactions do not generate follow-up tickets that increase agent workload.
• Mastermind (EdTech): 93% live chat resolved, deployed in 6 weeks, freeing agents from repetitive inquiries.

Maven AGI Approach: The most effective way to reduce AHT is to resolve most tickets before they reach an agent. Maven AGI's AI Agents handle the volume, and the AI Copilot gives human agents the context they need to resolve remaining issues faster. The result is lower AHT, lower cost per ticket, and higher CSAT.

Frequently Asked Questions

What is a good average handle time?

The cross-industry benchmark is approximately 6 minutes. However, "good" depends on your context. Retail targets 3-5 minutes, while technical support may target 8-10 minutes. The key is ensuring your AHT aligns with strong resolution rates. A 3-minute AHT means nothing if the customer has to call back.

How is AHT different from time to resolution?

AHT measures the active agent time per interaction: talk, hold, and after-call work. Time to resolution measures the full elapsed time from ticket creation to resolution, which may span multiple interactions and include wait time between contacts.

Should I try to minimize AHT?

Not at the expense of quality. Pushing agents to minimize AHT can lead to incomplete resolutions, repeat contacts, and lower Customer Effort Scores. The goal is to reduce unnecessary time (hold, research, admin) while preserving the time needed for thorough resolution.

Can AI reduce after-call work specifically?

Yes. AI excels at post-interaction tasks like summarizing conversations, tagging tickets, updating CRM records, and generating follow-up emails. According to Forrester, after-call work typically represents 15-25% of AHT, and AI-driven automation can reduce ACW by 30-50%, delivering measurable agent productivity gains.

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