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The Time is Now for AI in the Contact Center


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We are living through one of the most impactful technological shifts in our lifetimes, as the role of artificial intelligence can’t be understated. From new medical breakthroughs to everyday conveniences, AI will change the world as we know it – including the customer experience and ways that consumers interact with businesses. Most industry watchers agree that the contact center is one of the areas that will be most impacted by the power of AI. 

Most consumers will tell you that the customer service experience needs to be improved. According to a study RingCentral conducted with Opinium Research, over half of the survey respondents would rather be without TV for an hour, while almost half would rather clean the bathroom than contact customer service. Something needs to be done! While AI isn’t a panacea, it can have a great impact on customer service.

According to survey respondents, the top ways AI can enhance the customer service experience include reducing average hold times, enabling a single agent agent to access your full history, expanding availability to 24/7 support, increasing first call resolution rates, and more. To get the most out of AI, it’s important to focus on specific use cases and problem sets, and customer service is one area where AI can provide tremendous value.

Use Cases and Benefits of AI for CX

Despite the recent buzz around generative AI and large language models (LLMs), AI isn’t new and is already being used in contact centers in many ways. Some of the leading use cases for AI to enhance the customer experience are:

  • Chatbots
  • Self-service
  • Call guidance
  • Agent assist
  • After-call work including call summarization
  • Coaching/training
  • Sentiment analysis
  • Quality management

With call guidance and agent assist, the AI provides response recommendations and best practice guidance. Rather than having an agent spend time searching for information, the AI is “listening” in the background and provides the agent with suggested answers, resources, next best actions, and more to help save time and produce better outcomes.

AI-enhanced analytics help businesses extract useful information from each conversation to better understand customer interactions, while sentiment analysis uses natural language understanding to identify the sentiment behind text or voice interactions and guides agents to respond to calls with the appropriate emotional sentiment.

AI-enabled Workforce Engagement Management/Workforce Optimization improves quality monitoring, forecasting, and scheduling. Available for all RingCX customers, RingSense AI Quality Management is an out-of-the-box AI model that automatically scores every call, providing insights to agent performance. Supervisors are no longer limited to reviewing just a tiny subset of calls and can spend time focusing on those that fall below a set threshold, or where certain keywords appear. Automated scoring, transcripts, and summaries of all interactions provide a complete picture of agent performance. For agents, an AI Coach provides actionable feedback and coaching to help improve their skills and performance. 

Going the next step, RingSense AI Quality Management includes Conversation Analytics that help understand customer interactions and provide deeper performance insights such as customer sentiment, causes of customer frustration, and topics that are trending by tracking keywords, competitive mentions, and objections.

Despite the growing surge of AI for CX, organizations need to understand the limitations and realities of current offerings. There are many options out there, but most are complex, expensive, and require massive amounts of professional services. Some of these solutions will be overkill for the average contact center, which require CX solutions that are cost effective, easy to deploy, and provide quick time to value. 

Enter RingCX

RingCentral’s RingCX is a native, AI-powered contact center that takes the fear and complexity out of deploying AI. For organizations requiring key capabilities in a cost-effective, easy-to-deploy solution, RingCX offers full omnichannel capabilities, prebuilt CRM integrations, and AI that is easy to implement and use. This is ideal for businesses that want to take advantage of the recent AI innovations in conversational intelligence, agent assistance, and simple self-serve options, but without the complexity, cost, and overhead of most AI solutions.

Powered by RingSense, RingCentral’s conversation intelligence and AI platform, RingCX helps customers and contact center employees before, during, and after interactions. 

Before the interaction begins, RingSense AI gives agents insights from prior customer conversations, helping to provide a more personalized experience, reduce handle time, and improve agent effectiveness. 

During the interaction, RingCX provides real-time guidance and agent assistance. 

After the interaction, post-call transcriptions along with Real-Time AI Summaries provide automatic summaries of the interaction, highlighting action items to help agents better follow-up on tasks, reducing post-call work by up to 20%. Automated scoring and monitoring give supervisors a better handle on agent and team performance, while identifying where coaching and training may be needed. RingCX Conversation intelligence offers keyword spotting to identify when objections or competitors’ names are mentioned, for example, as well as customer sentiment to help the agent provide an optimized customer experience. AI-based automated quality management, coaching, and conversation analytics help improve agent performance while giving supervisors visibility into every customer interaction. 


RingCX with RingSense uses the power of AI without the high cost or complexity of most contact center AI offerings, making it ideal for organizations that want an out-of-the box AI-enabled, affordable solution that’s easy to deploy.

With RingCX, companies can deploy AI without the heavy lift or expense, while accessing key AI capabilities like real-time summaries, agent assistance, Quality Management, and conversation analytics. 

If you haven’t started thinking about AI for your contact center – the time is now. 

Originally published May 08, 2024, updated May 09, 2024

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