Tips for integrating AI into your design process
Join me as I share 5 prompts you can use right now to enhance your discovery process, dive into trivia, and talk about this week's cool tech discovery.
Good morning designers! Today, I want to start by expressing my sincere gratitude to all of you who reached out about the free template included in last week's post—your feedback and enthusiasm truly made my week!
As for today's post, it's one I've been particularly excited to share. Over the past few weeks, some of you might have noticed that I've been running a series of surveys on how designers are using AI to enhance their workflow. While the results are still pending, the insights I've gathered so far have already sparked a lot of inspiration.
As both an AI power user and designer, I've experienced firsthand the transformative impact AI can have on our work. I often find myself thinking, "I wish I had tools like this when I first started," and this sentiment has largely motivated me to write this post—it's all about helping you supercharge your design workflow with the power of Gen AI.
So, whether you're new to AI or already experimenting with it, I hope the tips I share today will provide you with some practical ways to integrate AI into your design thinking process.
Trivia Time!
It’s safe to say that we’re all pretty used to touchscreen devices—they’re a common part of our everyday lives now. But as you may know, this wasn’t always the case. Crazy, right? Seriously, could you imagine a world without touch screens? What would Candy Crush or Angry Birds look like? I guess we’ll just have to wonder! But with that in mind, here’s today’s trivia question:
➡️ Do you know what the first product to introduce a touchscreen was?
Find the answer at the bottom of today’s post!
Tips for integrating AI into your design process
The Importance of AI in Design
In today’s fast-paced design world, staying competitive requires more than just keeping up with trends—it’s about leveraging the right tools to get ahead. AI isn’t just a buzzword; it’s a powerful resource that helps you work smarter, create better user experiences, and maintain your edge in the industry. By streamlining repetitive tasks and providing data-driven insights, AI can be a game-changer in your design process.
To help you maximize the benefits of AI, I’m breaking down how you could use it within each phase of the design thinking process. I’ll be presenting you with a few scenarios and examples of prompts based on my real-life interactions with Gen AI models like GPT, Claude, and Co-pilot. To avoid overwhelming you with information, we’ll start with the discovery phase today, and in future posts, I’ll focus on each subsequent phase. So whether you’re new to AI or already experimenting, these tips will offer practical ways to integrate AI into your everyday work.
Scenario 1: Preparing for a Kick-Off Meeting
Scenario: I need to prepare for an upcoming kick-off meeting where we’ll discuss the project’s objectives and next steps. I want to ensure I’m prepared to ask the right questions and cover all critical areas so that I can confidently move forward in my workflow.
Thoughts: In situations like this, I like to treat my AI assistant as a sounding board and ask if I’m missing anything or if it suggests adding something to my questionnaire lineup. It’s an opportunity to provide details about the general problem space, maybe even share some questions I already have queued up. You might find that the very act of writing out your thoughts can go a long way. Below I’ll share an example of how this could be put into practice.
Prompt Example: “Hey chat, I’m going into a kick-off meeting to discuss next steps for the new checkout flow for our e-commerce store. My briefing says users are having a hard time moving forward after reviewing their cart, and we’ve heard loading times can get pretty messy during this step. Aside from timelines, what other questions should I be asking during this call? Consider that I’m a UX/UI designer at XYZ Ecommerce store.
Leveraging the response: As you review your AI assistants suggestions, keep in mind that your expertise as a designer is key. Use your understanding of the project to filter out what’s most relevant. Not everything will apply, but that’s okay—focus on what will truly drive the conversation forward with your team. I encourage you to also play around with the possibilities maybe you can even ask your AI assistant to help craft a meeting agenda that centers on the most important points. The goal here is to take these tools, adapt them to your needs, and make the process uniquely yours.
Scenario 2: Creating a Lean User Persona
Scenario: I might be resource-constrained, but I want to create a lean user persona that includes high-level attributes based on my understanding of the user or customer. This persona could be used to align with others on the team, creating a common language as we prepare for a user research testing plan.
Thoughts: I’ve found this to be a great way to save time. By leveraging my AI assistant to help organize my thoughts, I can quickly create and refine personas. Since personas often have multiple attributes, I like to explicitly ask for the ones I feel are most relevant and request the persona in a table format. This makes it easier to comb through the details and make adjustments as needed. See the prompt example and interaction below for how this might look.
Prompt Example: “Hey chat, I need to create a lean user persona for a quick alignment with my team. Here’s what I know: Our product is a fitness tracking app designed for users who are new to fitness routines and need guidance on forming healthy habits. I understand our users to be tech-savvy millennials who value convenience and personalized experiences. Can you help me draft a persona that includes the following key attributes: name: age range, goals, pain points, tech proficiency, and activity level. Please present the information in a table format for easy review.”
How to Leverage the Response: While the AI-generated persona is a great starting point, remember that it’s not exhaustive. Don’t hesitate to add or modify fields that you feel will be important when communicating with your stakeholders. The persona should be a flexible tool that evolves as you gather more information and insights. Customize it to fit your project’s needs and make sure it aligns with your team’s understanding of the user.
Scenario 3: Generating a Testing Plan Report
Scenario: I’ve identified that a user research study is required to better understand why users are not finding the onboarding experience of our [SaaS idea] satisfactory. To align our team and stakeholders on the objectives and scope of this study, I need to generate a comprehensive testing plan report. This report will clarify why the study is being conducted, what type of research will be used, and how the results will be tracked.
Thoughts: Using an AI assistant can save significant time by helping you draft a detailed report that includes all necessary information. Leveraging AI in this way allows you to gather your thoughts and ask clarifying questions to ensure the report is accurate and tailored to your needs. Below, I'll share how I might approach asking ChatGPT to aid in this process
Prompt Example: “Can you help me generate a testing plan report for our upcoming user research study? The report should include the purpose of the study, the research methodology we’ll use, a list of stakeholders, our expectations, and how we will track the results. Please ensure the final document is formatted as a Word doc. Before we begin, please ask me clarifying questions to ensure the report is accurate.”
How to Leverage the Response: The AI’s generated report will give you a solid foundation, but it’s important to review and customize it to fit the specific needs of your project. Make sure to answer any clarifying questions the AI might ask, as these will help tailor the report to your exact requirements. Once the initial draft is ready, use it as a springboard for further refinement, ensuring all details are aligned with your project goals. By taking the time to personalize the AI-generated content, you can ensure that your testing plan report not only meets but exceeds expectations, providing clear guidance for your team and stakeholders.
Scenario 4: Brainstorming and Drafting a Survey
Scenario: I want to identify areas where we can introduce new features or enhance existing ones. To do this, I consider drafting a survey that can be sent to both existing users and potential customers. The survey could explore both current user experiences and potential future needs, helping me gather insights that will drive user engagement and app improvements.
Thoughts: Starting with a template is often easier, but even then, finding the right words and potential answers can be time-consuming. This is where an AI assistant can really help. By assisting in brainstorming and drafting a survey, AI can streamline the process, ensuring that the questions are targeted and relevant. In the example below, I'll share how I might approach asking ChatGPT to help me brainstorm for the scenario described above.
Prompt Example: “Can you help me brainstorm and draft a survey for our photo-sharing application? The survey should aim to identify areas where we can introduce new features or enhance existing ones. It will be sent to both existing users and potential customers, so please include branched questions that explore both current experiences and potential future needs. For each question, please provide a brief explanation of why it’s important. The goal is to gather insights that will help us improve the app and drive user engagement. Before we proceed, please ask any clarifying questions to ensure the survey aligns with our objectives and effectively targets our audience.”
How to Leverage the Response:
The AI-generated survey draft will provide a solid starting point, but it's essential to review each question carefully. Make sure the branching logic accurately reflects the different perspectives of existing users and potential customers. Also, consider the rationale provided for each question—this will help ensure that every question has a clear purpose and contributes to your overall goals. If needed, adjust the questions or add new ones to better align with your specific objectives. By taking the time to personalize and refine the survey, you can ensure that it effectively gathers the insights needed to enhance your photo-sharing app and boost user engagement.
Scenario 5: Assisting with competitive analysis
Scenario: As part of the discovery process, we identified that examining how competitors handle similar workflows would greatly aid in our ability to design a solution. This typically involves searching for relevant companies and applications, reviewing their workflows and design patterns, and assessing user sentiment around the overall product. However, this process can be time-consuming—starting with finding companies that are strong candidates for comparison and then researching the specific patterns they use.
Thoughts: In my experience, asking an AI assistant to support competitive research can save hours and uncover insights that might have otherwise gone unnoticed. However, it’s important to fact-check and explore each app more closely. Using tools like Mobbin in conjunction with your AI assistant can be a game changer. Below, I’ll share an example prompt of how I might interact with an AI assistant to get started with a scenario like the one above.
Prompt Example: “Can you help me identify five companies that might be good candidates for a competitive analysis? I’m working on creating a sharing/inviting team members feature within our infinite canvas workspace. I’m interested in understanding how they are solving for this specific design workflow. Also, please provide a link to customer reviews that I can read through.”
How to Leverage the Response: The AI-generated list of companies provides a solid starting point, but it’s crucial to dig deeper. Use tools like Mobbin to explore visual design patterns and see how they align with your own design challenges. Don’t hesitate to ask clarifying questions to understand why the AI provided certain data, just as you would with a human. This approach allows you to gather insights and inspirations that you can refine and adapt to your product’s needs. By combining AI research with hands-on exploration, you can uncover innovative solutions and streamline your discovery phase.
Embrace AI as a Design Ally
As we’ve explored, AI can be a powerful ally in your design process, helping you work smarter and more efficiently. But remember, while AI can provide valuable insights and streamline tasks, it’s your creativity and insight that will ultimately drive successful outcomes. Embrace AI as a tool that enhances your abilities, not replaces them.
I encourage you to explore AI tools and experiment with integrating them into your workflow. Whether you’re just starting out or looking to deepen your use of AI, remember that this is just the beginning. The potential of AI in design is still expanding, and by staying curious and adaptable, you can continue to leverage AI to push the boundaries of what’s possible in your work.
Cool Tech of the Week
Self-Adjusting Brain Pacemaker for Parkinson’s Disease
This week, the NIH highlighted a groundbreaking development in healthcare technology: a "brain pacemaker" using adaptive deep brain stimulation (aDBS) to help reduce Parkinson’s disease symptoms . This AI-powered device, was tested in a small NIH-funded trial, adjusts stimulation in real-time based on brain activity, offering a more personalized and potentially more effective treatment than conventional deep brain stimulation (DBS) methods .
Why It’s Cool: The aDBS system represents a significant leap forward in personalized medicine. Using machine learning algorithms, the device monitors brain signals and dynamically adjusts electrical stimulation to meet the patient’s immediate needs. This "closed-loop" technology creates a continuous feedback mechanism that can counteract symptoms as they arise, providing more precise management of Parkinson’s disease. Additionally, patients have the flexibility to switch out of the adaptive mode or turn off the treatment entirely with a handheld device, offering them greater control over their treatment.
Design Insights: This innovation is a powerful example of how AI can be leveraged to address complex, real-world challenges in healthcare. For designers, it opens up opportunities to ask critical questions: How do users interact with the device? What trends and data are most relevant for doctors? How is the data communicated, and how can it be made clearer to ensure continuous advancements? These are the types of considerations that can drive impactful design in specialized use cases like this, pushing the boundaries of what’s possible.
Read more about it:
Survey question answer
🥇 The IBM Simon: The First Smartphone That Paved the Way for Future Innovations
In 1994, the IBM Simon Personal Communicator made history as the world's first smartphone, a device that was truly ahead of its time. Designed by Frank J. Canova, a visionary designer and engineer at IBM, the Simon was a groundbreaking product that combined the functionalities of a mobile phone and a Personal Digital Assistant (PDA). What set the Simon apart was its touchscreen interface—a feature that would later become a standard in smartphones.
Design and Development: Frank J. Canova led the project with the goal of integrating communication and computing into a single handheld device. The Simon allowed users to make calls, send emails, manage contacts, and even run rudimentary apps, all through a touchscreen that could be operated with a stylus or a finger. This was a revolutionary concept in the early 1990s, setting the stage for the smartphones we use today.
Market Introduction and Consumer Access: The IBM Simon was officially released to the public in 1994, available exclusively in the United States through BellSouth Cellular. Priced at around $899 with a service contract (equivalent to roughly $1,600 today), it was positioned as a high-end device for business professionals. However, its high cost, limited availability, and a battery life of just about an hour restricted its appeal and accessibility to the broader consumer market.
Legacy and Influence: While the Simon was not a commercial success, selling only around 50,000 units, it laid the crucial groundwork for future smartphones. It demonstrated the potential of combining telephony with computing and showed that a single device could handle multiple communication tasks.
However, it wasn't until over a decade later that these ideas reached their full potential. Enter Apple, which took the foundational concepts introduced by the IBM Simon and revolutionized them with the release of the iPhone in 2007. Apple's innovation lay not only in the technology but in making it accessible and intuitive for the average consumer. The iPhone’s sleek design, user-friendly interface, and robust ecosystem of apps transformed the smartphone into an essential tool for daily life, far surpassing what IBM's Simon had started.
The IBM Simon might not have achieved widespread success, but its influence is undeniable. It was the first step in a journey that would eventually lead to the iPhone, a device that would define the smartphone era and change the way we interact with technology.
Thank you for reading today’s post!
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