AI is evolving so quickly it can be hard to keep all the different types straight. That’s especially true when it comes to conversational AI and conversation AI. Not only do both use AI to enable natural-sounding conversations, but their names are so similar they’re often (mistakenly) used interchangeably, adding to the confusion.
But there are important differences when it comes to conversational AI vs. conversation AI, and understanding those distinctions is key to ensuring you’re getting the most out of each.
Conversational AI helps in the moment
Conversational AI is the set of technologies that enable machines to simulate conversations. At its core, it delivers real-time voice or text assistance to people.
Conversational AI powers tools that help customers (or associates) in the moment, by quickly delivering the answers or information they need. These include chatbots, speech-based assistants, voice bots, and other self-service options.
Not all conversational AI tools are the same. AI-powered chatbots, for instance, are automated software that simulate a chat conversation with a user in natural language. They’re very useful for automating simple tasks and enabling 24/7 access for customers, but limited because they’re primarily text-based and scripted to answer only specific questions.
Intelligent virtual assistants (IVAs), on the other hand, use conversational AI to learn from each interaction and get smarter over time. They’re chat assistants that can generate more personalized responses by combining analytics and cognitive computing. They consider – in real time – individual customer information, past conversations, and location, and are more advanced than simple chatbots.
Conversation AI improves the future
Unlike conversational AI that’s used to facilitate seamless interactions in the moment, conversation AI (also known as conversation intelligence) analyzes large volumes of data from conversations to cull insights and trends over time and improve future decision making and interactions.
Your contact center collects huge amounts of data; conversation AI harnesses its potential by making sense of it all. Technologies like speech and predictive analytics let you listen in on every interaction happening in the contact center.
In addition to helping identify what works and what doesn’t during interactions, these tools quickly comb through large quantities of data and identify trends, patterns, and anomalies. You’ll get to know your customers much better, enabling you to serve them faster.
Armed with those insights, you can eliminate guesswork and make data-backed decisions that improve customer experience (CX), employee experience (EX), and your bottom line going forward. Speech analytics, for instance, helped a global social media company grow customer conversions by 233% and call volume analysis helped a national energy company reduce call volume by 60%.
Simply put, conversation AI speeds up your ability to put insights to work.
Both are keys to CX success
While there are definite differences when it comes to conversational AI vs. conversation AI, both can play important roles in a successful CX operation.
Embrace conversational AI where automating simple tasks makes sense. Customers will appreciate the ability to resolve basic inquiries in their own time and in their preferred channels. And using chatbots and other tools frees your associates up to focus on tasks where they can add more value – improving CX, EX, customer satisfaction, and loyalty.
Use conversation AI tools on a deeper level, to get the most from your data. Your contact center is a treasure trove of insights, but you’ll never uncover them without the right tools. Conversation AI can help you to get know your customers (and your contact center) better and make more-informed decisions that drive the results you need.
But don’t implement either type of AI merely for technology’s sake. Neither will deliver the ROI or results you want if they aren’t part of a thoughtful AI strategy. A “set it and forget it” approach doesn’t work for AI.
Brands need to continually check on how tools are performing and making adjustments as needed. If you lack that know-how in house, working with a CX partner that specializes in conversational and conversation AI is a great way to tap into proven best practices and expertise.
