We here at PI Apparel are launching our first-ever footwear-specific event next March in Portland, aptly named Stride 2025. To ensure we deliver an agenda that is topical and valuable, I spoke with designers, product developers and digital champions from 25+ of the world’s leading footwear brands and asked them: ‘what are your main challenges and priorities for the immediate future?’
The overarching themes were revealed pretty quickly: Digital Product Creation (DPC), AI, Maturing Technologies (xR, 3D Printing, 3D Scanning, Virtual Try-on and more) and finally, Local Production & Sustainability.
Missed Part 1 on DPC? Worry not, you can access it here.
With the Stride 2025 agenda now live, I wanted to share some of these insights with you. In Part 2 of this series I share ‘The Top 10 Themes Shaping the Use of AI in Footwear Creation’.
1. Challenges in AI Adoption Remain High for Footwear.
Despite AI’s promise, the footwear community often prefer traditional methods, valuing physical samples and handcrafted elements over digital inputs. Concerns around loss of control, cost, and complexity also contribute to resistance. How can the industry overcome these barriers to unlock AI’s potential across all market segments?
2. AI as a Creative Tool Expands Designer Capabilities.
AI has emerged as a creative design tool, moving beyond trend analysis and rapid prototyping to actively inspire designers. The debate over AI inputs versus outputs highlights the need for high-quality data to achieve brand-relevant, business-focused results. But how can designers best balance AI’s creative input with human intuition?
3. AI Investment Lacks a Central Owner and Strategy.
Everyone, to some degree, has started playing around with AI. But to date, as we’ve seen with other major technologies in the past, this experimentation is being conducted in siloes and without an overarching strategy. With this field evolving so fast, is it time to implement a more formal and holistic owner and framework to ensure a proactive approach to successful adoption?
4. AI Needs to be Integrated into the Existing Digital Ecosystem.
AI promises to be another disruptive and impactful tool in a brand’s arsenal. But for maximum success, we need to ensure that it is integrated with existing tools and workflows, such as 3D and PLM. How can we begin to plan for its seamless integration into the digital ecosystem already in place?
5. AI in Rapid Prototyping Accelerates Design Cycles.
AI supports rapid prototyping by creating digital models quickly and minimizing the need for physical samples in certain construction methods. This technology provides real-time feedback, improving product quality and speeding up design iterations. How can companies best leverage AI to make the prototyping process even faster and more precise?
6. AI & Digital Twins Streamline Production.
With AI enhancing digital twin accuracy, digital models now more closely represent physical products, enabling smoother manufacturing and faster development cycles. By integrating AI with digital twins, companies can achieve streamlined processes from design to delivery. But what are the most effective ways to ensure digital twins evolve alongside product complexity?
7. AI in Material Scanning and Digital Fabric Processes Elevates Sustainability.
AI enhances material scanning and allows designers to evaluate materials digitally, reducing reliance on physical samples. This also improves the accuracy of digital fabric representations, fostering more sustainable and efficient material use. But what additional capabilities are needed to make digital material processes mainstream, and who should own this?
8. AI-Driven Design & Market Trend Forecasting Enhances Proactive Design Decisions.
AI is playing a significant role in design inspiration and market trend forecasting by scraping websites and generating structured data. This technology allows brands to anticipate market trends and consumer behaviors, empowering them to make proactive design and production decisions. But how can brands maximize AI’s full potential to stay ahead of the curve?
9. AI Integration Can Simplify Personalized Design & Customized Products & Experiences.
AI-powered customization tools streamline the personalization process, enabling consumers to design shoes tailored to their preferences with ease. Moreover, by using consumer data, AI can create personas, recommend existing products and tailor the shopping experience on the individual level. What are the most effective ways to integrate AI-driven customization without compromising brand identity?
10. AI Can Optimize the Supply Chain, Reducing Waste & Improving Efficiency.
AI-driven analytics optimize supply chain logistics, helping reduce overproduction and improve inventory management through real-time insights into demand and capacity planning. This can lead to significant sustainability improvements across the supply chain. How can brands further leverage AI for real-time supply chain adjustments?