{"id":16967,"date":"2024-04-11T15:57:58","date_gmt":"2024-04-11T14:57:58","guid":{"rendered":"https:\/\/uxstudioteam.com\/ux-blog\/?p=16967"},"modified":"2024-06-17T14:20:52","modified_gmt":"2024-06-17T13:20:52","slug":"best-ai-design-tools","status":"publish","type":"post","link":"https:\/\/timemachine.uxstudioteam.com\/ux-blog\/best-ai-design-tools\/","title":{"rendered":"Best AI Design Tools: Insights & Tips From 50+ Tools"},"content":{"rendered":"

Generative AI has taken the world by storm. Anyone can generate images and designs in different styles with a few words, and naturally, this affects design and AI design tools. We have reviewed 50+ current AI design tools to understand their capabilities, strengths, and limitations<\/span> so we can understand the impact AI will have on the design industry and on our work as designers. We also share our recommendations for the best ones.\u00a0<\/strong><\/p>\n

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\"Decorative<\/h2>\n

Impact of AI in design<\/b><\/h2>\n

When it comes to design, AI has great creative capacity, given its text generation and text-to-image capabilities. Seeing some photorealistic images generated by AI, we cannot help but wonder what this means for us as designers.\u00a0<\/span><\/p>\n

Some of the questions that were on our minds:<\/span><\/p>\n

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  1. How can we use this technology to our benefit?\u00a0<\/span><\/li>\n
  2. How can it actually help us, especially in areas like product and UX design? Does it do what it promises?\u00a0<\/span><\/li>\n
  3. What are the current options, and how can we integrate this into our workflow as design?<\/span><\/li>\n<\/ol>\n

    We set out to explore these questions by looking into AI design tools.\u00a0<\/span><\/p>\n

    Our experience working with AI design tools<\/b><\/h2>\n

    Our experiment allowed us to understand both the benefits and limitations of AI design tools. While the results can vary, we believe this is what you can generally expect when you start to work with AI design tools.\u00a0<\/span><\/p>\n

    \"AI
    Image generated with DALL-E 3.<\/figcaption><\/figure>\n

    Benefits of using AI design tools<\/b><\/h2>\n

    Let’s start with the good things first. Currently, AI design tools are great for ideation, especially for new projects and products. This is due to the following factors.\u00a0\u00a0<\/span><\/b><\/p>\n

    1. Speed and quantity of ideas<\/b><\/b><\/h3>\n

    One of the biggest benefits of current AI design tools is that they can help designers generate lots of ideas within a very short amount of time. When it comes to screen or wireframe generation, designers can have starting screens ready in less than 5 minutes by using text-to-image tools like Uizard, Also, platforms like ChatGPT can be used to approach different design directions or angles to a specific problem. And if the ideas are not good enough, there’s almost always a Regenerate option.\u00a0<\/span><\/p>\n

    While the quality of the ideas might be debatable, one thing’s for sure: when it comes to the speed with which these are generated and the volume of ideas, it’s hard to beat these tools. Additionally, it might provide designers with approaches they haven’t considered before.\u00a0<\/span><\/b><\/p>\n

    2. Ideation kickstarter\u00a0<\/b><\/b><\/h3>\n

    Because they can produce a lot of ideas quickly, AI design tools can be a great help in kick-starting ideation, especially for new projects and for simple design problems \u2014\u00a0 we’ll go into this a bit later on.\u00a0<\/span><\/p>\n

    However, the usefulness of this approach depends on the designer. For some, this could be very inspiring and refreshing, especially if the AI tools provide ideas or approaches they haven’t considered. Still, for a designer who feels more comfortable sketching to understand a concept better or to explore different ideas, this approach might not be that valuable.<\/span><\/p>\n

    AI design tools limitations<\/b><\/b><\/h2>\n

    1. Design output can be pretty generic<\/b><\/b><\/h3>\n

    One of the issues with generative AI and large language models is that the output is pretty generic. From our experience, even with a detailed prompt, the visual output often feels like the AI design tools work based on layout templates filled in with automatically generated text. Also, the style isn’t too original: it looks a lot like the clean, modern, sans-serif, almost ubiquitous designs we see almost everywhere.\u00a0<\/span><\/p>\n

    Some of these AI design tools provide customization options, but they are fairly limited: a few font options and some styles. Also, it doesn’t solve the initial problem: that the output is pretty standard, somewhat generic and lacking a fresh perspective or approach.\u00a0<\/span><\/p>\n

    In the cases where the AI design tool does come up with multiple variants, there is little difference between them and it’s mostly on the layout level.\u00a0<\/span><\/p>\n

    It will still be up to designers to come up with visually remarkable ideas that communicate brand identity and stand out.\u00a0<\/span><\/b><\/p>\n

    2. AI design tools cannot consider deeper context<\/b><\/b><\/h3>\n

    For now, AI design tools mostly react to prompts that provide details about the style, device, and specific features within an app, such as a dashboard. However, when it comes to further details about the target audience, like age or other characteristics, it misses these details or misinterprets them.\u00a0<\/span><\/p>\n

    This is especially important as designers often need to be aware of multiple inputs, perspectives, and constraints. For example, in order to develop a new feature in a larger, mature organization, designers need to be aware of development and potential legal constraints to start with. They might also need to take into account insights from research and they might also need to deal with marketing or sales requests at the same time.\u00a0<\/span><\/p>\n

    \"AI
    Image generated with DALL-E 3.<\/figcaption><\/figure>\n

    For the time being, AI tools can only take into account a single, briefly defined perspective.\u00a0<\/span><\/p>\n

    Example: In testing an AI design tool that provides color suggestions, we tried using prompts with different details about the target audience. One of the prompts asked for a color palette for a Gen-Z target audience, while the other prompt focused on an elderly target audience. There was little difference between the two generated outputs.\u00a0<\/span><\/b><\/p>\n

    3. Can provide solutions for simple design problems<\/b><\/b><\/h3>\n

    Most of the AI design tools we’ve encountered focus on rather simple design use cases like landing pages or marketing websites for startups or small businesses. Sometimes these tools can also provide some ideas for mobile apps with specific features.\u00a0<\/span><\/p>\n

    However, we haven’t noticed any AI design tools that can tackle more specialized use cases and complex interfaces like enterprise or B2B. Here, domain knowledge is extensive, there are often multiple constraints to keep in mind, all of which might be difficult to include in a simple prompt.\u00a0<\/span><\/p>\n

    In our experience, introducing features like a check-out flow seemed to be the breaking point for the capacity of the AI design tools we looked at. For features that require custom inputs from users, whether it’s via input fields or checkboxes, for example, AI design tools might not be the best.\u00a0<\/span><\/b><\/p>\n

    4. AI design tools can mostly focus on new products\u00a0<\/b><\/b><\/h3>\n

    Design systems and their predecessors, UI kits, are the standard for designers these days. It\u2019s especially true when multiple designers are working on the same product or if it’s a suite of products that need to be visually consistent.\u00a0<\/span><\/p>\n

    None of the AI design tools we’ve tested provided the option to integrate a design system or to include a list of already designed components to include in the visual output. At best, most of these products allow users to define a style to generate the output.\u00a0<\/span><\/p>\n

    Especially for designers who have been working with design systems for a long time, this decreases the amount of value they can get from AI design tools. Even if they use these tools to generate new ideas, designers would still need to spend quite a bit of time seeing how they can align the ideas with their current design system.\u00a0<\/span><\/b><\/p>\n

    5. Consistency issues within designs and copy<\/b><\/b><\/h3>\n

    Current AI models don\u2019t have awareness and are prone to memory issues. You can easily see that when you’re prompting a tool and it starts to forget some of the information included in previous prompts. We noticed something similar in AI design tools, especially in wireframe and UI generators. In some cases, the visual output wasn’t consistent. Other times, the tone of voice and overall copy were completely off for the given prompt.\u00a0<\/span><\/p>\n

    In one of the AI wireframes and UI generators, we prompted the tool to create some screens for a B2B e-commerce for a chemicals supplier. While it created quite a few screens for the purchasing flow, there were considerable consistency issues from one screen to another. Sometimes the menus were differently structured, other times cards featured on the same page contained different content. Button spacings varied, too. Also, it didn’t really feel that the screens were connected to one another. Even when trying different prompts, the tool kept struggling to follow the prompts.<\/span><\/p>\n

    \"AI
    Screenshot from the output generated for “B2B e-commerce for a chemicals supplier”<\/figcaption><\/figure>\n

    6. Contrast and accessibility issues<\/b><\/b><\/h3>\n

    This was another surprising issue. Some of the AI design tools we tested had considerable issues with contrast and accessibility. Once more, it emphasizes the designer’s skills and experience to catch and correct these issues.\u00a0<\/span><\/p>\n

    Note that one of the main calls to action buttons is black text on a navy background.\u00a0<\/span><\/p>\n

    \"AI
    Screenshot of the output of a screen with the same prompt<\/figcaption><\/figure>\n

    7. AIs don’t always deliver on their promise<\/b><\/b><\/h3>\n

    One of the most surprising takeaways from testing AI design tools was that the AI within the product didn’t always perform as it claimed to. We tried testing some of these at different times and with different prompts, but we kept getting an error message straight away.\u00a0<\/span><\/p>\n

    Additionally, in some cases, the claimed AI within a product is mostly a long list of generated combinations. Which if you think about it, is not actually AI, it’s standard conditional programming. As Reka pointed out in her article about AI research tools, whenever a product claims they’re using AI, take that with a grain of salt and test it to see how and if it actually works.\u00a0<\/span><\/p>\n

    Example: One of the AI logo generators we tried produced a series of combinations of colors, fonts, and icons that we had previously selected. Another icon generator tool produced results that were far from usable.<\/span><\/p>\n

    AI design tools recommendations<\/b><\/h2>\n

    Check out below some of the best AI design tools that we’ve tested.\u00a0<\/span><\/p>\n

    AI Logo generators\u00a0<\/strong><\/h3>\n

    We looked at several tools in this category, and <\/span>Looka<\/span><\/a> and <\/span>Brandmark<\/span><\/a> are definitely the most promising. However, given the output quality, these might not be suitable for designers. They can be more useful for small business owners and startups looking to generate ideas.\u00a0\u00a0<\/span><\/p>\n

    AI UI & wireframe generators\u00a0<\/strong><\/h3>\n

    V0 by Vercel<\/a><\/strong><\/p>\n