Contact Center AI represents perhaps the most exciting opportunity for virtually any company focused on customer experience today. Companies have been looking for ways to transform their contact center into a more profitable, productive, and valuable resource for years.
Artificial Intelligence has proven to be a powerful component in this quest. With its ability to process vast volumes of data, automate tasks, and even proactively engage customers, AI empowers companies to live up to evolving CX expectations.
By 2027, the market for this technology is expected to reach $4.1 billion, and new opportunities are emerging constantly. In the last couple of years alone, new conversational AI tools, NLP solutions, and even generative AI apps in the contact center have exploded.
Today, we’re going to explain what contact center AI is and how it influences the CX landscape to help you prepare for the next generation of customer care.
What is Contact Center AI?
Most people are already familiar with “artificial intelligence,” the technology that allows computers to process information like the human brain. But how does computerized intelligence influence the contact center environment?
Contact center AI is a collection of tools and intelligent solutions designed to enable smarter, more data-driven, and more efficient customer interactions. It’s a broad concept that’s growing all the time. Initial examples of contact center AI began with innovative routing tools and IVR systems. These were intended to improve and streamline the customer journey.
Analytical tools in the contact center have also frequently leveraged AI to assist companies in processing and using vast amounts of contact data. These resources helped organizations to map and understand the customer journey and collect insights on market trends.
As natural language processing, machine learning, and conversational AI evolved, companies discovered new ways to embed AI into the contact center. We now use AI technologies to deliver self-service through intuitive, creative chatbots and virtual assistants.
Employees leverage generative AI to help them respond faster to customer queries and personalize the service experience. We’re even leveraging intelligent tools to assess customers' sentiments and intent in various communication channels.
AI has emerged as a critical solution to modern contact centers' challenges.
It automates repetitive work, streamlines communication, and helps businesses adapt to unpredictable call volumes. Some contact center platforms, such as Google’s Contact Center AI, are now built entirely on artificial intelligence.
What Can Contact Center AI Do?
Contact center AI's potential use cases and opportunities have evolved drastically in recent years. Once, many business leaders saw AI simply as a solution for task automation. It’s becoming a core component of many strategies to improve employee and customer experience.
As we move into a new era of generative AI in the contact center, driven by rising hype around ChatGPT, the potential of intelligent technologies has become virtually limitless.
Some of the most common use cases for contact center AI today include:
Intelligent Interactive Voice Response (IVR)
In the past, IVR technologies were notoriously frustrating. They restricted customers to a simple menu of options and could not collect valuable information or perform crucial tasks. However, intelligent voice solutions built into IVR technologies are changing this.
Using natural language processing and understanding, companies can improve customer journeys from the first moment of contact. The right IVR solutions can collect customer data, identify intent, and even automate specific service tasks.
Intelligent Conversation Routing
Like IVR solutions, call routing technology hasn’t always been very efficient. Many tools simply passed customers to the first available agent without assessing specific needs or requirements. However, with contact center AI, companies can build more effective routing flows.
Intelligent systems can analyze customer intent and sentiment, gather information from customer profiles, and examine agent skill sets, to find the perfect match. They can also pass valuable information over to an agent automatically, speeding up the time to resolution.
Live Transcription and Translation
If there’s one thing contact center AI excels at, it’s collecting and processing information. Innovative tools with NLP technologies can rapidly accumulate and transcribe spoken words. This term unstructured data into searchable documents for auditing and training purposes. Generative AI tools can even use transcriptions to generate automated summaries after each call.
Some leading tools can rapidly translate speech into different languages in real-time. This helps agents to interact with consumers all over the world. It also reduces the need to outsource customer service to professionals from other countries.
Conversational Analytics
In a world where companies are becoming more attuned to the voice of the customer, AI in the contact center can be extremely valuable for collecting information. NLP tools can analyze conversations on any platform, surfacing information about intent and customer trends.
Conversational Analytics solutions can also offer valuable sentiment analysis insights. This gives agents real-time views into whether a call is going well based on tone and inflection. Some tools can even automatically notify a supervisor or manager when sentiment begins to drop. This allows leaders to jump in and guide a call before a customer churns.
CX Reporting and Business Insights
Contact center AI tools can process vast volumes of data in seconds. This allows contact center leaders to access more valuable insights into crucial metrics. An innovative tool can provide behind-the-scenes views on everything from agent performance to call volumes.
Pioneers like Dialpad are using contact center AI to enhance companies' analysis of crucial metrics like CSAT. These tools use customer sentiment and extensive databases to give users a real-time view of satisfaction scores, without relying entirely on surveys.
Self Service Technology
Chatbots and virtual assistants are typical examples of contact center AI. They empower companies to offer customers new ways of accessing support and guidance without human input. Although human contact center agents are still necessary for some interactions, chatbots are becoming more effective. With generative AI, chatbots can offer a more “human” experience.