Go to app
GuidesProduct development

Artificial intelligence is revolutionizing product design

Last updated

22 July 2023

Author

Dovetail Editorial Team

Reviewed by

Jean Kaluza

Working in a large organization with over 100+ employees? Discover how Dovetail can scale your ability to keep the customer at the center of every decision. Contact sales.

Artificial intelligence is quickly changing a wide range of business aspects and how target audiences interact. 

AI can also play a helpful role in assisting your product design team with creating new products your customers will love. 

Keep reading to learn how your business can use artificial intelligence tools to create the best products.

How are companies using AI in product design?

AI's capabilities are developing quickly, so artificial intelligence tools can support your business's product design team in many ways. 

AI can assist your business with: 

  • Generating new design ideas

  • Creating designs based on a particular customer's browsing or purchase patterns

  • Revolutionizing how your company collects and analyzes data 

  • Determining how a particular product design works in certain situations 

  • Understanding how a product interacts with other products

Each of these benefits can help you create products that provide a better customer experience

Pros and cons of AI in product design 

Understanding how AI can benefit and potentially negatively impact your product design is important in determining how to leverage it effectively. 

Pros

When you use AI correctly, it can be a helpful tool for your team's designers. They can develop new product design ideas and ways to use them. 

More importantly, your research team can leverage AI to assist in: 

Other benefits include:

Increased automation options 

Automating as many aspects of your product design process as possible frees up a significant amount of time, money, and resources. You can use these to advance other areas. 

This option can reduce the time your team needs to spend on tasks that an AI tool can manage just as well, which can stretch your limited resources. 

Improved personalization options

AI can collect real-time data and allows for better customization to design personalized experiences. 

This could result in products that more closely align with what your customers have in mind than your team might otherwise have been able to create. 

These tools can analyze a wide range of: 

  • Customer buying habits

  • Usage patterns

  • Past searches

  • Other behavior patterns

This allows you to more accurately determine what customers want from your products, so you can better match their preferences. 

Improved product usability 

Designing easy-to-use products is important in ensuring customers are satisfied with their purchases. It also increases the likelihood that they will become repeat customers. 

AI tools can help you design products that are a better fit for your customers. 

Cons 

While AI can be a helpful tool for assisting your design team, it has several limitations. These keep it from being an appropriate replacement for your human design team. 

It’s important to keep these points in mind when determining how to best incorporate AI into your product design strategy:

Limited creativity 

AI can only go so far when it comes to creating new designs. So far, it’s only capable of building pre-existing material that humans have taught it. 

Although these programs can use information that already exists in new ways, they cannot come up with new information like your team can. 

Also, good design should solve problems by thoroughly understanding them and human nature. In AI’s current state, it can’t create a complete solution without human intervention. 

Importance of data 

AI tools rely on the accuracy of human-taught data when it comes to forming conclusions about that information. 

When it uses data to generate new product designs, it will only provide the results you want if your data is correct. 

Flawed data may be: 

  • Incomplete 

  • Biased

  • Not cleaned properly

  • Incorrect

  • Irrelevant or inaccurate to your product’s audience

Similarly, AI data analysis is limited to what the algorithm is capable of. If we implement data and get an unexpected result, we need to know if the data analysis method is valid. 

With AI being such a new technology, it’s currently best to run Python and R scripts to do your analysis alongside AI to ensure accuracy.

What do your users really want?

Just upload your customer research and ask your insights hub - like magic.

Try magic search

How does AI play a role in product design?

Your business should not attempt to completely replace human product design with AI. Knowing how to effectively leverage it to support your design team's work can help you get the most out of both options. 

You can blend the speed and volume of content AI can produce with the human side of creating the best products for your customers by using AI to: 

  • Devise new design ideas

  • Determine whether designs work as effectively as you would like

  • Optimize your designs to focus heavily on certain areas

Find inspiration and generate ideas 

Creating fresh product ideas and designs is key to keeping your customers interested in your brand. 

Your team may not always be able to find the inspiration to create just what your customers want. 

Although you can’t copy a design that already exists, AI's easy access to millions of images and designs can give you a wide range of material to draw inspiration from during brainstorming

You can generate hundreds of possible design options at once and combine elements you like from multiple designs. Then, you can create a final product that will best meet the expectations and needs of your customers

Run simulations and QA test products

Including plenty of product testing before releasing any new product is an important step in ensuring it works how you expect. 

AI QA (quality assurance) simulations can make it easier to determine how various factors will function in a real-world environment. 

Your understanding of how certain concepts should work based on various data types may occasionally translate to how they work in real life. Using AI to test multiple versions of your products makes it easier to compare the results you obtain. 

You can use the simulation information to adjust how specific factors work and determine which combination of elements will likely provide the best product for your customers. 

Optimizing your processes 

AI can significantly simplify the process of product design. 

Tools like goRetro can generate user stories for teams and product managers rapidly. GPT Design can produce your product designs, leaving your team to focus on meeting specific guidelines. 

In addition, they can leverage AI’s rapid data analysis to ensure your designs always match your customers' preferences and the needs of your business. They can make your products as lightweight as possible and reduce costs. 

AI boasts tools like ABtesting that can show the higher-performing option between 2-3 solutions. 

AI product design stages

AI product design includes four stages that integrate it into a more complex workflow:

  1. Preparing data to ensure your AI tool has the information it needs

  2. AI modeling to further train your AI tool to understand your products and your business

  3. Running simulations to test how various product design options work

  4. Deploying your final product design decisions

Challenges associated with the traditional design process

While the traditional design process can provide a relatively high level of success in most situations, it has certain challenges. 

Some challenges include: 

  • Too little in-depth user research 

  • Too little collaboration

  • Difficulties incorporating and adjusting to non-linear design processes

  • Continuing to use ideas that do not work well

Correctly incorporating AI can alleviate these. 

Top AI applications for product design

Using the right AI tools is important to get the most out of them. Some of the top applications on the market include: 

  • Midjourney

  • Khroma

  • Pixso

  • Wix ADI

  • VanceAI

FAQs

Will AI take over product design? 

AI will almost certainly play a role in the evolution of product development.

However, any creative process that only uses artificial intelligence misses the human element that makes it possible to create fresh, new ideas. 

AI simply rehashes information humans have taught it. That means it is very unlikely to replace innovative human product design completely. 

It’s also currently unable to think for itself or solve complex problems. It also lacks the empathy to understand humans outside of tech. Plus, it doesn’t have the self-awareness to assert when its solutions may need adjustments and how and why those tweaks are necessary.

Instead, it will likely play a supporting role. Currently, it’s primarily handling simpler, automation-friendly areas, which can free up time for to spend on more complex elements.

What is the future of AI in product design? 

AI is likely to increase your business's options for offering highly personalized or custom products because it can generate variations faster than your human design team. 

It can also use a wide range of data about your customers' past purchases and other patterns to generate product designs that are an even better fit for their preferences. 

How can machine learning lead to better product design?

Machine learning uses algorithms to quickly and efficiently organize and analyze a significant amount of data. That can help you learn more about your customers' typical behavior patterns. 

It’s a great way to help your company develop more innovative products for your customers. 

Should you be using a customer insights hub?

Do you want to discover previous interviews faster?

Do you share your interview findings with others?

Do you interview customers?

Start for free today, add your research, and get to key insights faster

Get Dovetail free

Editor’s picks

How to use product pricing strategies to maximize revenue

Last updated: 17 October 2024

An introduction to the Shape Up Method

Last updated: 29 October 2024

Creating an effective outcome-based roadmap

Last updated: 24 October 2024

Stakeholder interview template

Last updated: 13 May 2024

Product feedback templates

Last updated: 13 May 2024

How AI can transform product management

Last updated: 10 August 2023

Related topics

Product developmentMarket researchPatient experienceCustomer researchResearch methodsEmployee experienceSurveysUser experience (UX)

A whole new way to understand your customer is here

Get Dovetail free

Product

PlatformProjectsChannelsAsk DovetailRecruitIntegrationsEnterpriseMagicAnalysisInsightsPricingRoadmap

Company

About us
Careers11
Legal
© Dovetail Research Pty. Ltd.
TermsPrivacy Policy

Product

PlatformProjectsChannelsAsk DovetailRecruitIntegrationsEnterpriseMagicAnalysisInsightsPricingRoadmap

Company

About us
Careers11
Legal
© Dovetail Research Pty. Ltd.
TermsPrivacy Policy

Log in or sign up

Get started for free


or


By clicking “Continue with Google / Email” you agree to our User Terms of Service and Privacy Policy