Agent Assist

What Is Agent Assist?

Agent assist is an AI-powered technology that works alongside human support agents in real time, providing contextual recommendations, suggested responses, and relevant knowledge during live customer interactions. Unlike fully autonomous AI Agents that handle conversations independently, agent assist operates as a behind-the-scenes partner, helping human agents resolve issues faster and more accurately without taking over the conversation. The human agent remains in control while the AI handles the research, retrieval, and drafting that would otherwise slow the interaction down.

How Agent Assist Works

Agent assist systems monitor live conversations in real time, whether through live chat, email, or voice. As the customer describes their issue, the AI uses natural language processing (NLP) to understand the conversation's intent and context. It then searches connected knowledge bases, CRM records, order systems, and product documentation to surface the most relevant information.

The agent sees this information as real-time suggestions in their workspace: recommended replies, relevant knowledge articles, customer account details, and next-best-action guidance. For voice interactions, agent assist can provide live call transcription, sentiment analysis, and compliance prompts. After the interaction, many agent assist tools generate automated summaries and populate ticket fields, reducing the after-call work that drains agent productivity.

Why Agent Assist Matters

Even as AI Agents handle a growing share of routine inquiries, human agents remain essential for complex, sensitive, or high-stakes interactions. The challenge is that these agents spend a significant portion of their time searching for information, toggling between systems, and writing responses from scratch. Industry research shows that real-time agent assist platforms can improve productivity by 40 to 66% and cut average handle time substantially.

Gartner reports that 85% of customer service leaders will explore or pilot customer-facing conversational generative AI in 2025, with agent assist as a primary use case for teams that need to maintain a human touch while improving speed and consistency.

Agent assist matters because it improves every interaction where a human is involved. New agents ramp faster because the AI provides real-time coaching. Experienced agents handle cases more efficiently because the AI eliminates manual research. And customers get better outcomes because responses are grounded in accurate, up-to-date data.

Use Cases and Applications

Agent assist adds value across industries and support scenarios:

• Complex troubleshooting: Surfacing relevant documentation and past ticket resolutions while an agent diagnoses a technical issue
• Regulated industries: Providing compliance-approved response templates and flagging policy-sensitive language during financial services or healthcare interactions
• High-volume contact centers: Generating auto-summaries after each interaction to reduce wrap-up time and improve cost per ticket
• Onboarding new agents: Acting as a real-time training tool by suggesting best-practice responses and guiding agents through unfamiliar workflows
• Multilingual support: Translating and suggesting responses in the customer's preferred language to support global teams

The Maven Advantage

Maven AGI's AI Copilot is the company's dedicated agent assist product, designed to make every human agent faster, more accurate, and more confident. AI Copilot provides real-time suggested responses, full conversation context from prior interactions, and one-click access to relevant knowledge base content. When an autonomous AI Agent escalates a conversation, AI Copilot passes along a complete summary so the human agent never starts from zero.

Mastermind, an EdTech company, achieved 93% live chat resolution with Maven AGI. For the remaining interactions that required human involvement, AI Copilot ensured agents had full context and suggested responses, keeping handle times low and customer satisfaction high.

With 100+ integrations, AI Copilot pulls data from CRMs, ticketing systems, and product platforms to deliver contextual recommendations in a single pane. Explore how agent assist is reshaping service operations in McKinsey's research on generative AI in customer care, or see Gartner's framework for high-ROI customer service AI.

Frequently Asked Questions

What is the difference between agent assist and an AI Agent?

An AI Agent handles customer conversations autonomously from start to finish. Agent assist works alongside a human agent, providing real-time suggestions and information without taking over the interaction. Many platforms, including Maven AGI, use both together: the AI Agent resolves routine inquiries independently, and agent assist supports human agents on complex cases.

Does agent assist replace human agents?

No. Agent assist makes human agents more effective, not redundant. It eliminates time spent searching for information and drafting responses, allowing agents to focus on empathy, judgment, and relationship building. Gartner predicts that 50% of organizations that planned significant customer service headcount reductions due to AI will reverse those plans, confirming the hybrid model of AI plus human agents.

How does agent assist improve first contact resolution?

By surfacing the right information at the right moment, agent assist helps agents resolve issues on the first interaction. Instead of putting customers on hold to research a question or escalating to another team, the agent has immediate access to account data, relevant articles, and suggested responses. This reduces transfers, callbacks, and repeat contacts.

Can agent assist work across multiple channels?

Yes. Modern agent assist platforms support omnichannel workflows, providing real-time assistance whether the agent is handling a chat, email, phone call, or messaging conversation. Maven AGI's AI Copilot works across all supported channels, delivering a consistent experience for agents regardless of how the customer reached out.

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