AI Training AI: Welcome to the Intelligent Contact Center

The intelligent contact center leverages AI to bolster its data sets. It then utilizes those enhanced data sets to improve AI

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AI Training AI Welcome to the Intelligent Contact Center - CX Today News
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Published: May 16, 2024

Charlie Mitchell

In January, prominent CX futurist Blake Morgan predicted that 25 percent of AI agent-assist deployments will fail in 2024.

One critical reason is that many contact centers cannot unlock the necessary data or discipline to truly benefit from AI. That extends beyond agent-assist and across the whole spectrum of contact center AI.

Zeus Kerravala, Founder and Principal Analyst at ZK Research, previously made this point in conversation with UC Today.

He said: “Some companies want to connect their communication data with their CRM data… but how many companies do you know that love their CRM data?”

The unfortunate answer: not many.

However, in recent years, contact centers have started to utilize AI as an input mechanism to push past this problem.

“It could listen to a call, summarize it, and automatically update a CRM record,” continued Kerravala. “This could be useful in contact centers, sales, or customer success.

“With good AI, you can generate better data, which leads to better AI in the future.”

In stating this, Kerravala lifts the curtain to the intelligent contact center of the future, which leverages AI to bolster its data sets. It then utilizes those enhanced data sets to improve AI. That’s a powerful cycle!

Moreover, that intelligent contact center could go beyond the CRM example Kerravala gave.

After all, across the CCaaS space, there are already examples of that powerful cycle in action.

AI Training AI: 4 Fabulous Examples

No CCaaS provider can currently execute on all of the below. Nevertheless, each example showcases how an intelligent contact center platform could utilize AI to generate data and insights for other AI models to thrive on.  

1. AI Performance Insights Inform Contact Center Routing

For years, CCaaS vendors have developed predictive routing models. These models analyze contact center data to predict which agent is most likely to deliver a particular outcome – such as a high CSAT score – for the specific customer reaching out.

Now, vendors can take this to the next level with AI-augmented QA systems – which surface new agent performance data across all customer conversations.

Indeed, their intelligent contact center platforms could scour that automated QA data to uncover which agents best handle specific queries.

That QA data could then inform a triage system, which routes contacts based on the likelihood that the agent will solve the customer’s query.

2. AI Knowledge Management Enables Next-Level Agent Assist

The latest AI agent-assist models leverage the content within a contact center’s knowledge base to draft customer replies or recommend next best actions.

However, there are often gaps where there is no knowledge article related to the customer’s query. Other times, a relevant article is within the system but outdated. 

As a result, agent-assist models may supply agents with incorrect information. Some may even “hallucinate” and make up information for which the contact center can be found liable.

Thankfully, new natural language processing (NLP) and generative AI (GenAI) models can spotlight knowledge improvement opportunities and even draft new knowledge articles for review and publication.

With such tools, the contact center can reimagine its knowledge management strategy and ensure its virtual assistants leverage the latest and greatest knowledge base insights.

3. AI Troubleshooting Automates Virtual Agent Designs

Some CX providers have developed GenAI-driven solutions that evaluate successful customer conversation transcripts – specific to one query – to define the optimal troubleshooting steps.

A GenAI-powered virtual agent platform may then automatically develop a conversation flow across these steps to automate such queries in the future.

At the very least, an AI assistant could guide the agent through those steps, surfacing relevant data and knowledge at the ideal moments.

4. AI Sentiment Analysis Prompts Automated Outreach

AI models can gauge customer sentiment during an interaction and funnel that data into the contact center’s CRM system. There, the sentiment data may feed various AI models.

For example, HubSpot has a Customer Health model, which mixes it with other insights – such as product usage data – to categorize a customer as “healthy”, “neutral”, or “at-risk”.

CRM users may then devise an automated proactive outreach strategy, which differs depending on the customer’s “health status”.

For instance, they may run an ongoing campaign to automatically send a discount code to “neutral” customers so they can build better connections with them. Alternatively, they could trigger alerts to engage with at-risk customers to recover the relationship.

A final example is to run an upsell campaign that aims to extract greater value from “healthy” customer relationships and drive up profit.

Intelligent Contact Centers Are Cloud-Native, Model Agnostic

As highlighted, an intelligent contact center leverages AI to bolster its data sets. It then utilizes those enhanced data sets to improve AI outcomes.

However, not all contact centers are set up to deliver on that promise.

Point solutions within on-premise environments are an excellent example. Yet, first-generation CCaaS platforms don’t cut the mustard, either.

After all, those first-gen platforms are not cloud-native. Instead, they are monolithic stacks of software in the cloud.

As a result, these platform providers cannot easily bake AI across various layers of the stack.

In the modern CCaaS market, that capability is crucial. After all, the intelligent contact center of the future has AI everywhere, with many use cases hinging on AI-augmented data sets.

As such, forward-looking businesses must work with a cloud-native CCaaS provider that understands and works toward this vision of the intelligent contact center.

Zoom is one such vendor, with Chandler Galt, Senior Product Marketing Manager for the Zoom Contact Center, telling CX Today:

“Intelligent contact centers need a platform born in the cloud without tech debt and a modern, reliable network and architecture.

“Staying ahead of your competitors and evolving with your customers means moving your business at the speed of Zoom.”

To learn more about Zoom and its next-gen CCaaS platform, visit: 

Alternatively, to dive deeper into the intelligent contact center of tomorrow, register for our webinar:  The Future of CCaaS: An Inside Look”?

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Brands mentioned in this article.


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