5 things to know about getting started with AI, machine learning

ACCORDING to Oliver Wyman Forum's inaugural Global Cities AI Disruption Index, Singapore topped the list of 105 cities most ready for AI disruption, thanks to its strong performance in the vision category, which measures the presence of plans to respond to technology changes and plans to upgrade labour skills and infrastructure such as mobile networks. Indeed, companies across Asia-Pacific are investing billions of dollars on artificial intelligence (AI) and machine learning (ML) - with good reason.

These technologies deliver real business-altering potential and for these reasons, Gartner's Enter the Age of Analytics report predicts that by 2023, AI and deep-learning techniques will be the two most common approaches for new applications of data science. But despite the promise, few companies have been able to successfully implement and deploy this technology as part of their overall data and analytics strategy. According to Deloitte's State of AI in the Enterprise 2nd Edition Survey, only 41 per cent of companies in Asia-Pacific are using AI, while less than one-third of sales teams have put AI systems into action. At the same time, the results of a global survey by software intelligence company Dynatrace confirm that 94 per cent of CIOs in Singapore say that AI will be critical to IT's ability to master the increasing complexity of the evolving technological landscape.

The truth is that it will take years before many organisations realise the true potential of AI and ML, but it is never too early to lay the groundwork now for an AI-driven future. In fact, if an organisation is not already thinking about what an AI strategy looks like, its competition is likely one step ahead. There's no time to waste, so here are five important points to consider when getting started with AI and ML.