{"id":72941,"date":"2025-08-13T17:33:40","date_gmt":"2025-08-13T16:33:40","guid":{"rendered":"https:\/\/www.cxtoday.com\/?p=72941"},"modified":"2025-08-13T20:14:27","modified_gmt":"2025-08-13T19:14:27","slug":"the-hidden-downsides-of-contact-center-agent-assist-technology-cyara","status":"publish","type":"post","link":"https:\/\/www.cxtoday.com\/contact-center\/the-hidden-downsides-of-contact-center-agent-assist-technology-cyara\/","title":{"rendered":"The Hidden Downsides of Contact Center Agent-Assist Technology"},"content":{"rendered":"

Over 50 percent of customer experience leaders have prioritized investments in real-time agent-assist technology, according to a 2025 CMP Research study.<\/p>\n

In doing so, they\u2019re unlocking many powerful new use cases to improve agent experiences.<\/p>\n

For instance, some applications can auto-draft responses across digital channels, so agents simply have to review, edit, and send them off to customers.<\/p>\n

Additionally, when an agent is on the phone, the tech might proactively feed them relevant knowledge articles to accelerate a path to resolution.<\/p>\n

Further use cases include real-time transcriptions, auto-summarizations, and automated coaching suggestions. Yet, these are just some of the many possibilities.<\/p>\n

As contact center providers stretch the limits of generative and agentic AI innovation, many more will likely emerge.<\/p>\n

However, while that\u2019s an exciting possibility for many market evangelists, agent-assist deployments still, in many cases, underwhelm.<\/p>\n

Indeed, some contact centers have uncovered the hidden downsides of the tech, derailing their deployments and infuriating agents, the very people the tool should “assist”.<\/p>\n

The Downsides of Contact Center Agent Assist<\/h2>\n

No one doubts the potential of agent-assist software. However, a 2025 paper from a select group of Chinese universities spotlighted how the tech is frustrating customer service reps.<\/p>\n

The study, “Customer Service Representative\u2019s Perception of the AI Assistant in an Organization\u2019s Call Center<\/a>“, found shortcomings in even the simplest use cases.<\/p>\n

Take real-time transcription, for instance. Researchers found that often the tech would freeze after transcribing the first ten minutes of a call. They also found frequent transcription errors when customers would switch between languages, accents, and dialects.<\/p>\n

Moreover, reps reported the AI\u2019s inability to interpret phone numbers and addresses as a common concern, resulting in frequent manual corrections.<\/p>\n

The paper summarized that repeated errors like this have placed three new types of burden<\/a> on contact center agents. These are:<\/p>\n

    \n
  1. A Learning Burden<\/strong> \u2013 When agent-assist tech fails to perform tasks, like accurately transcribing phone numbers and addresses, agents have to learn workarounds, adding to their cognitive load.<\/li>\n
  2. A Compliance Burden<\/strong> \u2013 Often, AI-generated outputs won\u2019t align with internal policies, as most large language models aren\u2019t domain-specific. As such, agents can spend quite some time making sure outputs are compliant.<\/li>\n
  3. A Psychological Burden<\/strong> \u2013 Think of use cases like next-best action. If the suggested action is superfluous, that can irritate agents during busy, high-pressure moments. It can also distract them from listening closely to customers.<\/li>\n<\/ol>\n

    While this is just a single study, with a small sample size, others have hinted at the hidden downsides of agent-assist technology.<\/p>\n

    More Than Just One Study\u2026<\/h2>\n

    While few other studies have honed in on contact center agent-assist technology specifically, some have highlighted agent resistance to new tools.<\/p>\n

    For instance, in 2023, a paper by the research firm Gartner found that 45 percent of contact center agents avoid adopting new tech<\/a>.<\/p>\n

    Contact centers can allay such issues with a comprehensive agent buy-in strategy. However, the underwhelming performance of agent-assist tooling is a significant factor.<\/p>\n

    Janet Vito, Senior Vice President of Marketing at Cyara<\/strong>, said she\u2019s heard from many customers who previously faced three core challenges when deploying agent-assist technology:<\/p>\n

      \n
    1. Accuracy of responses<\/strong> \u2013 Poorly trained bots can deliver incorrect or inconsistent information, frustrating agents and customers alike.<\/li>\n
    2. Timeliness of information<\/strong> \u2013 Even accurate advice is ineffective if it arrives too late during a live interaction.<\/li>\n
    3. Integration complexity<\/strong> \u2013 Ensuring agent-assist tools function correctly within complex contact center environments is difficult and time-consuming. (But skipping this critical step is risky and can potentially cost more than time and resources; it may also have reputational or financial consequences.)<\/li>\n<\/ol>\n

      Given this wide margin for mishaps, contact centers should consider an alternative approach for implementing contact center agent-assist that safeguards agent and customer experiences.<\/p>\n

      A Better Way to Implement Contact Center Agent-Assist Tech<\/h2>\n

      Validating agent-assist tech is the typical approach contact centers take to overcome the abovementioned challenges. However, that\u2019s easier said than done.<\/p>\n

      After all, to validate thousands of scenarios, which may take between two and five minutes each, quality analysts will spend weeks running through mundane tasks.<\/p>\n

      They\u2019ll also have to establish a testing process for when new scenarios emerge.<\/p>\n

      A much better way is to implement Cyara Agent Assist Assurance (Cyara AAA), a solution that plugs into the platforms enterprises already use, with custom connectors for Genesys Cloud, the Google Customer Engagement Suite, Kore.ai, and many others.<\/p>\n

      Introducing the solution, Vito said:<\/p>\n

      These connectors allow Cyara to test agent-assist capabilities directly within the agent workspace, validating not just if the advice is accurate, but if it\u2019s delivered in time and in context. This ensures a consistent, high-quality experience for agents and customers alike.<\/p><\/blockquote>\n

      In doing so, Cyara simulates authentic, end-to-end conversations between customers and agents, sending out alerts whenever it uncovers an issue for IT to address.<\/p>\n

      A Cautious Approach That Won\u2019t Stall Innovation<\/h2>\n

      Agent-assist technology promises to transform the contact center agent role. However, like any enterprise technology, it needs proper testing.<\/p>\n

      These long testing processes can stall innovation and disengage agents. That\u2019s a problem in a space on the cusp of AI transformation.<\/p>\n

      Cyara AAA promises to accelerate the process and support contact centers throughout their AI initiatives, with the vendor expanding its assurance capabilities to bolster support for future agentic AI-based agent-assist platforms.<\/p>\n

      “Cyara\u2019s focus remains on ensuring that even as AI becomes more capable, it remains trustworthy, accurate, and timely,” summarized Vito. “These are core pillars of exceptional experiences.”<\/p>\n

      To learn more about Cyara AAA, visit: cyara.com<\/a><\/p>\n

       <\/p>\n

       <\/p>\n","protected":false},"excerpt":{"rendered":"

      Over 50 percent of customer experience leaders have prioritized investments in real-time agent-assist technology, according to a 2025 CMP Research study. In doing so, they\u2019re unlocking many powerful new use cases to improve agent experiences. For instance, some applications can auto-draft responses across digital channels, so agents simply have to review, edit, and send them […]<\/p>\n","protected":false},"author":4063,"featured_media":72946,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[11850],"class_list":["post-72941","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-contact-center","tag-agent-assist","tag-agentic-ai","tag-agentic-ai-in-customer-service","tag-ai-agents","tag-autonomous-agents","tag-generative-ai","brands_to_track-cyara","editorial_type-interview","intent-evaluation","target_audience-dual"],"acf":[],"yoast_head":"\nThe Hidden Downsides of Contact Center Agent-Assist Technology - CX Today<\/title>\n<meta name=\"description\" content=\"CX Today covers Contact Center & Omnichannel\u200b news including Agent Assist, Agentic AI, 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