Using AI to make smarter decisions from data

It's no secret that artificial intelligence (AI)-enabled devices are listening in or observing what we're doing, collecting and digitising massive amounts of data. What underpins this entire enterprise is the work under the hood – maintaining data lakes and warehouses that store the data, performing data engineering tasks to establish and enhance the structure, using business intelligence and statistical analysis to make sense of it and, finally, training an AI program to make predictions that yield more "intelligent" decisions. For example, many of us are familiar with virtual assistant technologies that take in information, digitise the data, put it into data pipelines, and analyse it so the AI algorithms become better in near real-time, fine-tuning it specifically to one's world. What makes an AI algorithm potent is when it can start making connections with other data sets and data points. This results in the creation of a profile that encompasses your shopping behaviour, what you're doing at home, what music you like listening to, what you like eating, and even where you live – in suburbia or in the city.