The Future of UX Design: Planning Conversational and Immersive Interfaces for AI

Users are increasingly engaging with AI through voice assistants, chatbots, and immersive technologies like augmented reality (AR) and virtual reality (VR). Such interfaces move beyond traditional screens, requiring UX designers to think in terms of dialogues, gestures, and environment-based cues. As AI powers these experiences, usability expectations rise, and the threshold for error shrinks.

Introduction

Today I will talk about how conversational user interfaces (CUIs) and immersive technologies reshape UX practices. It summarizes the core considerations for designing AI-driven chatbots and VR/AR experiences, highlighting both the opportunities to broaden user accessibility and the challenges of orchestrating non-linear interactions.

1. Designing Conversational Interfaces

Conversational interfaces provide a dynamic way to access AI services, enabling tasks to be handled through natural language rather than clicking or tapping. Research by the Nielsen Norman Group (2018) shows that well-designed chatbots can reduce customer service costs by up to 30%.

• Personality and Tone: Designers often treat these interfaces as “characters” that must reflect the brand’s voice. Overly formal or robotic styles can alienate users.
• Context Management: Conversations are rarely linear. Handling interruptions, clarifications, or follow-up questions requires robust context tracking so the AI “remembers” user intent.

2. Leveraging AR/VR with AI

Augmented and virtual reality experiences increasingly integrate real-time AI-driven elements—such as object recognition or predictive analytics overlaid onto physical spaces.

• Task-Centric Interaction: AR can, for instance, help maintenance technicians see on-screen instructions while repairing equipment. AI ensures real-time updates based on sensor data, but the UX must ensure that visual overlays do not clutter or confuse.
• Immersive Storytelling: VR training simulations powered by AI can adapt scenarios based on user decisions. This on-the-fly adaptation demands robust user testing to confirm that experiences remain coherent and educational.

3. Accessibility and Inclusivity

Multi-modal interfaces can broaden accessibility for individuals with specific needs. For example, voice commands may be beneficial for users with visual impairments, while AR can provide subtitles or real-time translations for those who are hard of hearing. However, adopting these technologies requires careful attention to potential new barriers:

• Speech Recognition Bias: Some voice systems struggle with diverse accents. Teams must test with varied user groups or risk alienating significant segments of the population.
• Hardware Constraints: AR/VR devices can be expensive or physically demanding, limiting certain user groups from participating.

Next Steps

• Prototype and Test Early: Low-fidelity conversational scripts or AR mockups can reveal flaws before committing to full-scale development.
• Focus on Real Tasks: Building “cool” features might be tempting, but ensuring they solve genuine user problems is essential for adoption and satisfaction.
• Collaborate with Accessibility Experts: Partnering with specialists helps identify potential hurdles early and ensures that new AI-driven interfaces serve the widest audience possible.

This article is part of a series of 6 articles. Check my Linkedin profile to read more about.

Philippy Gonzales

https://www.dhirubhai.net/in/uxbrazil