Agent assist is software that supports human contact center agents while they handle customer conversations. It listens to or reads the conversation as it happens and offers help on the agent’s screen: suggested answers, relevant knowledge articles, next steps, compliance reminders and, after the conversation, an automatic summary. The agent stays in control and decides what to use. Vendors also market it as an AI copilot for agents.
At a glance
- Agent assist helps the agent, not the customer; customers usually don’t interact with it directly.
- Common features include live transcription, suggested responses, knowledge lookup, checklists and after-call summaries.
- Most current products use AI, often including generative AI, to interpret the conversation and draft content.
- Value depends on the quality of your knowledge content and integrations, not only on the AI.
- It is typically sold as an add-on to a contact center platform, and features vary widely by provider.
What problem it solves
Contact center agents juggle a lot at once: listening to the customer, searching for answers across several systems, following required scripts and disclosures, and writing notes afterward. New agents may take a long time to become confident, and experienced agents still give inconsistent answers when policies change often. Every minute spent searching or typing notes adds to wait times and cost.
Agent assist takes some of that load. By surfacing the right article or answer at the moment it’s needed, it can shorten searches and help newer agents handle conversations they would otherwise escalate. Prompts can remind agents of required disclosures. Automatic summaries can reduce after-call work, which feeds directly into average handle time (AHT).
How it works
Listening. For calls, the platform transcribes the conversation in near real time, using the same kind of technology as speech analytics. For chats and messages, it reads the text directly.
Understanding. Conversational AI identifies what the customer is asking for, key details such as an order number, and sometimes the customer’s tone. Many newer products use generative AI to interpret the conversation and draft responses.
Suggesting. The agent’s screen shows suggested replies, relevant knowledge articles, the next step in a process or a reminder to read a disclosure. The agent can accept, edit or ignore each suggestion. Some products can also fill in fields in the CRM or start a workflow with the agent’s approval.
Wrapping up. After the conversation, the software drafts a summary and suggested disposition codes for the agent to review, instead of the agent typing notes from scratch.
Learning. Teams review which suggestions were used and which were ignored, update knowledge content, and tune prompts. Supervisors may also see real-time alerts when a conversation goes off track.
Agent assist is usually delivered as part of, or an add-on to, a contact center as a service (CCaaS) platform, though standalone products that work alongside existing platforms also exist.
When it matters for buyers
- When onboarding is slow or turnover is high and new agents need support to reach proficiency.
- When after-call work is a large part of handle time.
- When products, policies or regulations change often and agents struggle to keep up.
- When evaluating AI add-ons from your contact center provider, since claims about time savings vary and are best tested in a pilot.
- When conversations contain sensitive data, which raises questions about where transcription and AI processing happen and whether data is retained.
See our artificial intelligence page for a broader view of AI in business systems.
Questions to ask vendors
- Which features are generally available today, and which are on the roadmap?
- What knowledge sources and systems can the product draw from, and how is that content kept current?
- How is it priced: per agent, per conversation or by AI usage, and what is included in our current tier?
- How do you measure its effect on handle time and resolution, and can we run a pilot on our own contact types?
- Where is conversation data processed and stored, and is it used to train models outside our account?
- How do agents flag a wrong suggestion, and how does that feedback get used?
- Does it work with our existing contact center platform and CRM, or only yours?
How it differs from an intelligent virtual agent (IVA)
An intelligent virtual agent (IVA) talks to customers on its own, handling a conversation without a person or until it hands off. Agent assist sits beside a human agent and helps them. Both often use the same underlying AI, and some providers sell them together, but they solve different problems: an IVA reduces the number of conversations that reach agents, while agent assist makes the conversations that do reach agents faster and more consistent. A customer-facing chatbot falls on the IVA side of that line.