How do I apply AI to all my data and make my business different?

Sponsored Artificial intelligence (AI) started out as laboratory research, but today's AI techniques like machine learning and deep learning are increasingly finding their way into real-world applications such as detecting fraudulent activity in financial transactions, analysing retail data to deliver a personalised shopping experience, or finding the optimal route for delivery vehicles to take. These trends mean that AI is rapidly becoming an integral part of many enterprise workflows, from email to CRM or ERP, and especially data analytics to glean business intelligence insights from an organisation's own datasets on how to drive efficiencies or even create new business opportunities. Not surprisingly, a recent IDC survey showed that 85 per cent of organisations are evaluating AI or already using it in production. However, IDC found that most organisations reported experiencing failures among their AI projects, with a quarter reporting a failure rate of up to a 50 per cent. These failures have been attributed to a lack of skilled staff or cultural challenges, but another common cause of failure is the inability to scale from a proof-of-concept project to running in a production capacity that can serve the entire organisation.