There\u2019s\u00a0a version of the AI conversation in the contact center that, to put it bluntly, has been done to death.\u00a0\u00a0<\/p>\n
We\u2019ve\u00a0all heard about\u00a0the productivity\u00a0gains,\u00a0the cost efficiencies, and the agent experience improvements.\u00a0\u00a0<\/p>\n
That\u2019s\u00a0not to say that these\u00a0aren\u2019t\u00a0important and real. But\u00a0there\u2019s\u00a0a harder conversation that tends to get glossed over around what happens to a contact\u00a0center\u2019s oversight infrastructure when a growing share of its workforce isn\u2019t human?\u00a0\u00a0<\/p>\n
Because\u00a0that\u2019s\u00a0the reality\u00a0right now. AI agents are no longer a pilot project or\u00a0a proof\u00a0of concept.\u00a0They\u2019re handling\u00a0real customer interactions at scale every day in some of the largest contact centers in the world.\u00a0\u00a0<\/p>\n
And most organizations are navigating that reality with frameworks, metrics, and oversight structures that were built entirely around human agents.\u00a0\u00a0<\/p>\n
Indeed, one of the more underappreciated side effects of AI taking on customer interactions is what it leaves behind for human agents.\u00a0\u00a0<\/p>\n
The transactions handled by agentic bots tend to be simpler. This point came up in a recent CX Today discussion with\u00a0Dave Rennyson, CEO of\u00a0SuccessKPI, who said:\u00a0\u00a0<\/p>\n
\u201cWhat\u2019s left for the human agents are actually the harder bits of work.\u201d\u00a0<\/p>\n
That might sound like a clean division of labor, but the downstream implications for how contact centers support and evaluate their human workforce are significant.\u00a0\u00a0<\/p>\n
If agents are increasingly handling complex, emotionally charged, or high-stakes conversations, the benchmarks and coaching structures built around a far broader interaction mix may no longer reflect\u00a0what\u2019s\u00a0actually being\u00a0asked of them.\u00a0\u00a0<\/p>\n
Who\u2019s Watching the Machines?\u00a0\u00a0<\/p>\n
In a hybrid contact center environment, the management challenge now incorporates both human and AI agents. And this is where, according to Rennyson, most organizations have a real blind spot.\u00a0\u00a0<\/p>\n
In many deployments, the instinct is to treat AI agents as self-regulating. Systems that either work or\u00a0don\u2019t, and that can be assessed by outcomes alone.\u00a0\u00a0<\/p>\n
Rennyson pushes back hard on that:\u00a0\u00a0<\/p>\n
\u201cIf you\u2019re going to take the leap that conversational AI is able to have a much more durable, thorough, and consistent conversation on par with humans for certain types of tasks, then you need to be managing and quality managing these conversations the same way.\u201d\u00a0\u00a0<\/p>\n
\u201cIt would be the equivalent of letting your builder complete his own home inspections.\u201d\u00a0<\/p>\n
Third-party quality management, whether through manual review or automated tooling,\u00a0has to\u00a0sit on top of any AI deployment. And the feedback loops that improve an AI agent\u2019s performance work very differently from coaching a human.\u00a0\u00a0<\/p>\n
You\u00a0can\u2019t\u00a0sit down with the bot for\u00a0a one-on-one. But consistent, systematic feedback to the people building and\u00a0maintaining\u00a0it will affect every future conversation it has.\u00a0\u00a0<\/p>\n
As Rennyson puts it: \u201cYou had better be right, because whatever you change is going to change all the conversations.\u201d\u00a0\u00a0<\/p>\n
The Measurement Question\u00a0\u00a0<\/p>\n
There\u2019s\u00a0also the question of how you measure customer experience in a contact center where AI is handling\u00a0a significant portion\u00a0of interactions.\u00a0\u00a0<\/p>\n
Traditional survey metrics \u2013 such as CSAT and NPS \u2013 were built for a world where human agents were the primary touchpoint. In a hybrid environment, do they still hold up?\u00a0\u00a0<\/p>\n
Rennyson\u2019s answer is more considered than the current industry discourse around the \u2018death of CSAT\u2019 might suggest.\u00a0\u00a0<\/p>\n
\u201cI\u2019m not a big believer that the CSAT is dead,\u201d he says. The real problem, in his view, has never been the concept of a normalized satisfaction score.\u00a0\u00a0<\/p>\n
It\u2019s\u00a0the sample bias built into the survey model, where organizations end up hearing disproportionately from their most unhappy and most delighted customers.\u00a0At the same time, the vast majority of interactions go unmeasured.\u00a0\u00a0<\/p>\n
What AI changes is the feasibility of solving that. \u201cUsing AI tools, they can be exceptionally good at taking a million phone calls and rating each of them on a scale of zero to ten, both human and agentic, and finding areas of improvement.\u201d\u00a0\u00a0<\/p>\n
It\u2019s\u00a0not a replacement for the metric; instead,\u00a0it\u2019s\u00a0a reinvention of how the metric gets generated.\u00a0<\/p>\n
What Comes Next\u00a0\u00a0<\/p>\n
These are the questions at the heart of our two-part series with\u00a0SuccessKPI.\u00a0\u00a0<\/p>\n
Across both conversations with\u00a0Rennyson, we cover the practical mechanics of managing a hybrid workforce: what quality management looks like when one of your agents is an autonomous system, how to think about workforce balancing when humans and AI are working alongside each other, and what the data governance layer underneath all of it needs to look like.\u00a0\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"There\u2019s\u00a0a version of the AI conversation in the contact center that, to put it bluntly, has been done…\n","protected":false},"author":2,"featured_media":76759,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[9897,179,509,511,405,7537,513,806],"class_list":["post-76758","post","type-post","status-publish","format-standard","has-post-thumbnail","category-agentic-ai","tag-agent-assist","tag-agentic-ai","tag-agentic-ai-in-customer-service","tag-ai-agent","tag-ai-agents","tag-artificial-intelligence-agents","tag-autonomous-agents","tag-call-contact-center-software"],"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/76758","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/comments?post=76758"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/posts\/76758\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media\/76759"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/media?parent=76758"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/categories?post=76758"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ai\/wp-json\/wp\/v2\/tags?post=76758"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}