AI in product design
Introduction
As a product designer at Melio, I’ve been part of a remarkable journey. I witnessed our team’s hyper-growth from less than 40 to over 600 employees, exposing me to a fast-changing work and human dynamic. My journey has also exposed me to the full life cycle of payments and their challenges.
In this blog, I want to share how you can scale up your product design skills with AI, and how it became a game-changer in product design and research, providing a fresh perspective on the fintech industry. So, ready your screens, adjust your swivel chairs, and let’s navigate the AI landscape together!
The Role of AI in Product Design
Navigating the dynamic world of fintech product design presents a unique set of complexities. This is where AI steps in, revolutionizing the approach to these challenges.
AI Tools in Action:
- Chat GPT
This AI model has become an indispensable part of my design process. It streamlines the creation of a research itinerary, adeptly navigating the vast sea of data to pinpoint relevant information. It’s also a great tool to understand the world of finance and fintech in particular.
Various Figma Plugins
- WireGen — helped me get over the dreaded empty-page syndrome. Inputting the initial spec with some pointers does wonders.
- QoQo — an all-around tool to use for the whole UX process. Used the Chat function, but it has so many more capabilities I’ve yet to use.
- Various copy assistants — They guide the design process additionally, they increase the speed and quality of a wireframe. I use chat GPT a lot for that, but native Figma plugins are also common, and I have used some in the past.
These AI-powered tools are instrumental in processing the researched information and design process. They draw meaningful insights while respecting the boundaries of proprietary data, ensuring a balance between innovation and privacy. The efficiency of these AI tools allows for more focus on what truly matters — creative problem-solving and innovation.
Examples of AI in Action
Let’s explore some specific examples of how AI has been instrumental in my work.
Competition Research
One instance where Chat GPT proved invaluable was when I needed to surface a list of major competitors upon joining my current team. Chat GPT was able to sift through the vast amount of information available and provide a concise list of key players. This not only saved me time but also allowed me to focus my efforts on further inquiry into specific competitors.
Improvement to Existing Designs
Another example of GPT’s utility was when I was assessing a screen’s functionality. It assisted me in organizing an itinerary list of what currently existed on a particular screen and suggested where I could add new items. It also identified areas that were confusing or needed to be reduced in the hierarchy. This helped streamline the design process and improve the overall user experience.
However, it’s important to remember that the suggestions provided by Chat GPT are just that — suggestions. As a product designer, I have a fuller picture with more context of the product and feature, including considerations like development scope and how it works within the greater design and suite of features. While AI tools like GPT can provide valuable insights, they should be used as a guide rather than a definitive answer. The final decisions always rest on human judgment, taking into account a broader range of factors that AI is not currently aware of.
Thoughts on Design and AI
There have been rumors that generative AI, in particular, signals the end of UI and UX designers. However, I believe that it will simply help designers scale up. AI enables us to have a more significant impact and infuse more meaning into our designs. In more creative pursuits, it lowers the technical bar, allowing for advanced visuals and more intricate work.
Looking ahead, some designers may have their own public AI models, aiding them in their work, art, and design. Some might even create their own private models.
Companies might also develop their models, enabling designers and product managers to examine data and designs more freely, without worrying about security.
The familiarity and use of AI in product design is not just beneficial, but indeed critical to increase and refine your output, it certainly did mine. Soon, AI can also help us designers solve the increasingly complex work in Figma, like the work in variables, advanced prototypes, and design to code, etc.
Final thoughts.
Hopefully, the suggestions mentioned above will help you, especially if you’re a designer, or anyone curious about how to use AI in a product. I encourage you to use some of these tools, and share your experiences!
Don’t be afraid to try and use it in your field, the world of AI is vast, full of potential, and fast-growing. It’s waiting for you to explore.
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