In the world of AI-driven customer service and experience, autonomy is both the promise and the problem.<\/p>\n
The advancement of agentic AI has helped bring contact centers into a new era of automation. But when machines start improvising, who\u2019s keeping them in check?<\/p>\n
At Scorebuddy, that question has a clear answer.<\/p>\n
The company\u2019s GenAI Auto Scoring solution is designed not only to enhance quality assurance (QA) for human agents but also to keep a watchful eye on the growing number of autonomous AI tools operating on the front lines of CX.<\/p>\n
These checks are essential in making sure that your AI is working for you rather than against you, as Emmanuel Doubinsky<\/strong>, Scorebuddy\u2019s CEO<\/strong>, explains:<\/p>\n Agentic AI needs to be monitored. Because it will start making decisions that you don\u2019t necessarily want to happen.<\/p><\/blockquote>\n Before deciding on a strategy to effectively oversee your agentic AI offerings, it is essential to understand precisely what the technology is.<\/p>\n With its rise in popularity over the past 12 months, the actual definition of agentic can sometimes get lost amongst the excitement.<\/p>\n Doubinsky explains how \u201cmany people mistake agentic AI with AI agents.<\/p>\n AI agents automate front-end support; agentic AI is about letting AI decide the workflow itself. It doesn\u2019t just follow rules, it figures out what the rules should be.<\/p><\/blockquote>\n Agentic AI turns deterministic workflows into non-deterministic ones.<\/p>\n In practice, that means customer journeys are no longer tightly scripted; instead, the AI adapts in real time, bringing in documents, surfacing context, and choosing next steps.<\/p>\n It\u2019s a leap forward in automation. But it\u2019s also a compliance and accountability headache.<\/p>\n The benefits of agentic AI have been preached far and wide, with efficiency being one of the most apparent.<\/p>\n However, Doubinsky argues that \u201cwhen you deploy agentic AI in the contact center, it\u2019s not just about saving time; it\u2019s about making sure your AI behaves like a good agent.\u201d<\/p>\n While that may seem relatively straightforward, it is often a lot harder than it sounds.<\/p>\n Agentic AI can be \u201cvery creative in addressing unexpected problems,\u201d but that same creativity can introduce hallucinations, bias, and behavior that falls short of regulatory or brand standards.<\/p>\n In other words, just because the AI can respond doesn\u2019t mean it should.<\/p>\n To manage that risk, Scorebuddy\u2019s QA tools are evolving … fast.<\/p>\n Scorebuddy\u2019s GenAI Auto Scoring fights fire with fire by leveraging elements of agentic AI itself, but with tight controls.<\/p>\n \u201cWe are starting to use it, but with a lot of precautionary measures,\u201d says Doubinsky.<\/p>\n We don\u2019t promote it as a front-end tool. It\u2019s a backend service, and we\u2019re cautious with how it behaves.<\/p><\/blockquote>\n That caution is critical, especially as Scorebuddy looks to automate QA processes without sacrificing accuracy.<\/p>\n By blending agentic AI with human oversight, the platform enables organizations to:<\/p>\n This, in turn, frees up human evaluators to focus where their expertise is most valuable: edge cases, coaching, and complex problem-solving.<\/p>\n For Doubinsky, \u201cIt\u2019s not about replacing the human.<\/p>\n \u201cIt\u2019s about asking them to do what they\u2019re best at. And that\u2019s understanding context, nuance, and making judgment calls.\u201d<\/p>\n Another major benefit of GenAI Auto Scoring is the impact it\u2019s having on agent morale.<\/p>\n Surprisingly, automation has actually made QA feel fairer to many agents.<\/p>\n Doubinsky explains that previously, only two percent of calls were samples, with agents often feeling that they did not accurately reflect the overall level of customer service being provided.<\/p>\n \u201cNow, with auto-scoring analyzing 20%, 30%, or even 100% of conversations, agents see it as less biased.\u201d<\/p><\/blockquote>\n More comprehensive data also means more targeted coaching.<\/p>\n As AI handles routine queries, agents are dealing with more complex tasks, which necessitates better support.<\/p>\n GenAI Auto Scoring doesn\u2019t just flag issues; it helps managers pinpoint where individual agents need training or recognition.<\/p>\n \u201cIt\u2019s a self-serving circle,\u201d Doubinsky adds.<\/p>\n \u201cAI enables you to better coach humans and make them better at their jobs.\u201d<\/p>\n Hearing about a vendor\u2019s capabilities in theory is one thing, but the proof is always in the pudding.<\/p>\n One of the clearest examples of Scorebuddy\u2019s solutions in action is the company\u2019s work with Intercom \u2013 an AI-first company that, in Doubinsky\u2019s words, doesn\u2019t just talk the talk: \u201cthey promote it, they do it, they live it.\u201d<\/p>\n To become Intercom\u2019s QA partner, Scorebuddy had to prove its AI-first credentials.<\/p>\n Together, the two companies are pushing the boundaries of what responsible AI in QA can look like.<\/p>\n But the partnership isn\u2019t just technical, it\u2019s also cultural.<\/p>\n Intercom\u2019s rollout of AI automation was deliberately collaborative.<\/p>\n \u201cThey didn\u2019t impose it,\u201d says Doubinsky.<\/p>\n They deployed it progressively, with full buy-in from the agent population. We learned a lot from that.<\/p><\/blockquote>\n Agentic AI is already reshaping how contact centers function. However, the shift from rule-following bots to decision-making systems means QA can\u2019t be an afterthought; it must be the foundation.<\/p>\n Scorebuddy\u2019s GenAI Auto Scoring is a step toward that future.<\/p>\n By balancing autonomy with oversight, and automation with transparency, it helps ensure that both humans and machines are delivering the kind of customer experience that builds genuine trust.<\/p>\n As Doubinsky puts it:<\/p>\n \u201cYou never finish proving you\u2019re AI-first. That\u2019s the beauty of it. It\u2019s continuously changing.\u201d<\/p>\n <\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" In the world of AI-driven customer service and experience, autonomy is both the promise and the problem. The advancement of agentic AI has helped bring contact centers into a new era of automation. But when machines start improvising, who\u2019s keeping them in check? At Scorebuddy, that question has a clear answer. The company\u2019s GenAI Auto […]<\/p>\n","protected":false},"author":4983,"featured_media":72747,"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-72746","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-contact-center","tag-agentic-ai","tag-agentic-ai-in-customer-service","tag-ai-agent","tag-ai-agents","tag-automation","tag-autonomous-agents","brands_to_track-scorebuddy","editorial_type-interview","intent-evaluation","target_audience-dual"],"acf":[],"yoast_head":"\nWhat is Agentic AI? And Why Does It Matter?<\/h2>\n
Quality Assurance Needs a Redesign<\/h2>\n
How GenAI Auto Scoring Bridges the Gap<\/h2>\n
\n
Building Trust Through Feedback Loops<\/h2>\n
Walking the Walk<\/h2>\n
Responsible Autonomy Starts with QA<\/h2>\n