Designing for Generative AI: Balancing Innovation and Usability


Generative AI (GenAI) is at the forefront of conversations in both internal discussions and client projects. As companies explore ways to integrate AI into their products, it’s essential to design experiences that are intelligent, innovative, and user-friendly.

What Is GenAI Good At?



Generative AI is reshaping interactions with technology, making them feel more human and intuitive. Here are some key areas where GenAI excels:

  • Conversational Interfaces: AI-powered chatbots and virtual assistants create personalized, natural interactions that enhance user experience.
  • Content Generation: From marketing copy to creative writing, GenAI speeds up content creation while maintaining quality, acting as a creative partner.
  • Data Synthesis: AI can quickly analyze vast data sets, identify patterns, and provide insights that aid decision-making.
  • Enhanced Collaboration: By handling repetitive tasks and suggesting ideas, GenAI improves workflow efficiency, allowing teams to focus on strategic work.

Despite its potential, GenAI is a tool—not the product itself. It should enhance the user experience without overshadowing usability or functionality.

User Expectations for GenAI-Powered Products


Adding GenAI to a product does not eliminate the need for strong UX fundamentals. Users still expect:

  • Ease of Use: The product should be intuitive and not require AI expertise.
  • Task Efficiency: AI should streamline processes, not introduce complexity.
  • Modern Interfaces: Users anticipate sleek, cutting-edge designs that reflect the AI’s capabilities.

However, integrating AI also comes with new challenges. Users expect GenAI-powered tools to be reliable, secure, and ethical.

Key Considerations Before Implementing GenAI


Consider these factors to ensure a safe and effective user experience:

  • Accuracy & Reliability: Users must trust that AI-generated responses are correct and useful.
  • Data Security: AI models should not compromise sensitive data.
  • Feedback Mechanisms: Users need ways to refine AI outputs and provide feedback for improvements.
  • Ethical AI Design: Be aware of AI blind spots, including potential misinformation, biases, and manipulation risks.
  • Managing AI Hallucinations: AI can generate incorrect responses. Determine your tolerance for errors before integrating GenAI.
  • Complementing UX, Not Replacing It: AI should enhance usability, not serve as a workaround for poor design.


Moving Beyond Chatbots: Designing AI Experiences Thoughtfully


A common pitfall in GenAI integration is defaulting to chatbots. While chat interfaces are valuable, AI can power a broader range of experiences. When designing AI-driven UX, consider:

  • Innovative Interactions: Use AI to enable intuitive, user-friendly interfaces beyond chat.
  • Simplicity: Users don’t need to understand AI’s inner workings—just how to get results.
  • Human Touch: Maintain human oversight where needed to ensure trust and support.


Case Study: Designing a GenAI-Powered Sales Tool


Our team recently developed a GenAI-powered application for a client’s sales team. The tool assists users in determining pricing and directing them to the appropriate support team. Initially, we built a chatbot experience, but testing revealed significant drawbacks:

  • User Distraction: Open-ended chat allowed users to veer off-topic.
  • Hallucination Concerns: We needed high accuracy, making flexible chat responses risky.
  • Repetitive Use Fatigue: Frequent users found conversational interfaces tedious.


Our Solution: Instead of making AI the focal point, we positioned it as an assistant:

  • Guided AI Support: A video and audio guide provides personalized assistance.
  • Contextual Chat: A side-panel chat delivers quick answers without disrupting the main workflow.
  • Data-Driven Insights: AI synthesizes user inputs to recommend optimal pricing strategies, but final decisions remain with users.

Lessons Learned


Through iteration, we discovered best practices for integrating GenAI effectively:

  • AI Should Assist, Not Dominate: Users preferred AI as a supportive assistant rather than the primary interface.
  • Transparency is Key: AI-generated insights were framed as recommendations, not absolute answers.
  • Domain Experts Are Crucial: Business experts helped refine AI outputs to ensure accuracy.
  • Hybrid AI Approaches Work Best: Combining GenAI with traditional algorithms improved data processing.

Conclusion


GenAI presents exciting opportunities for enhancing digital products, but thoughtful design is crucial. By focusing on usability, ethical considerations, and strategic AI integration, we can create AI-powered experiences that are both innovative and user-friendly.


As GenAI evolves, the key to success will be balancing technological capabilities with human-centric design. AI is a powerful tool—but at the end of the day, great UX still wins.

Contributions


Product designer: Lauren Bradley

Product designer/engineer: Natalie Eichorn