In this article, I discuss why design serves as an excellent example of a profession that defines how AI can assist designers by allowing them to produce superior designs with greater efficiency, rather than supplanting the essential skills that proficient designers contribute to their field. I show how AI can make the future of design more exciting and promising as the technology continues to evolve and enable designers to do more. In the process, AI will enable designers to focus on developing the design skills that matter, namely those anchored deeply in design thinking, empathy and user research.  

In this case study, we examine a team that has recognized the potential of Machine Learning (ML) and Artificial Intelligence (AI) to refine and enhance a longstanding methodology for forecasting product order volumes. By leveraging AI and ML, the team can achieve more precise ordering based on those forecasts, while also gaining the capability to monitor market prices and receive insights on how to adjust orders to minimize costs. Historically, this team has relied on Excel for manual and meticulous user input, maintaining continuous communication among members and adhering to a process honed over several decades. While this approach has been effective, they have now realized that integrating AI and ML can significantly enhance their workflow by handling larger datasets at a faster pace and generating profound insights aimed at maximizing efficiency, reducing costs, and driving business growth.  

The rapid integration of Artificial Intelligence (AI) and Machine Learning (ML) capabilities into products and applications necessitates a shift in the role of Product Designers.

AI offers significant opportunities for organizations to address complex business problems. Users are now able to provide input into detailed data models that can process extensive datasets and generate insights through what-if scenarios and simulations.

AI-driven scenarios and simulations often rely on substantial input data and calibration tailored to user needs. As output complexity increases, it becomes essential for Product Designers to be at the forefront, understanding these sophisticated models and shaping designs that present the results in an intuitive, user-friendly way.

Consequently, Product Designers must move beyond translating requirements into mock-ups and they must instead lead the vision for how human-interactive design can refine data input, guide calibration, and surface outputs that make AI models more actionable and aligned with business objectives. In this article, I’ll explore the following key areas and what’s needed to succeed:

• Adopt a Product Owner’s Mindset

• Design with Clarity and Logic

• Lead with a Hybrid Mindset

• Growing into the Role