AI in customer service has matured. The conversation has shifted from full automation to intelligent assistance.
Agent-assist AI is part of this evolution. It does not replace human agents. It helps them perform better, faster, and more consistently.
This model is now defining the future of support operations. Companies using agent-assist tools report measurable gains in handle time, accuracy, and customer satisfaction. The technology is changing what it means to deliver service, and what it means to be a support agent.
Agent-assist AI refers to tools that provide real-time support to human agents during live customer interactions. These systems listen, analyse, and suggest relevant information in context.
They surface knowledge, detect sentiment, and recommend next-best actions, all while the conversation is taking place.
This is very different from chatbots or self-service automation. Chatbots work independently of people. Agent-assist tools sit beside them, guiding rather than replacing.
According to McKinsey, companies that use hybrid models combining human expertise with AI assistance resolve issues 30 to 50 percent faster and deliver more consistent experiences.
Agent-assist AI is, in practice, a co-pilot. It keeps the human at the centre while automating the background complexity.
A modern support agent juggles multiple systems and channels. Calls, chats, messages, and emails often overlap. The goal of agent-assist AI is to simplify that environment.
Key functions include:
Platforms such as Yellow.ai and boost.ai have made these capabilities widely accessible. Yellow.ai reports that its Agent Assist product reduces repetitive tasks by up to 80 percent, while boost.ai clients report lower handle times and higher accuracy through intent detection and live prompts.
A 2024 Oliver Wyman report found that organisations using agent-assist AI reduced handle times by 70 percent and improved first-time resolution rates by 50 percent. The gains are linked to better knowledge retrieval and fewer manual steps during calls.
Support work is repetitive and cognitively demanding. Agent-assist AI removes a significant amount of mental effort. It provides answers in context, reduces the need for multitasking, and helps agents focus on tone and empathy.
A ResearchGate study found that employees working alongside AI systems showed greater confidence in decision-making and faster skill development compared to those in non-augmented environments.
By surfacing policy-based responses and real-time prompts, assistive systems help agents stay aligned with compliance requirements. This also improves customer experience because communication remains accurate and consistent across channels.
Agent-assist AI can only be as good as the data it draws from. Poorly maintained knowledge bases or fragmented customer records limit its usefulness. Clean data pipelines and clear integration with CRMs are essential.
Agents need to trust the system. That trust is built through training and transparency. They must know what the AI is doing, why it suggests certain actions, and how their feedback influences future recommendations.
Introducing an assist tool is not a plug-and-play exercise. It often requires rethinking how scripts, escalations, and knowledge management work. Without redesign, the system becomes another layer of noise.
Agent-assist AI technology is rapidly evolving, and Condado collaborates with several leading vendors that are shaping this space.
Partners within our network, such as Yellow.ai and Boost.ai, are driving innovation in how AI supports human agents.
Yellow.ai has developed an Agentic AI architecture that blends conversational intelligence with real-time orchestration. The platform uses retrieval-augmented generation (RAG) to deliver accurate prompts, context-aware knowledge retrieval, and sentiment-driven insights during live interactions.
Boost.ai focuses on embedding conversational AI directly within live-agent environments. Its system delivers real-time intent recognition and smart suggestions designed to fit naturally into existing agent workflows, reducing average handle time while improving response quality.
These partners represent the new standard of what effective AI augmentation looks like. Their work aligns closely with Condado’s goal of helping enterprises move from fragmented automation toward integrated human-AI collaboration.
To adopt agent-assist AI effectively, operations leaders must balance technology with people and process.
Agent-assist AI is not another automation trend. It represents a structural change in how human support teams work.
When integrated well, it strengthens both performance and morale. It brings speed without removing empathy.
For contact centres, it is the foundation of a new kind of hybrid service — one where technology does the heavy lifting and people deliver the human connection that customers value most.
