AI Agent Assist: How AI Helps Call Center Agents
AI agent assist is software that works alongside call center agents during and after customer conversations. It surfaces answers, drafts replies, carries context forward from bots and earlier contacts, and writes up the interaction so the agent can focus on the customer. Unlike AI voice agents or chat bots, which handle conversations on their own, agent assist keeps a person in charge and makes that person faster and more consistent. For small and mid-size teams it is often the lowest-risk place to start with AI, because customers still talk to a human.
Key Industry Statistics
- NBER (Brynjolfsson, Li & Raymond): a generative AI assistant raised issues resolved per hour by 14% on average and by 34% for novice and low-skilled agents, in a study of 5,179 customer support agents. The study also found improved customer sentiment and employee retention. Source
- Verint: after-call work such as summaries, ticket creation, CRM updates and notes takes agents roughly 3 minutes per call on average. Source
- Observe.AI: Accolade cut after-call work by more than 50% with AI summarization. Source
- Verint: AXA Health reduced individual average handle time by 60 seconds across 50,000 calls per week using AI call summaries. Source
What AI Agent Assist Actually Does
“Agent assist” covers a group of capabilities rather than one feature. Most fall into five jobs:
| Job | What the agent gets | Main benefit |
|---|---|---|
| Find the answer | Relevant policy, product or troubleshooting content without searching | Shorter holds, fewer transfers |
| Draft the reply | Suggested wording for chat, SMS or email that the agent edits and sends | Faster, more consistent replies |
| Carry context | What the customer already told a bot, form or earlier agent | No repeated questions |
| Write it up | Call or chat summary, suggested disposition, follow-up tasks | Less after-call work |
| Coach | Patterns from scored conversations, delivered in one-on-ones | Faster ramp for new agents |
Some platforms also offer live prompts during a call, such as compliance reminders or sentiment alerts. These can help, but they are also where agent assist most often goes wrong, as covered below.
Why AI Agent Assist for Call Center Agents Pays Off
The strongest independent evidence comes from the NBER study of 5,179 support agents. Access to an AI assistant raised the number of issues resolved per hour by 14% on average. The gains were uneven in an instructive way. Novice and low-skilled agents improved by 34%, while the most experienced agents saw little change. The authors suggest the tool spreads the habits of top performers to everyone else.
That has three practical consequences for a growing contact center:
- Faster ramp-up. New hires reach a useful level sooner, which matters when attrition is high. Deloitte’s 2026 survey puts average 2025 contact center attrition at 38% (Deloitte).
- More consistent service. When every agent sees the same approved answer, customers get the same answer regardless of who picks up.
- Better use of senior agents. Experienced people spend less time answering colleagues’ questions in team chat and more time on difficult cases.
The Biggest Quick Win: After-Call Work
If you only automate one thing, make it the write-up. After-call work is invisible to customers but expensive. Verint estimates that summaries, ticket creation, CRM updates and notes take roughly 3 minutes per call. Published results from AI summarization are concrete. Accolade reported more than a 50% reduction in after-call work, and AXA Health took 60 seconds off individual handle time across 50,000 calls per week.
Summaries help beyond time saved. Notes become consistent in format, the next agent who picks up the case can read what happened in seconds, and the data in your CRM stays usable. To get there:
- Define a summary template: reason for contact, what was done, outcome, next step and owner.
- Let AI draft the summary, and require the agent to review it before saving, at least for the first month.
- Pair the summary with a suggested disposition so reporting stays clean.
- Spot-check a sample weekly and fix the template where summaries miss important details.
Context Handoff: Where Bots and Agents Meet
Agent assist is closely linked to automation. When an AI voice agent or chat bot cannot finish a request, the human who takes over should see what the customer already said. Nothing frustrates a caller more than repeating their account number and problem after a bot transfer. Gartner found that 87% of customers say access to a human agent is essential when companies use generative AI in customer service (Gartner, 2026). The handoff has to be seamless.
Nectar Desk’s virtual customer assistant is a good example of the pattern. It gathers the caller’s name, issue type and intent before transferring, and when it cannot help, it routes the call to the right queue with a context summary. The same principle applies to messaging. Whether a conversation starts with an AI chat bot on WhatsApp, SMS or live chat or on the phone, the agent should inherit the full thread, not a blank screen.
Common Agent Assist Mistakes to Avoid
- Prompt overload. A constant stream of pop-ups during a live call distracts more than it helps. Show guidance when the agent asks for it, and reserve automatic alerts for things that truly matter, such as a missed compliance step.
- Unreviewed answers. AI suggestions should come from approved content. If the source material is outdated, the assistant will confidently repeat outdated policy. Assign an owner for knowledge content.
- No feedback loop. Agents need an easy way to mark a suggestion as wrong. Their corrections are the best signal for improving content.
- Treating it as surveillance. Position agent assist as a tool for agents, not a monitor of them. Coaching data from AI call scoring should be used to help people improve, and agents should see their own data.
- Measuring only speed. Faster handle time is good only if resolution and satisfaction hold steady or improve. Track them together.
What to Look For in an Agent Assist Tool
Feature lists for agent assist look similar from vendor to vendor. These questions separate useful tools from noisy ones:
- Is it inside the agent’s workspace? If agents have to switch to another tab or app, adoption drops quickly. Help should sit next to the conversation.
- Does it work across channels? The same assistant should support calls, live chat, SMS and social messages, so agents do not learn different tools for each.
- Can you control the sources? You should decide which content the assistant draws on and be able to update it the same day a policy changes.
- Are summaries editable and structured? Free-text summaries are hard to report on. A template with fixed fields keeps data usable.
- Does it connect to QA and coaching? Agent assist and scoring work best together. What the AI learns from scored calls should feed back into the answers agents see.
- Is pricing predictable? Per-agent pricing is easier to budget for a growing team than usage fees that rise with every call.
How to Roll Out AI Agent Assist in 30 Days
| Week | Focus | Output |
|---|---|---|
| 1 | Pick two high-volume contact reasons and gather approved answers, policies and canned responses | Clean source content |
| 2 | Turn on AI summaries and suggested replies for a pilot group of 3 to 5 agents | Baseline vs pilot comparison |
| 3 | Review summaries and suggestions with the pilot group and fix content gaps | Updated templates and answers |
| 4 | Expand to the full team, and add scorecard-based coaching in one-on-ones | Team-wide rollout plan |
Measure before and after on four numbers: average handle time, after-call work time, first contact resolution and CSAT. If handle time drops but resolution falls, slow down and review what the AI is suggesting.
Agent Assist in CallKarma
In CallKarma, Nectar Desk’s AI contact center product, agents work from a toolbar that combines the dialpad, team chat and an AI Assistant panel, so help is one click away in the top bar. The short video guide shows where each one lives. Supervisors get AI call analysis with call detail, team analysis, trends, one-on-ones and detailed scorecards, which closes the loop between what happens on calls and what gets coached. You can browse every setup video in the Call Karma knowledge base. For the bigger picture of where agent assist fits next to voice agents, chat bots and analytics, read our guide to the benefits of AI in contact centers.
Frequently Asked Questions: AI Agent Assist
What is the difference between agent assist and an AI agent?
An AI agent, such as a voice agent or chat bot, handles a conversation on its own. Agent assist supports a human agent who stays in control of the conversation. Most contact centers use both: AI agents for routine requests, and agent assist for the conversations people handle.
Does AI agent assist reduce average handle time?
It usually does, mainly by cutting search time and after-call work. Published examples include Accolade’s more than 50% reduction in after-call work and AXA Health’s 60-second reduction in handle time. Results depend on your call mix and how good your source content is.
Is agent assist only for voice calls?
No. Suggested replies and summaries are often even more useful in live chat, SMS and social messaging, where agents juggle several conversations at once.
Will experienced agents benefit?
Less than new agents, according to the NBER study. Experienced agents still save time on write-ups, and their best answers become the material that helps everyone else.
What do I need before starting?
Approved answers for your top contact reasons, a summary template and a clear disposition list. Clean source content matters more than any specific AI feature.