The #1 AI hack? Just do it
Our CEO Patrick Vanbrabandt recently came back really energized, from a Nexxworks’ tour in Munich, where he visited some of the most successful AI pioneers in the world. Unsurprisingly, many companies today are heavily experimenting with AI because we may very well be on the cusp of a paradigm change.
But on the other hand, as the Nexxworks tour guide Peter Hinssen explained: we also should be prepared to be “underwhelmed” a lot. Despite, for instance, all that talk about AI having the potential to enhance performance by 30%, we are still a long way from that today. AI has an incredible potential, yet at the same time a lot of the current capabilities are overhyped.
But in such a fast-evolving environment full of potential, the worst thing to do would be to just wait it out until the technology is fully developed. The most successful companies out there tend to test emerging technologies to find out what they could mean for their companies, even if the tech is not yet fully mature. Why? Because that will help them move fast, once the tech is ready to be scaled qualitatively.
Take the example of BMW, for instance, where innovation runs through the entire DNA of the organization. They are continuously experimenting with new technologies, certainly in the case of AI. They use Generative AI in their website pictures, they are experimenting with online avatars to assist customers with finding the right car and they have a test project with humanoid Figure robots in their Spartanburg plant. For now, these experiments are mostly about showcasing how dedicated they are to innovation, but the learning that flows from these ventures for future endeavors is just as important.
Actually, Alexander Buresh SVP of the BMW group IT is truly convinced that “within five years every process in the BMW Group’s value chain will be supported by artificial intelligence”. So that’s why they are so heavily investing in AI.
One of the most important aspects of these types of emerging tech experiments are the employees, according to Patrick. Find those dynamic young people in your organization that like to experiment and that are a lot savvier with new tech and then empower them to experiment. And hire new people if you lack these capabilities. Most importantly, realize that the friction to implement AI in your organization will be big, so start with smaller scale experiments to test out the water.
But in such a fast-evolving environment full of potential, the worst thing to do would be to just wait it out until the technology is fully developed. The most successful companies out there tend to test emerging technologies to find out what they could mean for their companies, even if the tech is not yet fully mature. Why? Because that will help them move fast, once the tech is ready to be scaled qualitatively.
Take the example of BMW, for instance, where innovation runs through the entire DNA of the organization. They are continuously experimenting with new technologies, certainly in the case of AI. They use Generative AI in their website pictures, they are experimenting with online avatars to assist customers with finding the right car and they have a test project with humanoid Figure robots in their Spartanburg plant. For now, these experiments are mostly about showcasing how dedicated they are to innovation, but the learning that flows from these ventures for future endeavors is just as important.
Actually, Alexander Buresh SVP of the BMW group IT is truly convinced that “within five years every process in the BMW Group’s value chain will be supported by artificial intelligence”. So that’s why they are so heavily investing in AI.
One of the most important aspects of these types of emerging tech experiments are the employees, according to Patrick. Find those dynamic young people in your organization that like to experiment and that are a lot savvier with new tech and then empower them to experiment. And hire new people if you lack these capabilities. Most importantly, realize that the friction to implement AI in your organization will be big, so start with smaller scale experiments to test out the water.
