FACTS McKinsey highlights five
McKinsey highlights five elements that must be tackled elements that must be for AI adoption within tackled for AI adoption enterprises : within enterprises :
• Clearly defined use cases or
• Clearly defined use cases or sources of value sources of value
• Robust data ecosystems
• Robust data ecosystems
• A workforce that is adept at using
• A workforce that is adept at systems and tools using systems and tools
• Clear integration with workflows
• Clear integration with in the core business workflows in the core business
• An open culture that embraces a
• An open culture that embraces ‘ test and learn ’ approach a ‘ test and learn ’ approach 79 have them uploaded to a machine learning-enhanced platform for a diagnosis to be made based on learnings from other patients . Changes over time may be minor and difficult to detect by a human being , but such signs can be caught and flagged by the system as new images are supplied . But , of course , for such ideas to become reality , “ most of the region will need to build foundational digital infrastructure and data ecosystems to realise these types of opportunities ,” McKinsey says .
It is clear that Asia and the ASEAN region is both replete with opportunity and risks that must be addressed when it comes to the implementation of artificial intelligence and its technological brethren , machine learning , deep learning , and RPA . Governments and enterprises
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