Stop Experimenting with AI and Machine Learning


The ability to make fast, data-driven decisions has never been more valuable as businesses grapple with the shift toward hyper-personalisation, driven by rapidly changing customer behaviours and expectations. The pandemic has accelerated the imperative for businesses to invest in Artificial Intelligence (AI) and Machine Learning (ML) so they can replace guesswork with data-powered certainty to reorient strategy and optimize operations for success in an uncertain future. Nevertheless, enterprises often struggle to integrate these technologies at scale and monetize the benefits. Stumbling blocks typically include challenges associated with cost, lack of investment protection, undefined business outcomes, lengthy timeframes from development to deployment, lack of expertise, and the complexities of the regulatory landscape. Gartner predicts that by 2022, at least 50% of ML projects will not be fully deployed into production.

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