Hidden Pitfalls of Contact Center Agent-Assist Tech and How to Avoid Them

The Hidden Downsides of Contact Center Agent-Assist Technology

Contact center agent-assist technology holds significant promise. Over half of customer experience leaders have made it a priority to invest in real-time agent-assist tools, unlocking new ways to improve agent workflows. These tools can auto-draft responses, provide relevant knowledge articles during calls, generate real-time transcriptions and summaries, and even offer coaching suggestions.

Despite these advantages, many deployments fall short of expectations. Some contact centers have found that agent-assist tech can frustrate the very agents it aims to support, sometimes creating more issues than solutions.

The Downsides of Contact Center Agent Assist

Recent research highlights several challenges faced by agents using AI-powered assist technology. A 2025 study from Chinese universities revealed common problems such as transcription freezing after 10 minutes, errors when customers switch languages or accents, and difficulties interpreting phone numbers and addresses.

These issues lead to three main burdens on agents:

• Learning Burden: Agents must figure out workarounds for tech failures, increasing their mental load.
• Compliance Burden: AI-generated suggestions often don't comply with company policies, requiring agents to manually adjust outputs.
• Psychological Burden: Irrelevant or poorly timed recommendations can distract and irritate agents during high-pressure interactions.

While the study had a limited sample size, similar concerns have surfaced elsewhere, pointing to real challenges in adopting agent-assist technology effectively.

Agent Resistance and Practical Challenges

Resistance to new tools is common among contact center agents. A 2023 Gartner report found that 45% of agents avoid adopting new technologies. Poor performance of agent-assist tools is a key reason for this reluctance.

Common issues include:

• Accuracy: Bots delivering incorrect or inconsistent information frustrate both agents and customers.
• Timeliness: Advice that arrives too late during calls is essentially useless.
• Integration Complexity: Incorporating agent-assist tools into existing systems can be difficult and time-consuming, with risks to reputation and finances if done poorly.

A Better Way to Implement Agent-Assist Technology

Validating agent-assist solutions thoroughly is crucial but often tedious and slow. Running through thousands of scenarios manually drains resources and delays improvements.

One effective approach is using automated assurance tools like Cyara Agent Assist Assurance (AAA). This solution works with popular platforms such as Genesys Cloud and Google Customer Engagement Suite to test agent-assist features directly within the agent workspace.

Cyara AAA simulates real conversations, checking if advice is accurate, timely, and contextually relevant. It alerts IT teams immediately when issues arise, helping keep agent and customer experiences smooth.

Balancing Innovation with Reliability

Agent-assist technology can change how agents work for the better, but it demands proper testing to avoid causing more harm than good. Lengthy testing can slow down progress and frustrate agents, which is a risk in an industry moving quickly toward AI adoption.

Tools like Cyara AAA aim to speed up validation without sacrificing quality, ensuring AI remains trustworthy and delivers value in real-time interactions. Maintaining accuracy, timeliness, and relevance is essential to supporting agents and delivering exceptional customer experiences.

For those in customer support looking to improve AI skills and stay ahead in agent-assist technology, exploring targeted AI courses for customer support roles can provide practical knowledge and guidance.