Conversational AI represents the most significant advancement yet in how people interact with technology. While punchcards, keyboards, GUIs and even touchscreens are all ways that we communicate with computers on their terms, conversational AI changes all that, as it finally enables an innately human form of interaction between people and machines: natural language.
More sophisticated than hard-coded/text-only chatbots, the AI technologies involved with full-featured conversational solutions include automated speech recognition, natural language processing, machine learning and, increasingly, image recognition, semantic and sentiment analysis, and smart analytics.
A conversational AI solution tends to encompass certain characteristics:
- Applies AI-based language processing, machine learning and smart analytics.
- Reach extends across multiple channels, including voice, video, chat, messaging, social, etc.
- Resolves customer requests autonomously.
- Handles both structured and unstructured data.
- Incorporates “perceptive” capabilities (i.e., sentiment awareness, emotional recognition, conversational context).
- Security and privacy compliant.
Coming into the Mainstream
The impact of conversational AI is just now coming into focus for digital commerce leaders, chief marketing officers and CIOs. Consumers today expect always available access to research, advice, commerce and support from any device, platform or channel they prefer. Conversational AI helps companies meet that expectation — providing interactive, knowledgeable, finely personalized and virtual sales and service across an increasing array of connections. Examples of this are appearing in all manner of products, including cars, speakers, appliances and kiosks, as well as services such as retail, travel, banking and healthcare.
Conversational AI Benefits
With conversational AI, customers can engage with websites, apps, mobile devices, smart speakers and a growing list of other objects in the same way they might interact with a salesperson or customer service agent. It represents a powerful new capability for marketing, customer experience and digital commerce leaders to enhance brand awareness, improve retention and further personalize their services. The benefits of conversational AI include:
- Reduce friction for both commerce and customer care interactions. “One-click” purchasing can be made even more convenient when extended across a multitude of devices and activated using natural language voice commands.
- Create a more personalized user experience with contextual awareness, sentiment analysis and emotion recognition. GPS may inform your app of where you’re standing, but taps and clicks alone cannot convey buying signals, urgency, delight or frustration.
- Produce volumes of rich, highly contextual data that doesn’t exist today. Interactions with customers, prospects and other users across conversational AI channels create a digital flood of information to further enhance machine learning algorithms, feed smart analytics and improve predictive models and business intelligence. For customers, it continuously improves and personalizes interactions with their favorite brands and services.
- Prepare for the future of AI-powered commerce and customer care. While today voice is the new user interface, coming soon are a growing array of personalized and interactive technologies, including powerful image and video recognition, gesture control, biometric authentication and augmented and virtual reality.
Putting Conversational AI to Work
Within our conversational AI practice, we’ve helped clients evaluate, design, deploy and support cognitive solutions built on the most advanced smart technologies available. Examples of projects we’re currently delivering include:
- Restaurant virtualization: A solution automating the entire quick-serve restaurant customer ordering process, with conversational AI technology built on Google’s cloud AI services. Includes integration with digital displays, image recognition and kitchen, POS and customer loyalty systems.
- Intelligent mortgage advisor: A cognitive agent designed on Amazon Alexa, AWS machine learning and a range of APIs. Offers customized research and loan recommendations, initiates the mortgage application process and delivers post-closing updates.
- Voice-enabled Magic Mirrors, providing concierge-like services in retail, hotels and offices: Uses Amazon Alexa voice commands to activate visual content such as facility services or amenities and to display and engage airline, ride-sharing, restaurant and other apps on the Magic Mirror surface.
- Personalized virtual agents for mutual fund and money management firms: Built on Teneo from Artificial Solutions, these virtual advisors automate fund and account FAQs, facilitate transfers, sales, purchases and other transactions, and respond to a variety of customer requests.
- A voice- and image-driven virtual agent for consumer goods manufacturers: Built on Microsoft’s Cortana and LUIS natural language service, the agent provides how-to and care recommendations on household appliances and products.
- A virtual agent that improves automotive sales and service engagements: Allows vehicle shoppers and owners to ask questions about features, capabilities or dashboard notifications, book appointments and schedule other services via Alexa and Facebook Messenger.
What’s Next for Conversational AI
We’ll further explore where conversational AI is headed in the third blog in this series . But at a high level, consider this perspective from a recent Wired article, discussing Amazon’s vision for the future of this technology. “One day, Amazon believes, AIs will do much more than merely control lights and playlists. They will drive cars, diagnose diseases, and permeate every niche of our lives. Voice will be the predominant interface, and conversation itself – helpful, informative, companionable, entertaining – will be the ultimate product.”
What happens between now and this ultimate reality is going to be a thrilling and sometimes elusive test of creativity, skills and foresight for the innovator within each of us. In my next post , I’ll outline the lessons we’ve learned from our pilots and deployments, which can help businesses succeed in their conversational AI endeavors.