AI is being investigated by many participants in the manufacturing sector, both large and small companies. However, only large companies like Siemens, FANUC, some major robotics companies, and larger automotive and aerospace firms, as well as pharmaceutical companies, can afford to implement AI meaningfully. AI is still too early in its development cycle to have numerous ready-made applications, making it difficult to implement. AI applications need to be built on a case-by-case basis since there are no off-the-shelf manufacturing applications that use AI natively. As a result, only large companies are currently taking advantage of AI. Despite this, there is widespread excitement about AI, with many companies starting to use it at the ChatGPT level, such as writing better marketing copy, which is an excellent use case. The challenge, however, is that AI applications are slow to develop because they require a lot of data to be effective. Manufacturing is a great industry for AI as it generates a lot of measurable data and hard facts. But most manufacturing companies are under-digitized, so medium-sized and smaller companies are rapidly trying to digitize their data and create AI-ready repositories.
To continue reading what Ilia Badeev, Head of Data Science at Trevolution Group, says, click here
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