Next-Gen UX: From Apps To Natural Language

(MENAFN- Khaleej Times) Apps reign supreme in our digital world

We use apps for everything: searching, browsing, learning, writing, reading, communicating, connecting, creating and, of course, completing tasks. Yet, beneath this convenience lies a fragmented reality.

Our digital lives resemble isolated islands of single-purpose apps, each in its own silo, demanding constant attention. This leads to a disjointed user experience where brand ecosystems overshadow our evolving, diverse needs as individuals.

The reality is that apps and websites aren't always the best ways to get the job done. In particular, they are terrible for completing more nuanced tasks, requiring continuous task-switching and leading to increased mental load. Take, for example, comparing costs to book a flight. You'd first need to scan various sites or apps, compare prices, routes and then come back to your preferred option to book. Current price comparison sites exist today but are too clunky to make booking a smooth process. Plus, the lack of pricing transparency and complexity of such a search make these sites hard to trust and harder to navigate.

However, a revolution is underway, spurred by the fertile grounds of Generative AI (GenAI). We are witnessing a pivotal shift from app-centric to natural language-centric experiences, where user journeys transcend individual platform boundaries, transforming frustrating, disconnected interactions into integrated, holistic experiences.

Today's consumers, especially Gen Z and Gen Alpha, yearn for real-time, anticipatory experiences. They envision AI as an invisible assistant, seamlessly coordinating tasks and services across platforms, delivering insights and solutions instantaneously.

This transformation is exemplified by the Rabbit r1, an innovative personal AI assistant . Its Large Action Model (LAM), a type of "universal controller for apps," not only learns your preferences, but performs actions aligned with them: anticipating your needs and seamlessly orchestrating tasks across various apps. Imagine planning a weekend getaway. Once trained on your preferences, the r1 could manage everything -from flights and hotels to restaurant reservations and activity bookings - crafting a seamless tapestry of experiences rather than a disjointed series of app interactions. Or train it to streamline paying bills, avoiding the need for dealing with a phone tree or unresponsive online forms.

More AI-driven examples demonstrate how the app as we know it may be losing ground. At 2024's Mobile World Congress, Deutsche Telekom debuted an app-free phone . The company's CEO Tim Hoettges went as far as to say, "I can tell you that in 5 – 10 years from now, nobody from us will use apps anymore."

In this emerging landscape, we face unique challenges and opportunities. A natural language-centric revolution means that our primary way of interacting with digital devices will mirror how we interact with each other. We won't need to navigate through multiple apps to complete an action. We'll just say what we need into our devices, by chat interactions and voice recognition . This paradigm shift will revolutionise our approach to product and service design , making natural language-centric interaction the standard. The competitive edge will increasingly be defined by the service delivery model, rather than just the user interface.

Here are some guiding principles and use case examples for designing in this new era:

1. Privacy as a Paradigm:

Building trust is critical when actions occur behind the scenes. We need to design for ethical and transparent AI, giving users control over their data privacy . To build trust in this first stage of the AI revolution, it is critical to give users the ability to verify and modify the data and outputs from LLMs and LAMs.

2. Frictionless Interoperability:

We must break down the barriers between apps, enabling seamless data and service exchange. Imagine an AI assistant that integrates with your calendar, fitness tracker and music streaming service, personalising your schedule, workouts and playlists based on real-time needs and preferences.

3. Adaptive Experiences:

Future experiences must dynamically adapt to user needs through contextual awareness. The Large Action Model allows every person to train their experiences. For instance, your home could transform into a spa-like environment for relaxation, with lights dimming and chill music playing automatically as you walked through the door after a busy day.

4. Empathy to Balance Efficiency:

Prioritising emotional resonance in design is essential, rather than focusing solely on task efficiency. A mental health service, for instance, could function as an empathetic companion, engaging you with thoughtful questions, active listening and reflective conversations, all attuned to your current mood and emotional state.

5. Exploration, Taste and Expression:

In a future guided by AI's recommendations, content generation and optimised experiences, maintaining the uniqueness of personal and brand expression is crucial. While AI streamlines and unifies, we must create spaces away from uniformity. We want people and brands to have the freedom to explore, develop unique tastes and craft dynamic narratives. Such intentional design strategies are key to preserving diversity and promoting the richness of personal and brand expression in an AI-assisted landscape.

We stand at the forefront of not only new products and technologies, but also a paradigm shift. Both new ventures and established businesses are taking notice. Tomorrow's users will seek experiences that flow as naturally as their thoughts and emotions.

The natural language-centric revolution is here. Are you prepared to design for it? Let's embark on this journey together , reshaping the digital landscape to be more intuitive, empathetic, efficient and aligned with our human needs.

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