Contact Center AI: The Story So Far, and What Comes Next?

Take lessons from the contact center AI deployments of yesterday and leverage those to inform your AI strategies of tomorrow

4
Sponsored Post
Contact Center AI: The Story So Far, and What Comes Next?
Contact CenterConversational AIInsights

Published: January 20, 2025

Charlie Mitchell

The contact center AI story so far is a trilogy. Yet, unlike most, these plotlines get better and better.

First came the speech recognition models that enterprise tech firms, like BT, built back in the mid-90s. Yet, implementations proved few and far between, as the cost-benefit ratio didn’t quite stack up.

Next, in the early 10s, came the natural language revolution, as contact center vendors built bulky natural language processing (NLP) engines to spot trends in customer conversations.

Natural language understanding (NLU) also played a key role in early chatbots, uncovering customer intent and presenting scripted responses.

Yet, the third edition of AI in the contact center is where Star Wars’ Return of the Jedi meets Lord of the Rings: Return of the King.

Of course, it’s the generative AI (GenAI) tale. It has proven massive in enabling contact centers to not only extract insight much faster but act autonomously on that insight.

As such, contact center AI is not only cheaper and more accessible than before, it’s much more powerful.

Cue a spike in contact center AI use. Indeed, a recent study found that 42 percent of businesses have fully integrated AI into customer interactions. Meanwhile, a further 29 percent are testing chatbots and AI support.

But, before stepping forward, it’s best practice to look back and consider those lessons learned from the AI implementations of yesterday, which can inform the AI strategies of tomorrow.

What We’ve Learned Along the Way

Still, many associate AI with chatbots, fixating on the opportunity to automate customer communications. However, as the natural language boom taught us, there’s much more to consider.

Two excellent, often-overlooked examples are automating quality assurance (QA) and mining unstructured data to identify more points of frustration within the service experience.

By becoming more familiar with such use cases – and the many others – contact centers can uncover various other impactful applications they might miss by hyper-focusing on automation.

Yet, no matter the use case, contact centers should start small, learn quickly, and scale intelligently. That lesson still rings true.

One helpful best practice is to deploy AI amongst the agent population first. By doing so, CX leaders gain insight into where it works well and fails. That enables optimization before rollout.

While many may completely trust AI and its “guardrails”, it’s best to make mistakes where no one sees them.

But remember, AI is not something a contact center can install and leave. Continue testing, learning, optimizing, and embedding workflow to ensure long-term success.

To ensure this happens, the contact center needs to assign resources. Whether it includes new hires or uplevelling supervisors, the team must continually refine these tools.

Then, there’s the agent piece of the AI pie, especially when applying conversation automation. That’s critical as handling times climb higher and agents get fewer easy calls to take a breath.

In recent years, tools have helped, with virtual assistants providing instant access to pertinent information, offering real-time coaching, and automating tedious tasks like post-contact processing.

However, contact centers should think broader. That may involve revisiting the coaching program, agent metrics, and – dare we say it – salaries…

The Vendors Pushing the Story Forward

The contact center space has become crowded. That competition has helped accelerate AI progress, and now – when one vendor introduces a new AI capability – it’s not long before the others catch up.

So, while some may release more “industry-first” tools, every vendor is – ultimately – pushing the AI story forward.

As such, the playing field has leveled. Take RingCentral as an example. It only launched RingCX in November 2023. Yet, the prominent industry research firm ISG already considers the brand an “exemplary” contact center provider.

Why? Well, according to Keith Dawson, Director of Research for Customer Experience at ISG, what distinguishes vendors like RingCentral is their vision for where the industry and AI are heading.

Commenting on the analyst’s industry research, he told CX Today:

“Whether that’s automation, workflow design, or data-driven CX, those investments shape the leaders in this space.”

Given this, consider RingCentral more closely. The vendor’s RingCX CCaaS solution pairs with RingEX and RingSense AI, its respective UCaaS and conversational AI platforms.

By pulling this all together, RingCentral creates an enterprise communications “super-suite”, with workflows running across the platform for differentiative innovation.

In an environment where the contact center functionality gap is closing, this “beyond AI” approach will set vendors apart rather than baseline AI features, like routing.

The Plot Thickens…

While the distinction between contact center AI features is often lacking, innovation advances, and – in 2025 – vendors will continue releasing new capabilities.

Meanwhile, contact centers will become more adept at pinpointing what’s possible and gauging how they can augment their operations.

There are many great resources online to help here, including a new research report: “RingCentral Trends 2025: The state of AI in business communications,” and an on-demand webinar that dives deeper into 4 different AI trends.

Featuring tech leaders and industry analysts, the webinar aims to provide practical examples of contact center AI applications, actionable strategies, and exclusive insights.

Additionally, it will provide predictions for the next wave of AI developments so operations leaders can ensure their strategies remain relevant and effective.

So, as the story of contact center AI evolves, attendees can stay ahead of the curve.


Discover the Power of AI in Business Communications

Unlock valuable insights from industry experts John Finch and Esther Yoon as they explore the latest trends shaping the future of AI in business communications.

  • Learn how to close the AI optimism gap between leaders and teams
  • Discover strategies to prove AI’s ROI
  • Uncover how to harness data for groundbreaking use cases

Don’t miss this opportunity to stay ahead of the curve and gain practical takeaways for your business.

Watch the video now and transform your AI strategy!

Artificial IntelligenceCCaaSGenerative AI

Brands mentioned in this article.

Featured

Share This Post