Natural Language and Zero UI Are Redefining Engagement Now
After years of rapid developments in artificial intelligence technology and customer experience, we’re entering an era when companies can finally redesign their digital interactions to be truly intuitive and transparent. Based on a recent report with observational data from design teams around the world, the most innovative brands will use natural language and zero user interface (UI) interactions to deliver touchless, more accessible, seamless omnichannel experiences for their customers.
Brand organizations have been investing for many years in technology to achieve personalization that anticipates customer needs, and now true transformation is finally taking place due to generative AI. This technology is poised to help brands leverage their data for new, better, and radically different ways to engage with customers.
Until now, despite those tech investments, most organizations have been unable to string their vast amounts of data together in the right way to identify next best actions, motivation, or even where a customer is on their journey. As a result, despite sharing data with brands, consumers generally still feel like brands don’t know them. In fact, U.S. customer experience is at its lowest point in the last 10 years. Now, though, Gen AI’s natural language capabilities offer the possibility of new customer relationships that reduce or eliminate the need for people to learn and use a brand-specific interface to find what they need. It also gives consumers new capabilities to streamline their interactions with brands.
Redesigning Customer Relationships to Meet New Expectations
People are increasingly overwhelmed by the number of screens and apps they have to interact with to get things done. Every time we switch among the dozens or hundreds of apps on our devices, we’re changing context, which drains attention and focus. The cumulative impact of all this context-switching adds up to exhaustion and a desire for something different.
Gen AI allows for the development of natural language interactions that can eliminate the need for UI in many use cases. Instead of web- and app-based interactions, consumers can engage in direct, productive voice or text conversation with brand agents. Users get natural language results, while in the background the brand takes action based on the natural language request.
For example, a customer might ask a retail brand agent to recommend a capsule wardrobe for a winter cruise to the Caribbean. The agent, pulling from the customer’s history and preferences, could recommend half a dozen items for the customer to select or reject, and then ship the selected items in time to try them on and exchange them if necessary before the trip. This approach lets the customer avoid searching through the site, browsing the web and social media for capsule wardrobe recommendations, searching the weather forecast for the destination, and other related tasks. The result is less context-switching fatigue, stronger user affinity for brands based on the ease of the conversation and transaction, and greater customer insights based on conversation and purchase histories.
The shift to natural language, agent-mediated customer interactions also has big implications for how consumers learn about brands. Reliance on websites and apps will be replaced by meeting customers where they are, whether that’s social media, online game platforms, or within popular large language model (LLM) results. This last strategy requires moving beyond search engine optimization (SEO) to generative engine optimization (GEO) so their brands appear in AI-generated recommendations and answers to user questions. Brands will also need to develop a unique tone of voice or persona for their customer-facing AI agents to differentiate and build rapport with their customers.
New Models for Brand-Consumer Interactions
By offering intuitive, natural language, zero-UI interactions, brands can avoid being tuned out by consumers seeking to protect their cognition and attention. Instead, these brands may become consumers’ first choice for interactions because they provide an easier, less cluttered, and more natural experience. To save even more time and cognitive load, consumers may subscribe to LLM services that let them have their own personal agents, which can then interact with brand agents.
The idea here is that consumers can give their agent the information it needs to handle appointments, shopping and other tasks with no or minimal involvement by the consumer. For example, you could set up an agent to learn who your family’s dental and medical providers are, your hair and nail salon, your dog’s veterinarian, and your preferred items at the local grocery store, as well as the best times of day and days of the week for appointments, pickups and deliveries. Then as the personal agent takes actions on your behalf, it learns and remembers with each new interaction. Of course, the personal agent will also need to connect with reliable brand agents to complete its tasks.
The result is a network of agents that allows you to use the same window to handle multiple tasks simply by speaking or texting with your personal agent. For example, you could tell your agent that you need to schedule a dental checkup within the next two weeks, and the agent could handle checking your calendar, contacting the dentist’s office agent, and requesting and confirming your appointment. You could also ask the same agent to order milk, greens, school lunch items, and pet food for delivery from the grocery store to your office before you leave for the day. Because the agent would know your favorite brands and quantities, it could arrange everything for you while you focus on work. Then you would simply take the delivery on your way out the door in the evening without having to tap your way through a grocery app.
Consumers have been expecting easier experiences like these for years now, and brands have been trying to crack the code on how to deliver them. Gen AI is likely to make this the year when brands can offer valuable personalized experiences so consumers can shift their attention and mental energy away from apps and re-center their daily lives.
As head of frog North America, Jess Leitch is responsible for leading the frog business in North America.
As head of frog North America, Jess Leitch is responsible for leading the frog business in North America. With a background in Service Design, Jess has spent the past 15 years leading teams in the design and launch of new products, services and businesses.
