Getty Images
How agent assist technology works in the contact center
Contact centers that invest in agent assist technology can help their agents become more productive and eliminate tedious tasks to make their jobs easier.
The integration of artificial intelligence into customer experience platforms is transforming how contact centers operate, sparking a pivotal question for CX leaders: Is AI's role in CX primarily to replace human agents or to empower them? The answer for most companies today is that AI is a complement to the contact center's human workforce.
Metrigy has seen this in recent AI and CX studies. For example, in Metrigy's "Customer Experience Optimization: 2025-26" global research study, 85.6% of 656 participating companies said humans and AI are actively working together to serve customers. Agent assist technology is proving to be a common workhorse of today's contact center -- the second-most-used application for CX.
In fact, over 55% of companies were already using agent assist to support customer interactions when surveyed in the third quarter of 2025 and another 32.3% were actively planning to implement it. In "AI's Role in Customer Experience: 2026-27," a second quarter 2026 study of 759 companies, 56.7% said they've prioritized the use of AI to help human agents serve customers, compared to 43.3% that place their greater focus on AI for customer self-service.
As CX leaders develop their technology roadmaps, understanding the strategic value of agent assist is crucial. For forward-thinking organizations, this technology isn't just an operational tool but a bridge technology that provides immediate measurable success while serving as a proving ground for fully autonomous, agentic AI use cases.
What agent assist means
Agent assist, sometimes referred to as an agent copilot, is an application category that uses a variety of AI technologies -- such as generative AI, natural language processing, machine learning, transcription and sentiment analysis -- to provide contextual, real-time information to human agents.
This technology typically integrates directly into contact center as a service (CCaaS) platforms or rides over the top of existing on-premises contact center infrastructure. The ultimate goal of agent assist is to serve customers more quickly and intelligently by topping off the emotional intelligence of human agents with the machine efficiency of AI.
How agent assist works in real time
In practice, agent assist acts as a human agent's silent partner throughout the lifecycle of a customer interaction. When a call or text initiates, the AI immediately opens the interaction and gathers preliminary information for the human agent.
As the conversation unfolds, the AI listens and analyzes the context in real time. It actively suggests responses, surfaces relevant knowledge base articles and even guides agents to present specific sales offers based on the customer's profile and current need. Once the interaction concludes, the AI wraps up the engagement with the necessary terms and conditions, feedback survey, and a summary of the conversation.
Core features of agent assist software
Agent assist software today brings a robust suite of capabilities to the contact center desktop. Core features include:
- Transcription and summarization. The AI automatically takes notes for the human agent and generates post-call summaries, shrinking time spent on after-call work.
- Response suggestions and knowledge retrieval. The software proactively suggests the next best response or pulls up complex product details and policy information, ensuring a human agent's ability to deliver accurate and consistent answers.
- Workflow and task automation. It automates follow-up tasks and interacts directly with back-office systems to close out an issue without requiring manual data entry from the human agent.
- Real-time coaching. The system provides live feedback to agents on their performance during an interaction, ensuring quality standards are met on the fly.
Business benefits of agent assist
Metrigy's research shows that deploying agent assist drives notable business value, primarily measured across sales, efficiency and quality. The business benefits of agent assist include the following:
- Increased revenue and upselling. Agent assist doesn't just resolve customer problems; it actively helps bring revenue into the company. In the above-noted "CX Optimization" study, 59% of companies cited increased sales as a direct result of agent assist, as the AI dynamically guides agents on cross-selling and upselling during service calls.
- Improved agent quality and efficiency. Two-thirds of companies report improvements in agent quality. Additionally, 76% of companies said AI helps them achieve the goal of keeping service quality high without needing to add more live agents.
- Faster agent onboarding. New hires reach full proficiency faster when the software acts as a real-time, on-the-job coach.
- Improved contact center KPIs. With its auto-summarization and other post-interaction capabilities, agent assist software has proven highly effective at reducing after-call work, a traditional contact center metric. However, it doesn't always decrease another much-used stat: average handle time (AHT) -- but that's OK. Because agents are using the AI-gained time to present sales offers or acquire deeper customer insights, AHT sometimes increases. CX leaders generally view this AHT increase as acceptable as long as customers leave happy and agents successfully drive upsells.
Common use cases and implementation questions
Agent assist thrives in scenarios where human empathy must be paired with complex data retrieval. For example, while AI agents can be highly effective at self-service password resets and simple billing inquiries, human agents -- empowered by agent assist -- remain the preference for handling complaints, issuing refunds and selling new products.
During such interactions, the agent assist software analyzes voice or text dialog to instantly surface relevant information, such as a troubleshooting guide, product specifications or a compliance script. The agent receives the information and recommended response on their screen without entering a single search query.
If done well, the use of agent assist software eliminates dead air on calls and prolonged text responses while reducing the hazards of agents guessing on how best to answer -- and delivering false or misleading responses. It also removes the tedious and time-consuming post-interaction work via auto-summarization.
To ensure effective use of agent assist software, CX leaders should consider several factors before implementation. These factors include the following:
- Complexity of integration. Agent assist software may be available natively from a CCaaS provider or from a partner, or ride on top of on-premises contact center platforms. Regardless, CX leaders should understand how agent assist works with their contact center platform, as well as their CRM application for auto-updates.
- Knowledge readiness. Agent assist software is only going to be as helpful as the knowledge it has at its disposal. CX leaders must ensure knowledge bases are up to date and that the agent assist software can ingest the data from them -- whether that's in the form of an existing article, a PDF or a CRM record, for example.
- Feedback mechanisms. The agent assist software should be able to self-refine its accuracy, learning from agent thumbs-up/down and content click-through rates, for example.
- Understanding AI agent vs. human agent performance. In order to find the right balance between self-service AI agents and human agents guided by AI, CX leaders must be able to measure the performance of both and compare one to the other. When comparing human agents empowered by AI against traditional models, companies predominantly rely on customer satisfaction scores, time to resolve the issue and successful upsell rates.
Looking ahead, AI is projected to resolve approximately 60% of all contact center interactions by 2030, according to Metrigy research. However, for the complex, high-stakes issues that will continue to require a human touch, agent assist ensures contact center staff is fully equipped to succeed.
By investing in this technology now, CX leaders are not just realizing immediate, measurable success -- they are actively building the necessary infrastructure for the AI-first, autonomous CX landscape that's coming.
Beth Schultz is vice president of research and principal analyst at Metrigy. She focuses her research on unified communications, collaboration and digital customer experience.
