What is AI agent assist?
AI agent assist is AI that helps the agent rather than replacing them. While a person handles the conversation, the AI works alongside: listening or reading, pulling up information, filling in fields and drafting the write-up. The customer talks to a human throughout.
It sits at the opposite end of the automation spectrum from an AI voice assistant or chatbot, which talk to customers directly. Many contact centres use both: self-service AI for routine contacts, and agent assist for the conversations that reach a person.
What agent assist does
Agent assist covers three stages of an interaction.
When a contact arrives
- Reads and structures emails and messages, extracting details such as names, addresses and reference numbers into the right fields.
- Routes by content, using intent recognition to send each item to the right queue, regardless of which address or number it came in on.
- Prioritises urgent work so it reaches the front of the queue.
During the conversation
- Surfaces knowledge. Following a live transcript from speech recognition, it suggests the relevant knowledge base article or process step as the topic comes up.
- Prompts next steps and compliance reminders, complementing guided call scripting.
- Improves written replies, checking spelling, grammar, clarity and tone before an email or chat message is sent.
After the contact
- Summarises the interaction (see AI call summarisation).
- Classifies the reason for contact and the outcome.
- Assesses the interaction, for example whether it was resolved first time.
Why it matters
A surprising share of an agent’s time goes on work around the conversation rather than the conversation itself: reading, searching, retyping details and writing notes. That time shows up in average handle time and after-call work, and it is often the least satisfying part of the job.
Agent assist targets exactly that work. The benefits usually include:
- Less manual capture, so fewer typing errors and more consistent records.
- Faster access to the right answer, which helps new agents in particular.
- Consistent classification and summaries, which makes reporting more reliable.
- More attention on the customer, because the agent isn’t splitting focus between listening and typing.
Because a person remains in the conversation, agent assist is also well suited to complex, sensitive or regulated contacts, where handing the conversation to an AI wouldn’t be appropriate.
Good practice
- Start with the biggest admin burden. Look at where agents lose the most time and target that first.
- Keep agents in control. Suggestions and drafts should be easy to edit or reject.
- Check accuracy. Review a sample of captured details and summaries regularly, especially early on.
- Involve agents in the design. They know which prompts help and which get in the way.
- Measure quality as well as speed, including first contact resolution and customer feedback.