AI‑Empowered Design Thinking for Hong Kong Manufacturers

The seminar “AI‑empowered Design Thinking: Manufacturing Excellence and Digitalisation” was organised by Hong Kong Productivity Council (HKPC) and supported by InnoEdge Consulting on 2 March 2026 at the HKPC Building, Kowloon. Conducted in Cantonese, it attracted distributors, manufacturers, and local representatives seeking new ways to upgrade their businesses.

The seminar on how AI‑empowered design thinking provides a structured, human‑centred and data‑driven approach to innovation. Through presentations and interactive exchanges, participants explored how this integrated framework can help Hong Kong manufacturers enhance competitiveness, accelerate digital transformation and respond more effectively to evolving customer and market demands.


Aligning Manufacturing Excellence with New Industrialisation

The event began with a welcome speech by Ir Patrick Tham, Consultant, Mechatronics Engineering, Advanced Industries Development, New Industrialisation Division, HKPC. He outlined how new industrialisation and smart manufacturing are reshaping global value chains, and why Hong Kong manufacturers must pursue manufacturing excellence to stay relevant. Ir Tham highlighted HKPC’s role in supporting enterprises through technology adoption, process re‑engineering and industry collaboration.

By connecting AI‑empowered design thinking with broader policy directions and market trends, his sharing set the strategic context for how manufacturers can systematically upgrade productivity, quality and innovation capabilities in a rapidly changing environment.


Applying Design Thinking to Smart Manufacturing and Digitalisation

Mr. Paul Lee, Senior Partner at InnoEdge Consulting, translated design thinking into practical applications for manufacturing and digitalisation projects. He explained how empathising with end‑users and frontline staff can uncover root causes of operational issues, and how reframing these problems often leads to more strategic solutions.

Participants learned a step‑by‑step approach to ideation, rapid prototyping and testing, tailored to factory and supply‑chain contexts. Mr Lee also demonstrated how design thinking helps manufacturers avoid “technology for technology’s sake” by ensuring that digital initiatives are driven by user needs, business value and measurable impact on quality, cost and delivery performance.


Integrating AI into Design Thinking for Manufacturing Innovation

In the AI‑focused session, Mr. Paul Lee and Mr. Kenny Kong, Co‑Founder of Kool Limited, showed how advanced technologies can strengthen each stage of the design thinking cycle. Using an international manufacturing case study, they illustrated how AI tools can analyse large volumes of customer and production data, generate alternative concepts, simulate production scenarios and support evidence‑based decision making.

The speakers shared practical, scalable approaches suitable for both large manufacturers and SMEs. The case demonstrated that when AI insights are combined with human creativity and domain expertise, organisations can achieve faster innovation cycles, higher product quality and more resilient operations.


From Insight to Action: HKPC Support and Industry Takeaways

To turn ideas into action, Ir Patrick Tham introduced HKPC’s comprehensive support for AI‑empowered design thinking and digitalisation in manufacturing. This includes consultancy services, pilot projects, technology trials and professional training programmes tailored to different stages of transformation.

During the closing Q&A, participants discussed real‑life challenges such as resource constraints, change management and data readiness. The dialogue reinforced a clear message: achieving manufacturing excellence now requires a blend of human‑centred design, AI capabilities and continuous learning. InnoEdge and HKPC will continue partnering with industry stakeholders to co‑create practical roadmaps for digital, innovative and globally competitive manufacturing in Hong Kong.


Official Seminar Poster