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From idea to action: How AI is changing the way innovation happens
The challenge now lies in how quickly ideas can be turned into something that works[SINGAPORE] For a long time, innovation followed a familiar path. You define a problem, study it carefully, develop a solution, test it, and only then bring it into the real world.It was a process that took years.But that model is starting to break. Research itself has also changed; it no longer takes years to move from idea to outcome.Today, artificial intelligence (AI) can search, analyse and generate information almost instantly. The challenge is no longer access to knowledge; it is what you do with it – how quickly you can turn an idea into something that actually works.In other words, the bottleneck no longer lies in thinking, but in doing.We are reaching a turning point where the gap between thinking and doing is narrowing fast. The organisations that move ahead not only analyse well, but can also build, test and adapt quickly in real-world settings.DECODING ASIANavigate Asia ina new global orderGet the insights delivered to your inbox.Practical applicationOne clear response to this change is the rise of fast, hands-on problem-solving done together with industry.Platforms such as the Design AI Fab Lab at the Singapore University of Technology and Design show how this works in practice.Instead of working on case studies, student teams work directly with companies on real problems, from process inefficiencies to system improvements. These provide live challenges with real consequences.SEE ALSOMoreStudents are involved from the start, helping to define the problem, explore solutions and build prototypes that can be tested quickly.What stands out is the speed. Ideas move quickly into prototypes. AI tools help teams explore options, test ideas and refine solutions much faster than before. What used to take months now takes mere weeks.The result is a different way of working: more practical, collaborative, and grounded in real conditions from the start. Students are not sitting on the sidelines; they are part of the delivery.This is real-world problem-solving happening from the start. It also reflects a broader Design AI approach, where design, AI and domain knowledge come together to move quickly from problem to solution. Known as trilingualism, this is essential for the new world.From tools to systemsWhat this looks like in practice can be seen in how industries such as architecture and engineering are beginning to work differently.Traditionally, architectural design has b...
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