Generative AI is transforming the way we interact with technology. At Google Cloud, our Applied AI Engineering team has shaped the design and development of generative AI solutions for Generative AI for Marketing, Customer Experience Modernization, and Open Data QnA (NL2SQL), among others. Throughout this process, we’ve gained valuable insights that we believe can help others to successfully and responsibly design and implement these cutting-edge technologies. In this blog post, we’ll share valuable lessons learned with three overarching design principles:
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Offer Frictionless Experiences: Design interactions that are intuitive, streamlined, and minimize any barriers to use.
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Build Trust Through Transparency: Explain AI’s role in the user journey. Be open about the system’s capabilities and limitations.
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Prioritize Your Goals: Determine whether you aim for enhanced engagement, increased conversion rates, or something else entirely.
Offer Frictionless Experiences
Indicate what action is being performed by AI or what content is being generated by AI
Openly communicating AI’s role in the user experience builds trust and empowers users. Transparency sets realistic expectations and prevents confusion or feeling misled. By clearly signaling when AI is involved, users can develop an accurate understanding of the system and how best to interact with it.
Recommendation:
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Implement clear visual cues, such as icons, color coding, or text labels, to distinguish AI-generated content or actions.
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Offer progressive disclosure mechanisms, allowing users to request more detail about how a particular output was generated.
