Conversational AI has a huge opportunity to impact technology, society and business
How easily we interact with computers strongly informs how likely technology is to disrupt a given aspect of life or business. When we needed to punch code into a command line just to load a program, computers were far less user-friendly. But the mouse and graphical interfaces made things much easier, and computers blossomed from niche products into the mainstream. Touch took things further still, helping create a world where most people carry a computer in their pocket while increasingly also wearing one on their wrist.
What’s the next frontier that will further evolve human-computer relationships? Conversational AI.
You might be thinking that voice interfaces are nothing new—after all, smartphone assistants that you can talk to have been around more than a decade. But you’ve probably noticed those assistants have become better listeners, better conversationalists, and overall much more useful—and that’s because a range of technological breakthroughs have occurred behind the scenes, not only improving smartphone experiences but also inserting AI-powered voice technologies into a range of new devices and use cases.
For example, Google AI researchers opened-sourced BERT, a technique for natural language processing that makes voice models more context-aware and easier and faster to train. DeepMind, one of Google’s Alphabet siblings, also released WaveNet, which has helped create significantly more natural-sounding synthetic voices by replacing models based on phonetics with ones that use waveforms to predict which sounds likely follow one another. Both technologies are now deeply embedded in Google Cloud services such as Text-to-Speech, and they’re just a few among many examples of advances that help computers not only interact with us more naturally, but also act on our requests more effectively.
This means our interactions with computers increasingly resemble our interactions with humans. Conversational AI not only understands and naturally responds to our statements but can also be connected to other AI technologies, such as search or vision, to handle tasks we’d otherwise only delegate to a trusted, qualified person. Soon, most human-computer interactions may not involve completing a series of set actions — clicking or swiping our way along a well-defined user journey — so much as just talking to machines and expecting them to keep up, even as the conversation changes course or topic.
In this article, we’ll look at the business opportunities Conversational AI offers, and how you can make sure your company is prepared for this emerging inflection point.
Related: New Technology: The Projected Total Economic Impact™ Of Google Cloud Contact Center AI
Hearing changes across the Conversational AI landscape
Conversational AI is becoming a force across a range of technology categories and use cases, acting as a concierge who speeds up or automates aspects of our personal and professional lives.
Driving this are two dimensions to the way people—your customers—want to communicate with a business or public service: communication modes, and communication goals.
The concept of communication goals makes clear that speech acts, and thus the ways we verbally ask things of machines, are not all the same:
- Information kiosk-type queries are the simplest interaction: one question (like “what time do you close?”) and one simple answer.
- Information-seeking queries are more complex, relying on a combination of speech understanding and traditional search engines operating over potentially billions of sources of information. A driver might ask their car navigation system, “what’s there to do in Breezewood” or someone cooking might ask their recipe app, “Can I substitute soy for salt?”
- Requests for help are still more complicated—things like asking to change the payment on a flight to frequent flier models or why your bill charged for 20 gigabytes even though you think you used only two. In these instances, several rounds of back-and-forth may be necessary. A short, respectful conversation with a problem-solving AI agent can be less stressful than waiting on hold or repeating information as you’re transferred from a person in one department to a person in another. In my view, whether your business can do this well will be a significant predictor of success over the next decade.
- Full concierge interactions are the most complex, with the AI going deep to solve complicated problems like “why is my bicycle crank clicking?” or “what kind of cat should I get?” In these scenarios, the AI doesn’t start with access to the solution—it uses all kinds of business objects (i.e., over an Enterprise Knowledge Graph) to infer bespoke, even out-of-the-box solutions to queries. We are a long way down this path in many domains, and although I am unsure how fast all the supporting technology will progress, I am confident that excellence in “requests for help” queries is a major stepping stone.
Turning to communication modes, it is important to envision all the interaction models Conversational AI can encompass, and to be prepared to operate across all of them:
- Talking on the phone
- Talking within an app
- Talking with an appliance
- Virtual video conferences
Whether the use case involves interacting exclusively with an AI via an app, handoffs between an AI agent and a human agent over the phone, or transcribing video chats to extract actionable insights, the potential for improved service is significant—a fact we can see in the numerous forecasts for rapid growth in the Conversational AI market.
How your business can join the conversation
To meet customers where they are, your company must be available 24/7 on every channel. You’ll need multiple interactive modalities operating concurrently to tie it all together: e.g., talking to the customer, seeing what the customer is looking at, letting the customer view options and make their selections, all in a seamless conversation.
Building the AI backbone for these kinds of interactions is expensive, difficult, and time-consuming. One way to accelerate your progress is using open-sourced solutions, such as the aforementioned BERT, or vendor building blocks, such as Google Cloud products like Dialogflow, our Speech-to-Text API, or our Natural Language AI API.
Whatever your IT stack looks like, it needs to be both sophisticated enough to meet the anytime-anywhere expectations of today’s customers, and agile enough to adapt to whatever disruptions may occur tomorrow. This means capabilities like:
- Automation & operational efficiency, e.g., AI-powered intelligence for contact deflection, predictive routing, agent productivity, etc.
- Cohesive experiences across multiple smart devices, e.g., channel blending that supports multimodal engagement across apps, digital touchpoints, and modalities (mobile applications, website, phone, SMS over chat, etc.), all with preserved context between touchpoints.
- Data unification, management, and analytics, e.g., unified customer data on a single CRM or system of record.
- Security, scale, reliability and call quality, e.g., services auto-scale as needed, protect personally identifiable information and other sensitive data, and are globally available with acceptably low latency across different devices and regions.
You can also investigate solutions that package these technologies for defined use cases. For example, in the case of reimagining contact center operations with the power of AI, Google Cloud offers Contact Center AI, a solution that provides a unified experience for offering virtual agents, live agent assist, and conversation analytics. At Enterprise Connect, we recently announced the Contact Center as a Service (CCaaS) ability of this platform, Contact Center AI Platform.
Conversational AI is a foundational group of technologies that will continue to change how we interact with computers for years to come—so now is the time to make sure your company can join the chat!
Related: Reaching more customers with Contact Center AI: 2021 Wrap-up