Data analytics and business intelligence are imperative to enhance business growth today. They have far-reaching benefits like improving customer experience, delivering better services, developing agility, risk management, fraud detection, and many more. AI has been a blessing to industries so that they could create better and intelligent insight. These data-driven insights are the crux of businesses today and companies are trying to get to these insights as fast as possible. The customer-centric approaches in the current scenario and the fast-paced technology-driven businesses demand faster insights.

If we are not actively engaged in industries related to technology, we may fail to fully appreciate how we might already be influenced by artificial intelligence in our day-to-day world. Everyone is talking about self-driving cars, seemingly inanimate objects conversing with you about your personal preferences, someone somewhere already seems to recommend your shopping list armed with the knowledge of what you like or dislike. From the viewpoint of the business world, all companies today are looking to adopt AI in some form or the other to improve business processes, achieve efficiency, so on and so forth. I recently read an article about Softbank's Masayoshi Son and his vision "for an AI-powered utopia where machines control how we live". While this may sound like an unreal possibility, one could relate to this thought better if one were to ponder over David Fano's (Chief Growth Officer, WeWork) words, "Basically, every object will have the potential to be a computer".

Digital transformation of the finance function can improve transactional performance and deliver insights that create and sustain value across the entire enterprise. Think of CFOs, and who do you picture? Typically, you might see them as prudent people. They're not the category of board members you might traditionally regard as the first adopters of technology. But times have changed, and it's time to look again.

Machine learning delivers insight into drugs' effects on stroke patients Researchers have used machine learning to identify how individual stroke patients might respond to different medications, based on the unique structure of their brain. An experiment by University College London (UCL) found that applying computer intelligence to data from from people who had suffered a stroke allowed researchers to see what effect drugs had on brains with varying patterns of damage. For the study, a machine learning algorithm was applied to CT and MRI scans of 1172 stroke patients and mapped the anatomical pattern of damage throughout the brain of each individual. The researchers then simulated the effects of certain hypothetical drugs, to see if any reactions that would have been missed by conventional methods could be identified. They found that the algorithm was particularly advantageous when looking at medication effects that reduced the size of lesions in patients' brains.