5 essential steps for designers to successfully embrace AI

What should a designer do if AI can already create art, design beautiful UI, write code, curate articles and more? Short answer, don’t get left behind by ignoring or being afraid of it.

As the field of user experience (UX) design continues to evolve, there is one technology that is making waves: artificial intelligence (AI). While some designers are either ignoring or unwilling to accept AI technology; others do not know how to bring it into their workflow. And there are still a few for whom the word “AI” is just a buzzword…

The truth is that incorporating AI into the UX design process can lead to significant benefits for both designers and users alike. In this article, we will explore why UX designers should embrace AI and how it can revolutionize the way we approach design. With Generative AI and new advancements happening everyday, navigating the changes happening in the tech industry can be a challenging but exciting opportunity. Here are some tips on how to navigate this change:

1. Understand the technology to ground yourself into reality 🧠

The solution can’t just be “AI will do it for the user” without knowing the how or to what extent. To effectively design products that leverage AI, you need to have a solid understanding of the technology. Educate yourself on the basics of AI and machine learning, and stay up-to-date on the latest advancements. You can do this by—

1. Experiment with AI tools: Did you try out the popular AI tools like Stable diffusion, Midjourney, ChatGPT? Or many AI tools and platforms available that can help you incorporate AI into your designs. Like a bunch of features introduced to Adobe CC; or in Canva; or Figma plugins to auto generate icons, avatars, images and more. Experimenting with these tools and platforms can help you understand how they work and how they can be applied to your design projects.
2. Read more, learn more: You can start with IBM technology, Olivio Sarikas’s youtube channel to keep yourself up to date on AI. Or there are many industry publications and blogs that cover the latest developments in AI and how it is being applied to UX design. Here are the ones I’ll recommend: Nielsen Norman Group, Smashing magazine, UX Magazine, UX Collective blog. Subscribing to these publications and reading them regularly can help you stay up-to-date on the latest trends and best practices.
3. Take an online course to learn the basics: There are numerous online courses, like this, that can teach you the basics of AI and how it can be applied to design. These courses range from free to paid, high-level to in-depth, offered by universities or individual experts. Learn about the subject, the buzzwords like ML, NLP, Computer vision and what are the differences, what are the applications etc.
4. Attend events and talk to the relevant people: Industry events such as conferences and meetups are a great way to learn more about AI and how it is being used in UX design. You can listen to keynote speakers, attend workshops, and network with other professionals who are working with AI (more on this below)

By taking these steps, you can gain a deeper understanding of AI and how it can be applied to UX design. This can help you create more effective and engaging designs that meet the needs and preferences of users.

2. Collaborate with AI experts 🤜🏼🤛🏾

By now you are probably already working on a project (or soon will) that integrates AI in your product. Work closely with AI experts (ML engineers, ML research scientists, data scientist, software engineers etc.) on your team or in your organization. They can provide valuable insights into what’s possible and what’s not, and help you design products that take full advantage of AI capabilities. Collaboration between designers and AI experts can be a powerful way to create innovative and effective design solutions. Here are some ways you can work together:

1. Understand each other’s skills and expertise: This will help ensure effective collaboration and that you both speak the same language. Do you know what unstructured learning, LLP, Generative AI, Vision, etc. mean? If you need to understand what your team is talking about, to effectively contribute to the discussions (goes back to the point 1)
2. Involve AI experts early in the design process: This way AI is incorporated in a way that is effective and efficient. They can provide valuable insights into what’s possible and what’s not, and help identify AI opportunities in the designs.
3. Collaborate on defining the problem: This brings all parties to the same page on user needs, goals, and pain points, and can work together to create a solution that addresses those needs.
4. Co-create solutions: Work together to co-create solutions that leverage AI in a way that enhances the user experience. By working together, you can ensure that the design is both effective and engaging, and meets the needs and preferences of users.
5. Analyze data to test and iterate: Work with AI experts to analyze the results and iterate on the design as necessary. This will help ensure that the solution is effective and meets the needs of users.

3. Continue focussing on the user experience ⭐️

Stop wasting your time perfecting the layouts, colors and fonts. AI will do that job way better than you!

Always keep the user in mind when designing products that will leverage AI. Consider how AI can make the user experience more intuitive, simple, efficient, and personalized. Here are some ways AI can enhance user experience:

1. Automating repetitive tasks: AI can automate tasks such as form filling, data entry, and document processing, which can save users time and reduce frustration. This can be achieved through the use of natural language processing (NLP), computer vision, and other AI technologies.
2. Personalizing user experiences: By analyzing user behavior, preferences, and history to provide customized recommendations and content. For example, AI-powered recommendation engines can suggest products, services, or content based on a user’s browsing and purchase history.
3. Providing predictive assistance: By anticipating user needs and providing relevant information or suggestions. For example, an AI-powered virtual assistant can suggest an appointment based on a user’s calendar, or provide relevant information based on a user’s location.
4. Simplifying complex tasks: Such as data analysis and decision-making by providing visualizations and insights. For example, an AI-powered dashboard can provide visualizations of data that enable users to quickly identify trends and patterns.
5. Improving accessibility: By providing voice interfaces and other assistive technologies that enable users with disabilities to access information and services. For example, an AI-powered voice assistant can help users with visual impairments to order groceries, book an Uber, call someone, play music, etc.

By leveraging AI to automate tasks, personalize experiences, and provide predictive assistance, designers can create simpler, more intuitive, and more efficient user experiences that meet the needs and preferences of users.

4. Embrace experimentation 🌱

AI is still a relatively new technology, and there is still much to be learned about its capabilities and limitations. Embrace experimentation and testing in your product design process to learn what works and what doesn’t:

1. Understand the capabilities and limitations of AI: Before starting an AI experiment, you should have a good understanding of what AI can and cannot do. This will help you design experiments that are feasible and have a high chance of success.
2. Identify potential areas for AI experimentation: You should explore different areas where AI could potentially enhance the user experience. Start with experimenting what is working out in the market right now e.g. chatbots, personalized recommendations, generating content, or predictive analytics, in your product.
3. Start small and iterate: Put on your Growth hat and start with small experiments and iterate as you go. Testing smaller and sooner will help refine the ideas without investing too much time or resources upfront.
4. Collaborate with data scientists: Data scientists or growth analysts can help with tasks such as setting up the AI experiment in the right way, gather the learnings that define the designs and more.
5. Test and measure the results: As a designer, you should pay attention to the qualitative tests done with users and quantitative results gathered from user behavior of using AI product experiment. This will help understand how users are interacting with the AI system and whether it’s providing value.
6. Learn from failures: Not every AI experiment will be successful, and that’s okay. Celebrate the failures, learn from them and use that knowledge to improve future experiments.

Designers should be open to experimentation with AI and embrace the iterative process of developing and testing new ideas. By working closely with data scientists and focusing on user needs, designers can create AI experiments that provide real value to users.

5. Design ethically ❤️

As with any technology, AI can be used for both good and bad. Designers are the user’s voice, should hold themselves accountable to design the AI products in such a way that it ethically serves the users and the business for the good and don’t harm or perpetuate biases. Here are some steps to consider when designing AI products ethically:

1. Set guiding principles and guardrails: Spend enough time at defining the core values of the products that your team MUST adhere to. Consider the ethical implications of the AI product. This includes thinking about potential biases, fairness, and privacy concerns. Your team must step back if any of these principles break, specially when your test shows successful metric impact.
2. Involve diverse perspectives: Include diverse perspectives from cross-functional team in the design process. Or recruit users for research from varying backgrounds (such as marginalized communities). This helps to identify and address potential biases and ethical concerns.
3. Prioritize transparency: Automation is inversely proportional to user’s trust. So, be transparent about how the AI product works, including the data it uses, the algorithms it employs, and the purpose and potential impact of the system to users.
4. Protect user privacy: Implement strong data protection measures, such as data minimization, user consent, and secure data storage. Consider how the data is collected, used, and shared.
5. Avoid discrimination and bias: Ensure that the AI product is designed to avoid discrimination and bias. This includes testing for potential biases and ensuring that the AI product is fair and equitable for all users. Designers may not have control over how the data has been collected which can have its inherent bias. But at least do your part by laying out the edge cases and scenarios where AI might be biased.
6. Continuously monitor and evaluate: Monitor the AI product continuously to identify any potential ethical concerns that may arise over time. Evaluate the product regularly to ensure that it aligns with the principles and values the team defined.

Be the force for good and help ensure that AI products are designed and deployed in an ethical manner, and that they serve the greater good of society.

Despite these benefits, some UX designers may be hesitant to adopt AI, citing concerns about job security and the potential for AI to replace human designers. However, the reality is that AI is not meant to replace designers, but rather to augment their skills and abilities. By automating routine tasks and providing insights and recommendations, AI can help designers work more effectively and efficiently, allowing them to focus on the critical thinking and creative aspects of design that AI cannot replicate. (as of now)

Designers should embrace AI as a tool that can revolutionize the way we approach design. By streamlining the design process, creating more personalized experiences, and making data-driven decisions, AI can help designers create more effective and engaging designs that meet the needs and preferences of users. Rather than seeing AI as a threat to job security, designers should see it as an opportunity to augment their skills and abilities, and take the user experiences to the next level.