Usability conventions constantly evolve, shaped by technological advancements and changing user expectations. Consider how mobile touchscreens transformed web design. Interfaces became more responsive, buttons grew larger for touch accuracy, and scrolling replaced pagination. Voice assistants introduced hands-free interactions, shifting how users search and control smart devices. Even something as simple as swipe gestures, once unfamiliar, is now second nature.
Now, we're on the brink of another significant shift: the rise of conversational interfaces powered by large language models (LLMs) and AI chatbots. As these systems increasingly integrate into our digital experiences, we must rethink usability conventions again.
And conversational AI isn't the only emerging trend. Generative UI will also reshape how interfaces dynamically adapt to user needs.
Conversational Interfaces: When do they work best?
LLMs, such as ChatGPT, enable users to interact with systems using natural language instead of navigating through menus or filling out forms. This development holds the promise of simplifying complex workflows, providing quicker access to information, and creating more intuitive user experiences. But does that mean conversation always enhances usability? Not necessarily.
A well-crafted conversational interface must align with the user's intent and context. Here are some essential factors to consider:
Efficiency: Sometimes, a well-designed button can outperform typing out a request. We must carefully consider when AI-powered conversations improve usability and when traditional UI elements are more efficient.
Engagement: For consumer experiences, visual browsing might provide more satisfaction than a Q&A format. Users might prefer flipping through a digital library rather than having an AI summarise book recommendations, for example.
Value: Subject experts may have domain-specific knowledge that AI lacks, allowing them to spot nuances that algorithms might miss. For instance, some scientists might prefer working directly with data to form their own hypotheses and interpretations, rather than being guided or primed by AI's suggestions.
AI excels at pattern recognition, summarisation, and automation. It can surface insights, highlight gaps, and assist decision-making. However, it lacks human intuition, contextual understanding, and empathy. Thus, usability research must transcend mere quantitative data; it requires us to observe users, listen to their frustrations, and grasp their motivations.
Differentiation through experience design
As more products adopt conversational AI, there's a risk of everything looking and feeling the same. How can brands stand out if every product offers the same AI-powered chat? The answer lies in user experience design. The key differentiator won't be the AI technology itself, but how well a product understands and caters to user needs. Deep user insights, thoughtful interaction design, and a strong focus on the human experience will set great products apart.
The future of usability conventions is exciting, but we must approach it with care. AI isn't a replacement for good design; instead, it should serve as a tool that, when used wisely, can enhance it. The challenge ahead is not just about adopting new technologies but ensuring they genuinely improve how users interact with the digital world.
