Turning AI Visions into Real-World Products: A Behind-the-Scenes Look

Turning AI Visions into Real-World Products: A Behind-the-Scenes Look
By Peter Ragonetti

Artificial Intelligence (AI) is transforming industries at an unprecedented rate, and product design is no exception. At Pratt Institute, a frequent discussion revolves around how AI is shaping creative professions and whether it should be integrated into design education. While AI excels at visualization, it often falls short in the deeper, iterative stages of the design process.

Rather than debating AI’s role in design, I see it as a tool—similar to how Photoshop revolutionized communication design, AutoCAD changed architecture, and engineering software redefined product design. These tools digitized manual processes, making them more efficient. The same applies to AI, which can be a powerful asset in product development when used correctly.

In my professional studio practice, I assist large companies, startups, and solopreneurs in bringing their ideas from concept to mass production. Through this work, I have witnessed AI’s growing impact firsthand. The following two case studies illustrate how AI-generated images served as the starting point for real, market-ready products.

CASE STUDY 1: Toyota Tacoma Dog Toy

In April 2023, an executive producer from Saatchi & Saatchi approached me with a unique project: creating an indestructible rubber dog toy shaped like the 2024 Toyota Tacoma pickup truck. The idea was pitched to Toyota as a promotional item, with an AI-generated image serving as the initial concept. The challenge was translating this digital visualization into a functional, manufacturable product.

(Insert AI-generated concept image here)

With years of experience designing pet toys and automotive-inspired items, I was confident in our ability to bring this concept to life. Once we received project approval, my team developed CAD models to ensure proper proportions and manufacturability. We worked closely with the Saatchi & Saatchi creative team, sketching multiple variations before settling on a design that closely resembled the original AI-generated image.

(Insert CAD model and design sketches here)

Engineering the toy required careful material selection, adjusting wall thickness for mold feasibility, and ensuring the design could withstand rigorous use. A 3D-printed prototype was produced to validate the final form, and we also developed custom packaging to enhance its retail appeal.

(Insert photo of 3D-printed prototype here)

Manufacturing rubber toys is a nuanced process, often requiring compression molding—where rubber slabs are pressed into metal molds and cooled to set their shape. At the client’s request, we sourced a U.S.-based manufacturer capable of delivering high-quality production on a tight schedule. Once the molds were created and sample units approved, we moved into mass production, ultimately delivering nearly 10,000 units.

(Insert photos of rubber molding and production process here)

Because of strict deadlines, we worked on both design refinement and vendor sourcing simultaneously. The entire process—from initial approval in April to final product delivery in August—took just four months, an incredibly fast turnaround for a new product. By leveraging AI-generated imagery, we reduced time spent on concept development and focused on engineering and execution. The result? A commercially successful product that won third place at the Cannes Lions Festival, highlighting its impact in the industry.

(Insert final product image and Cannes award photo here)

CASE STUDY 2: Halo Top Pint Pack

A month later, in May 2023, I was approached by Observatory, a creative agency developing promotional opportunities for Halo Top Ice Cream. Their idea was bold: a luxury crossbody leather bag designed as a pint-sized ice cream cooler. The concept was initially presented as an AI-generated image featuring quilted leather, embossed branding, and an elegant strap. The real challenge was turning this concept into 100 production-ready units by August.

(Insert AI-generated bag concept image here)

Recognizing the complexity of this project, I collaborated with Rebeccah, a professor and owner of Interwoven, a company specializing in soft goods. We analyzed the AI-generated concept and worked closely with the client to refine the design. Given the tight one-month timeline, we had to make key design decisions quickly. While some luxury details were not feasible within our constraints, we successfully integrated key elements such as an adjustable-length strap, a built-in spoon holder, and a 3D-printed gold-plated lid that mimicked Halo Top’s signature pint container.

(Insert prototype sample photos here)

Unlike previous projects I had worked on, handbags required a different production approach. Fortunately, I had an established relationship with ZenPack, a trusted supplier, who confirmed they could produce 150 units within the required timeframe. However, sourcing additional components was necessary. The pint-sized ice cream coolers had to be procured separately, requiring sample testing and branding adjustments. The gold-plated 3D-printed lids were manufactured by a U.S.-based company, while the spoons were sourced from a major retailer.

(Insert photos of 3D-printed lid and sourced cooler component here)

At the same time, we developed photorealistic renderings for an e-commerce website, allowing Halo Top to market the product ahead of its official release.

(Insert photorealistic renderings here)

By mid-July, production was in full swing, and by September, the finished units had been shipped to customers.

The Halo Top Pint Pack launched on National Ice Cream Day and sold out in under one minute. The overwhelming demand led to resale listings on eBay at significantly higher prices than the original $79.99 retail price, demonstrating its strong market appeal and the effectiveness of AI in visualizing high-impact promotional products.

(Insert final production photo and product packaging here)

Summation

These two case studies highlight how AI-generated visuals can accelerate product approval and streamline development. By providing detailed, high-quality imagery early in the process, teams can quickly align on design direction, reducing the time spent on initial ideation.

However, while AI is a powerful tool for visualization, it does not replace essential product development skills such as engineering, material selection, and supplier coordination. These examples demonstrate how AI can enhance efficiency, but human expertise remains indispensable in transforming digital concepts into mass-produced reality.

As AI continues to evolve, its role in product design will only expand. The key is knowing how to use it effectively while maintaining the craftsmanship and technical know-how required for successful production.

What are your thoughts on AI’s role in product development? Have you used AI-generated concepts in your own work? Let’s discuss in the comments!