in Blog

June 18, 2024

Generative AI in Product Development. How Does It Accelerate Innovations?

Author:




Artur Haponik

CEO & Co-Founder


Reading time:




11 minutes


The world is evolving at an alarming rate. New products and technologies are becoming obsolete almost as soon as they hit the shelf. At the center of all this are product design engineers, who have to keep up with the demand for better, more efficient products to satisfy the ever-changing market demands and customer preferences.

However, with the average simple product taking more than three months to design and create a working prototype, traditional methods of designing products just can’t cut it. [1]

The advent of Gen AI and its subsequent perforation into the manufacturing sector has come as a Hail Mary for product design and development specialists, who are leveraging generative AI’s impressive analytics and content creation capabilities to create new, innovative designs that cater to every need.

This guide will explore the role of generative AI in product development, with a focus on how it is enhancing the development of products and fostering innovation.

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Product development. How Generative AI accelerates innovations

According to a recent McKinsey report, Gen AI could unlock $60 billion in productivity. [2]Although the technology is still in its infancy, it has already shown great potential to revolutionize processes across various industries.

Take product development, for instance. Numerous engineers are using generative AI to explore new concepts and ideas, enabling them to not only redefine what’s already available but also develop previously unimagined ideas.

This has been made possible by specialized multimodal Gen AI models that can transform textual inputs into realistic visual displays of new design concepts. The ability to design concepts faster and visualize them earlier on in the design process enables manufacturers to get feedback from their consumers so they can fine-tune their designs to enhance user experience.

That said, despite their prowess in generating remarkable outputs, they cannot replace humans. So, in a way, Gen AI is just one among a huge list of product design methods geared toward streamlining the design process. Therefore, Gen AI cannot replace human engineers, just like computer-aided design (CAD), and augmented and virtual reality couldn’t replace the human element.

What it can do is aid in developing innovative designs and conducting consumer research. When properly leveraged, Gen AI could significantly reduce development cycle times, allowing teams that design products to focus on more crucial duties like optimizing designs for manufacturability and sustainability, which could ultimately lead to the development of better products.

Some of the most common applications of generative AI in product development include:

Reducing the cost of developing products

Sourcing and analyzing information are two of the costliest elements of developing a product. However, it is also important as it allows teams to figure out what the market needs, how to get it, and the cost of getting it.

Traditionally, this involved manually sifting through tons of information, which was often tedious and time-consuming. There was also the possibility of missing something important, leading to further time and monetary losses down the line.

Besides acting as a reliable source of information, generative AI can also comb through tons of data and provide useful analytics information. This significantly reduces the time and monetary requirements while bringing the product to market faster.

Transforming existing products

User feedback remains one of the biggest considerations in any product development endeavor. Everything from ratings, user interaction tracking and reinforcement learning enables AI tools to analyze user feedback and provide qualitative outcomes that drive future innovations.

These processes can also be used to refine existing products. For instance, by analyzing user feedback, product design specialists can effectively iterate new designs to existing products, thus improving the products’ functionality as well as user experience.

Take Airbus, for instance. The aeronautics company used GenAI to design a more efficient wingtip for one of its planes, resulting in a reduction in fuel consumption[3]. Similarly, Adidas, a fashion and sportswear brand, designed a lattice-like structure for its shoes by setting Gen AI parameters for structure, cost, and durability. Ultimately, the company was able to create a shoe that offers greater support and durability without negatively impacting manufacturing costs[4].

The benefits of Gen AI in improving current designs aren’t just limited to physical products. Software companies are also benefiting greatly, particularly when it comes to maintenance and software updates.

As the world becomes more digitized, customers have come to expect free software updates that ensure the products offer value, even as the market evolves. Software companies can utilize GenAI to produce custom, robust solutions to issues identified by analyzing customer feedback.

What’s even more impressive is that the process can happen in real-time. It can also be automated, freeing up software engineers’ time to focus on more humanistic elements of the software, thus making it more effective and competitive.

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Reducing time to market for new products

Before they can bring a product to market, design teams have to establish and keep a timeline. Unfortunately, most teams have a hard time keeping up with their set timelines due to unforeseen challenges and setbacks that have to be addressed before they can move forward.

GenAI allows engineers to examine a product from several standpoints, making it easier to identify and plan for potential challenges. One common approach is developing a project linearly, rather than developing a single prototype.

With several iterations of a product to work with, engineers can make different changes to several prototypes, enabling them to better understand which design works best.

Specialized GenAI models can also identify and address pitfalls by analyzing user feedback and cost calculations.

Ultimately, this can help bring products to market faster and cheaper compared to traditional trial-and-error methodologies used to identify product defects and pitfalls.

Enhancing creativity and productivity across the design lifecycle

The typical creative process used in creating concepts for designing new products must go through a few essential phases; user and market research, concept development, and finally, concept testing and refinement.

The analytics and generative capabilities of Gen AI make it an invaluable tool at each stage, enabling designers to identify bottlenecks and opportunities, replicate results faster, and enhance their creative thinking to create products that are not only usable but also have the potential to transform the users’ everyday experiences.

User and market research

Any company looking to release a successful product must start by conducting thorough market research. Everything from the qualities and features customers want in a product to how customers are responding to competitors’ products can significantly impact the potential success of a given product.

Gen AI models enable product designers to gather, analyze, and make sense of existing customer and market data, enabling them to identify untapped market opportunities and overlooked customer needs and expectations.

This way, engineers are better able to build a richer baseline of knowledge for consumer interviews and stakeholder discussions.

For instance, companies can augment their market and user research with new insights from generative AI tools to get a broader view of customer sentiment and how they can use their brand equity to expand into high-growth markets. This way, design teams are better able to broaden the scope of the ethnographic interviews and get feedback on important design elements that can be used to inform subsequent work, allowing them to develop new concepts and refine existing ones.

Concept development

Product designers and engineers are constantly creating new product designs or iterating on existing designs to improve them. The capability of Gen AI models, particularly multimodal models, to generate novel, life-like images based on prompts can provide a powerful medium for innovation and inspiration. This way, designers have a better chance of coming up with distinctive first-of-their-kind ideas.

What’s even more impressive is Gen AI can assist designers at every stage of the process. It doesn’t matter whether they’re looking for inspiration or working towards making an idea in their head into reality. With a few sketches or prompt ideas, gen AI can provide a good starting point, thus streamlining concept development.

That said, companies still need human product designers to validate, test, and refine the outputs to make them manufacturable, meaningful, and impactful. Therefore, GenAI works much like previous technological revolutions in design, such as 3D printing and CAD, which serve as tools to free up designers’ time from mundane, time-consuming tasks when preparing concepts.

Concept testing and refinement

Traditional concept testing and refinement typically revolved around creating working prototypes and testing their effectiveness. This led to significant time, monetary, and human-resource wastage, especially when a design needed multiple iterations before being put to market.

GenAI can help transform conceptual skins or designs into immersive visuals that can be scrutinized for errors and stakeholder negotiations.

For instance, museums could benefit from Gen AI by utilizing its image-generation capabilities to visualize and identify opportunities to increase accessibility. Similarly, designers can create, edit, and combine AI-generated content with supplementary visual content to create illustration storyboards showing novel formats, services, and products.

After demonstrating the concepts to stakeholders, product designers can utilize GenAI to refine the design, add final touches, and draw inspiration for future designs.

Read more: Generative AI and Knowledge Management

 

Examples of generative AI in product development

Any company that seeks to gain a competitive advantage must utilize every technological advantage at its disposal. The advent of GenAI and its subsequent mainstream utilization, particularly among content creators, has encouraged many companies to incorporate it into their development processes.

In that regard, several companies have already started testing out the technology in a bid to figure out the approaches that fit perfectly into their goals.

When properly leveraged, generative AI can capture consumer attention with innovative ideas and groundbreaking innovations that not only drive engagement but also boost sales.

Here are some of the most notable companies utilizing Generative AI in product development:

The Coca-Cola Company utilized Gen AI to create the flavor of the future

The Coca-Cola Company, known for its delicious flavors and engaging ad campaigns, utilized Gen AI to create Coca-Cola Y3000, a limited-edition flavor designed to understand how its fans envision the future through aspirations, emotions, flavors, colors, and more. [5]

To create the product, the company first collected data from its customers around the world, fed it into GenAI models to generate insights, and developed a new flavor purported to predict what the pallets of the future will enjoy. Essentially, Coca-Cola used Gen AI to predict the future – at least in terms of flavors and consumer preferences.

Estée Lauder  utilizes Gen AI to improve customer experience

Estée Lauder has recently partnered with Google Cloud to transform customer experiences online with generative AI [6]. The company hopes to leverage Gen AI-powered solutions to inform research and development (R&D), understand customer sentiment, and transform customer experience across its brand sites into top-of-the-line, high-touch digital experiences.

The company has also taken strides to increase investments into Gen AI after noticing how viral products on popular social media sites like TikTok drive customer taste in beauty and fashion.

FINESSE is utilizing Gen A to drive demand and sustainability

FINESSE, which has been dubbed the first AI-driven fashion house, is utilizing its proprietary specialized generative AI tools for clothing design. The company is also keeping its customers in the loop, particularly when it comes to determining what gets made and in what quantity.

Essentially, after its generative AI tools design a product, customers get to determine what comes into production through a voting process.

By combining AI with customer preferences, the company has effectively limited overproduction by prioritizing products with pre-established popularity while avoiding the not-so-popular designs.

Read more: Generative AI Strategy Is a Must-Have: How to Build It

Final thoughts

Gen AI has the potential to revolutionize every aspect of the manufacturing process, including designing a product and developing it. The technology’s impressive analytics and content generation capabilities make it particularly effective in fostering innovation and creativity.

Many companies are already utilizing generative AI to design new products, improve existing ones, and improve manufacturing processes, resulting in a boost in sustainability, engagement, and customer satisfaction.

As the technology continues to improve, and more companies jump on the GenAI bandwagon, we’re poised to see further developments in the manufacturing sector, including the release of innovative, never-thought-of-before products and processes.

References

[1] Mgtrading.com. How Long Does Product Design Take. URL: https://tiny.pl/dj575. Accessed on June 14, 2024
[2] Mckinsey.com. The Economic Potential of Generative AI in the Next Productivity Frontier. URL: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier. Accessed on June 14, 2024
[3]Airbus. com. How Airbus Uses Generative AI to Reinvent Itself. URL: https://www.airbus.com/en/newsroom/stories/2024-05-how-airbus-uses-generative-artificial-intelligence-to-reinvent-itself. Accessed on June 14, 2024
[4] Diva-portal.org. Development of VR facial interface using advantages of additive manufacturing. URL: https://www.diva-portal.org/smash/get/diva2:1599931/FULLTEXT01.pdf. Accessed on Jun 14, 2024
[5] Coca-colacompany.com. Coca-Cola® Creations Imagines Year 3000 With New Futuristic Flavor and AI-Powered Experience. URL:
https://www.coca-colacompany.com/media-center/coca-cola-creations-imagines-year-3000-futuristic-flavor-ai-powered-experience. Accessed on June 14, 2024
[6] Prnewswire.com. The Estée Lauder Companies Inc. and Google Cloud Partner to Transform the Online Consumer Experience with Generative AI. URL:
https://www.prnewswire.com/news-releases/the-estee-lauder-companies-inc-and-google-cloud-partner-to-transform-the-online-consumer-experience-with-generative-ai-301912131.html. Accessed on June 14, 2024



Category:


Generative AI