The year 2023 marked a notable rise in the availability and adoption of AI tools across different fields, reflecting the rapid evolution of this technology. To understand how these transformative tools are designed, we took a closer look at several popular examples in the market. Through our analysis, we aimed to uncover the patterns and behaviors that make these tools effective in their respective domains.
Key Elements to Consider:
Let’s first dive into the key elements that are fundamental for creating exceptional AI tools.
1. Prompt Area
The prompt area serves as the gateway to AI magic. This is where users specify their desired response from the AI model. Whether it’s through text-based input, images, videos, or files, the more detailed and descriptive the prompt, the better the AI model can generate a relevant and accurate response.
Runway — aside from the text prompt, a section to feed images and refine parameters can be found for better refinements
Grammarly — a comprehensive list of options to inspire users on ways to improve their text through AI
2. Results, Refinements, and Version History
Empowering users to fine-tune the AI-generated output is crucial. By providing the ability to regenerate and refine the results, users can customize the content to meet their specific requirements. Additionally, incorporating a comprehensive version history feature enables users to review and compare different iterations of the generated content, making it easier to select the most suitable output.
Jasper AI — the refined version is provided on top of the previous copy for comparison
3. Quick actions after content generations
Make sure to close the loop and keep the momentum going. Offering purposeful actions immediately after content generation brings users one step closer to their next task. Whether it’s copying or downloading the outputs, these functionalities seamlessly integrate AI-generated content into users’ workflows. And don’t forget the importance of feedback mechanisms, which reassure users that future outputs will be even more accurate and relevant.
Midjourney — options to upsize the resolution or create more variation of a generated image
ChatGPT — users can provide feedback, flag any inaccuracies, inconsistencies, or biases in the output
4. Buffer before AI Results
Patience is a virtue, but we can make the waiting game a little easier. Since calling the ChatGPT API may take some time, it’s crucial to provide users with a loading indicator and the option to halt the process if needed. This thoughtful feature ensures a smoother user experience and prevents frustration caused by long waiting periods.
Hostinger—walks through the different stages of website building processes to create anticipation and entertainment during the long wait
Design Approaches Adopted by Others:
Now, let’s explore the exciting design approaches that have been adopted by other AI tool creators. Remember, the approach you choose should align with your product and the desired user interaction, creating a tailored and delightful experience.
1. Drawer / Popup
A drawer or popup-style interface is one of the more common designs seen across AI tools today. It dedicates most of the screen space to your primary workstation, allowing you to stay focused on the content you’re working on, while ensuring easy accessibility to AI features when needed.
Canva—AI support is available as a drawer if the user intended
2. Side-Panel Integration
With a side-panel integration, you can create a more comprehensive AI experience. Though it takes up some screen space, this layout visually separates the prompt area from your existing content. The persistent visibility of the prompt reassures you that your settings are retained within the AI-generated process.
Jasper AI — side panel gives reassurance that inputs are always remembered
3. Form or Step-by-Step Process
This approach helps users provide the necessary information and structure their content effectively. It works wonders when personalization significantly influences the AI output. By occupying the entire page, distractions are minimized, and your focus remains intact.
Neural Canvas — fill up questions to generate an e-book with the given details
LogoAI — full-page step-by-step form for a logo creation
4. Chat-based Chat-based AI tools provide users with an open-ended and conversational experience when interacting with AI systems. Unlike other AI approaches that follow a more structured format, chat-based AI allows users to engage in a back-and-forth dialogue, enabling them to explore multiple topics, ask follow-up questions, and receive dynamic responses.
Microsoft Bing—encourages users to explore outside the original question fostering idea stimulation
5. Inline Completion
Offering inline suggestions and completions is a fantastic way to enhance content creation. The subtle design allows you to easily dismiss unhelpful suggestions, but when they’re on point, it adds that “wow” factor. Best of all, these suggestions seamlessly integrate into your workflow, just a keystroke away, keeping your hands on the keyboard and your productivity soaring.
GitHub Copilot — shows suggested code as autocomplete
We hope you’ve gained valuable insights into this fascinating field. If you would like to explore further how we have tailored AI to meet the unique needs of tech documentation, read our blog at Designing AI-Powered Content Suggestions for Tech Documentation.
