Technology often evolves too quickly for us to fully integrate it into our daily lives. Take Photoshop, MP3s, and wearables, for example — each took years to become ubiquitous and transform their industries.
I never imagined, as a twelve-year-old, that one day I could ask a speaker to play any song instantly. I still remember the thrill of going to a carnival and paying for a magazine photo booth to put me on the cover of Time or watching Star Trek episodes where people would talk into their watches to communicate with others.
As these innovations were embraced, they revolutionized everyday tasks. This is happening now in the design world, as seen with reactions to Figma’s Config Event. The introduction of advanced collaboration tools, AI features, and Figma Slides sparked both excitement and concern among designers, who are questioning their evolving roles.
"Why hire a designer when you can just type a prompt?" some asked. But designers are far more than "mock monkeys." Although fears of obsolescence are premature, the challenge is clear: designers must adapt, using AI and new technologies to meet user needs and optimize the creative process. Let’s spend more time ideating and less time pixelating! As AI continues to advance, the key will be not resisting change, but mastering it, as those who embrace AI will shape the future of design.
Reimagining the Design Process
Design starts with understanding a domain and its users, aligning business goals with user needs, ideating and testing, gathering feedback, iterating, and defining a direction for an MVP. This involves partnering closely with product and development teams to align on the approach and ensure the team is focused on the right goals. It’s also critical to understand the constraints, both from a technical and resource standpoint.
Any good team relies on a central repository of information — one place that hosts all key documents and logs each decision along the way. Often this is a combination of tools such as Jira, Google Workspace, Figma directories, and Slack channels.
According to a Gardner study:
47% of digital workers struggled to find the information they needed to effectively perform their jobs.
32% of employees made the wrong decision due to a lack of awareness.
Companies have been trying for years to win this market, but none have managed to effectively capture all of that knowledge in one easy-to-use solution. So, instead of a technical solution, teams have relied on that one individual with all that useful knowledge in their head. But this can stop a project dead in its tracks if that person is out of office or leaves the company.
The true opportunity of generative AI lies with its capacity to serve as the central repository of information for a team and its ability to generate new ideas from that information with a single prompt. It can help the team accelerate its work and optimize its output.
The integration of AI into the design process isn’t just about enhancing collaboration or centralizing information; it’s also reshaping how quickly teams can move from ideation to execution. With tools that streamline information sharing and idea generation, designers can reduce the time spent on repetitive tasks and focus on creating impactful solutions faster. This efficiency is particularly evident in accelerated design sprints.
The Accelerated Design Sprint
No two projects are the same, and domain complexity differs. So, I won’t pretend that any project can be designed in a few days. But it is possible. The key is having access to users and an understanding of business goals. If you have both, you may be on your way to a fast MVP prototype that can further refine your understanding of your problem space and set you up with a strong foundation for success.
1. Create an AI partner to serve as your knowledge base and accelerator.
Leverage generative AI to create a virtual partner — an expert in the given domain with access to project documents and research artifacts. This AI partner, securely stored in platforms like ChatGPT Teams, serves as an always-on project expert. It can provide competitive summaries, general domain knowledge, draft copy, ideate, and consolidate insights. This AI becomes the project's central hub, evolving as new artifacts are uploaded. The team drives the process forward, and the AI partner executes key tasks required to effectively build or enhance a new product.
Sample Prompt: “You are an expert in designing easy-to-use apps that help consumers find services. You are also an expert in the field of walking all sorts of dogs. Leverage that knowledge to help me design and build an app for consumers to find dog walkers in their neighborhood.”
If you have any existing documents regarding the project, be sure to upload them to the GPT.
2. Use AI to help you get insights from real users.
Although AI provides a strong starting point for common domains, it can’t replace real user insights. Leverage your AI partner to write a survey to better understand your user base and their current pain points.
Sample Prompt: “Write a short survey to help me better understand the needs of those requesting services from a dog-walking app and also include questions to capture demographic data.”
Use online platforms like Lyssna to run surveys targeting specific user segments. Often, you can get results within a few hours, depending on your screening criteria.
3. Leverage rapid feedback and prototyping to refine your AI partner.
Once survey results are in, upload the data to your AI partner. Request a summary of the insights in a few bullet points. Share the results with the team and review the raw data for a deeper understanding.
Now it’s time for some AI brainstorming. Prompt your AI partner with something like:
Sample Prompt: “Based on these insights, recommend a series of features for this app. Think big and be imaginative. Right now, there are no technical or resource constraints.”
Once you have a feature list, consider your technical and resource constraints. Dot vote on which three features are feasible and potentially most impactful. Then, get the AI partner’s sentiment with a prompt like this one:
Sample Prompt: “Now, assuming we have limited time and resources, which three features would best be suited for an MVP version of this product?”
You now have a robust foundation for team ideation. Collaborate on brainstorming sessions, inviting AI to contribute design ideas. Use tools like Uizard and Figma features. Ensure cross-functional team members provide input in order to diversify perspectives and bring the entire team on board at the very beginning of the design process.
4. Conduct user testing and iterate to find the best solution.
Vote as a team on the designs that fit within the constraints you have, to address user concerns, and align with business needs. Prototype a few of them leveraging tools like Uizard and Figma . Run some remote usability tests and surveys using Zoom and services like Lyssna. By the end of the day, you should have a good sense of which solution is working best.
Iterate on designs and conduct further testing.
5. Finalize your initial design.
Solidify your direction, uploading flows into the AI partner. Now, after the design direction is decided, you can work with your product manager to generate a draft product requirements document (PRD) with clear metrics and feature descriptions.
Sample Prompt: “Now create a comprehensive product requirements document, considering these high-priority features, relevant success metrics, and detailed use cases.”
This document won’t be perfect, but it will be a starting point. You can also tweak the prompt to refine certain sections if required.
Finally, you can ask your AI partner to recommend a branding approach for your app.
Sample Prompt: “Please recommend a branding approach, including colors and ideas for logo design.”
If you are feeling adventurous, you can then have it create a logo using these ideas.
Sample Prompt: “Please create a logo using these recommendations”
Conclusion
In conclusion, as we navigate this rapidly evolving landscape where AI is an integral part of the design process, it's clear that our roles as designers, researchers, and innovators are not replaced, but rather redefined.
By embracing AI as a partner, we can enhance our creative capabilities, streamline workflows, and focus on what truly matters — delivering exceptional user experiences.
The future of design lies not in resisting these technological advancements, but in mastering them to better serve our users and clients. As we continue to adapt, the possibilities for innovation are endless, and the role of the designer will be more crucial than ever in guiding the intersection of technology and human-centered design.
For a number of AI resources, take a look at our AI Resource Hub.
