Originally published September 16, 2024

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.

As a kid, I remember the thrill of going to a carnival and paying for a magazine photo booth to put me on the cover of Time, or how captivated I was watching Star Trek episodes where people talked into their watches to communicate with others. I never imagined one day I’d be able to ask a speaker to play any song instantly.

As people embraced these innovations, they revolutionized everyday tasks. This is happening in the design world today, as seen with reactions to Figma’s Config Event. The new collaboration tools, AI features, and Figma Slides have both excited and worried designers.

After all, why would you hire a designer when you can just type a prompt?

Though I see the cause for alarm, fear that designers are becoming outdated is premature. But the challenge is clear. Designers need to adapt. They must use new technologies, particularly AI, to meet evolving user needs and ultimately improve the creative process. Those who are integrating AI are seeing their output increase by 60%.

The reality is that AI will shape the future of design. Those who learn to leverage AI effectively will be able to reimagine the design process. 

Reimagining the Design Process

Design starts with understanding a domain and its users, and aligning business goals with those users’ needs.

Then, it involves brainstorming and testing ideas. Gathering feedback is important, as is making changes based on that feedback.

Finally, it helps define a direction for a Minimum Viable Product (MVP). Determining the direction of your MVP requires partnering closely with product and development teams to align on the approach, and ensure the team focuses on the right goals. Understanding the constraints from a technical and resource standpoint is also critical.

But goal alignment isn’t the final step; you need to ensure continuous collaboration throughout the entire project. This points to the need for a central repository of information — one place that hosts all key documents and logs each decision along the way. Teams often accomplish this through tools such as Jira, Google Workspace, Figma directories, and Slack channels.

A Gartner study showed the importance of having one central place for information. It found that 47% of digital workers had trouble finding the needed information. Additionally, 32% of employees made wrong decisions because of a lack of awareness.

Perhaps an exciting shift is the role that AI can play in design; it’s not just about the prompt for the visual, but also how to ensure teams work together. This means no longer relying on one person to hold all the essential knowledge in their head, something that can stop a project dead in its tracks if that person is out of the office or leaves the company.

The real opportunity of generative AI is its ability to be a team's primary source of information. With just one prompt, it can create new ideas from that information, helping the team accelerate its work and optimize its output.

Integrating AI in design isn’t just about better teamwork or organizing information; it’s also reshaping how quickly teams can move from ideation to execution.

Designers can use tools that make sharing information and generating ideas easier, which helps them spend less time on repetitive tasks. They can then focus on creating effective solutions more quickly. This efficiency is particularly evident in accelerated design sprints.

The Accelerated Design Sprint

An accelerated design sprint uses the main ideas of a regular design sprint, but shortens the timeline even further. This allows teams to quickly create and test ideas for a new product or feature in days, or hours. The sprint focuses on key decisions and simplifies activities.

However, no two projects are the same, and domain complexity differs. Designers cannot complete every project in just 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.

Designers can leverage AI in the design sprint in these steps:

1. Create an AI partner to serve as your knowledge base and accelerator.

Leverage AI to create a virtual partner. Your AI partner, securely stored in platforms like ChatGPT Teams, serves as an always-on project expert and will have access to project documents and research materials. It can provide competitive summaries, general domain knowledge, draft copy, ideate, and consolidate insights.

This AI becomes the project's central hub, and evolves as the team uploads new artifacts. The team moves the process ahead while the AI partner handles essential tasks, helping to build or improve 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, upload them with your prompt to ensure information shared leverages important context.

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. Depending on your screening criteria, you can often get results within a few hours.

3. Leverage rapid feedback and prototyping to refine your AI partner.

Equipped with survey results, upload the data to your AI partner. Request a summary of the insights in a few bullet points, and share the results with the team. Be sure to review the raw data for a deeper understanding, as well.

Run a brainstorm with your team and generate some ideas. Then augment that with 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.

4. Conduct user testing and iterate to find the best solution.

Collaborate on brainstorming sessions, inviting AI to contribute design ideas. Team members from different functions should give their input, which will help generate new ideas and ensure everyone is on the same page from the start of the design process.

Vote as a team on the designs that fit within the constraints you have to address user concerns and that align with business needs. Prototype a few of them, leveraging Uizard and Figma, then run some remote usability tests and surveys using Zoom and services like Lyssna. Iterate on designs and conduct further testing.

By the end of the day, you should have a good sense of which solution is working best.

5. Finalize your initial design.

Solidify your direction by uploading flows into the AI partner. After the design direction is decided, you can work with your product manager to generate a draft product requirements document. This document should include 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. If necessary, you can also tweak the prompt to refine certain sections.

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”

AI is Design’s Future

Our roles as designers won’t be replaced with AI, but it will be important to understand how to best leverage AI as a partner in the design process. Mastering AI to better serve our users and clients is essential. By embracing AI as a partner, we can enhance our creative capabilities, streamline workflows, and focus on what truly matters: providing exceptional user experiences.

As we adapt, the possibilities for innovation are endless. The role of designer will be more critical than ever. They will guide the intersection of technology and human-centered design.

Looking for even more ways to leverage AI? Check out our AI resource hub to find out how AI can bolster your business.