To seek lower Average Handle Time (AHT) while protecting Customer Satisfaction (CSAT) and Net Promoter Score (NPS), test assistance with knowledge retrieval and documentation while measuring resolution and survey outcomes. This is a proposed evaluation strategy, not an established result of purchasing AI software.
Why does reducing handle time risk hurting satisfaction metrics?
For the proposed pilot, define AHT consistently across talk, hold, and after-call work and preserve the same denominator between groups. Investigate rushed closures, unresolved issues, repeat contacts, and case mix instead of assuming every duration reduction helps or harms satisfaction. Evaluate documentation and retrieval tasks as possible efficiency opportunities; count review and correction time as part of the work.
How should contact centers structure an AI efficiency pilot?
A structured evaluation pairs handle time reductions with observed sentiment and quality indicators across interaction tiers.
- Establish baseline metrics: Measure baseline AHT, hold time, ACW, CSAT, and NPS across distinct contact reason categories prior to introducing automation.
- Isolate administrative tasks: Target real-time knowledge retrieval or after-call note generation rather than automated call termination.
- Segment by case complexity: Track simple transactional contacts separately from multi-step troubleshooting calls to ensure complex issues receive adequate time.
- Audit paired quality metrics: Pair duration reports with measured survey responses, response rates, repeat contacts, resolution, and supervisor reviews; analyze sentiment separately as an inferred signal, not a substitute for CSAT or NPS.
Which software capabilities should operations teams evaluate?
Level AI describes Agent Assist as providing guidance during conversations, access to information, and automatic call summaries. Documentation.
Five9 Agent Assist documents guidance cards and action checklists during conversations. Documentation.
Five9 Agent Assist describes live transcription and customizable call summaries. Documentation.
Qualtrics describes contact center analytics evaluating empathy, script adherence, and sentiment, with quality-improvement workflows. Documentation.
For a live guidance bottleneck, shortlist the assist products for a representative desktop trial. For quality oversight, assess the analytics separately. Neither category establishes a causal improvement in AHT, CSAT, or NPS.
What trade-offs accompany automated guidance and summarization?
In the proposed trial, test whether frequent or irrelevant prompts distract agents. Additionally, test whether agents or supervisors can review and correct summaries before CRM use. Operations teams must balance automation speed against data accuracy and agent focus.
What follow-up questions should buyers ask during software trials?
Before selecting a tool, teams should verify these practical implementation questions:
- How does the system ingest, index, and update internal knowledge bases to prevent outdated guidance?
- Can agents edit and correct automated call summaries before records commit to the ticketing system?
- What latency exists between live customer speech and agent guidance suggestions?
- How does the platform segment handling time reductions between hold time, active talk time, and after-call work?
Limits
This guide reflects documented vendor capabilities accessible as of October 2026 and does not represent an exhaustive market ranking or comparative benchmark test. Documented software features vary across licensing tiers, product editions, languages, and technical deployment models. This analysis establishes no guaranteed reductions in handle time, specific accuracy rates, or certified improvements in CSAT or NPS. Contact center teams must conduct internal pilot evaluations using their own baseline metrics, integration constraints, and quality assurance rubrics before purchasing software.