Agent assist

Agent assist refers to AI-powered tools and features that provide real-time guidance, information, and suggestions to human customer service agents during live conversations. Rather than replacing agents, agent assist systems augment them — surfacing relevant knowledge base articles, suggesting response drafts, flagging compliance risks, and providing context summaries so agents can resolve issues faster and more accurately.

Agent assist sits at the intersection of automation and human support, making it a key component of any hybrid AI-and-human customer service strategy. Where fully autonomous AI handles routine, well-defined queries, agent assist targets the high-complexity, high-stakes interactions where human judgment is essential but human knowledge has limits. Decagon's guide to AI agents covers how agent assist fits within a broader agentic AI deployment model.

How agent assist works

Agent assist systems operate in the background of an agent's interface, listening to or reading the ongoing conversation and surfacing relevant information in real time. Core capabilities typically include:

• Knowledge suggestions: Automatically retrieving relevant articles from a knowledge base based on what the customer is asking, so agents don't need to search manually.
• Response drafting: Generating suggested reply text that the agent can review, edit, and send — drawing on generative AI for customer service to produce contextually accurate drafts.
• Sentiment analysis alerts: Flagging when a customer's tone becomes frustrated or escalatory, prompting the agent to shift strategy.
• Compliance guardrails: Alerting agents when a conversation approaches regulated territory — topics like legal liability, medical advice, or financial commitments — that require specific handling.
• Wrap-up automation: Generating post-conversation summaries, tags, and disposition codes, reducing after-call work (ACW) and freeing agents to move to the next interaction sooner.

Why agent assist matters for support operations

Without agent assist, the quality of customer service depends heavily on the individual knowledge, memory, and experience of each agent. That creates inconsistency — two customers with identical issues may receive dramatically different responses depending on which agent picks up. Agent assist closes that gap by providing every agent with the same instant access to accurate information, regardless of tenure or specialization.

The business impact is measurable. Agents with real-time AI guidance tend to resolve issues faster, reducing average handling time (AHT). They also achieve higher first contact resolution (FCR) rates because they have the right information at the right moment rather than needing to escalate or call back. And onboarding new agents becomes faster when AI assistance compensates for the knowledge gaps that come with limited experience.

Agent assist and quality assurance

Agent assist tools are increasingly integrated with QA in customer service workflows. Because every assisted interaction generates a record of what was suggested versus what was sent, QA teams gain rich data for evaluating agent adherence to best practices, identifying coaching opportunities, and assessing the accuracy of the AI suggestions themselves. This feedback loop is what keeps agent assist systems improving over time. AI observability frameworks make it possible to monitor suggestion quality at scale, flagging cases where the AI guidance may have been incorrect or unhelpful.

Agent assist and customer experience

For customers, agent assist is largely invisible — but its effects are tangible. Interactions feel faster, more knowledgeable, and more consistent. Agents who are well-supported by AI don't fumble for answers or put customers on long holds to look things up. They can focus their attention on the human dimensions of the conversation — empathy, judgment, relationship — while AI handles information retrieval and documentation. That combination is increasingly what separates excellent customer service from merely adequate service. IBM's overview of AI-augmented service highlights agent augmentation as one of the highest-ROI applications of AI in contact center environments.