Is machine learning for the future or is it for your business right now? It\u2019s a question lots of business leaders are asking as each day new instances of AI and machine learning push the boundaries of what we thought we knew about technology. One recent and powerful example was Google\u2019s May 8 demonstration of its Google Assistant booking hair salon and restaurant reservations with conversational clarity that was both inspiring and unnerving. Many business leaders would be forgiven for a twinge of panic. If machines are learning that quickly, how behind is my business right now when it comes to leveraging machine learning?\n\nGood news: this is just the beginning\n\nWhile its part of Google\u2019s job to be the maverick, breaking ground with embryonic and advanced technologies, most CIOs are tasked with delivering solutions that yield business results. Outside of the companies racing to build self-driving cars or lead the way in global face recognition systems, few companies have figured out how to monetize the kind of machine learning that focuses on teaching robots to behave more like humans. Despite that fact, there is tremendous investment pouring into AI and machine learning. The International Data Corporation (IDC) predicts that investment in cognitive and artificial intelligence systems will grow to over $52 million by 2021.\u00a0\n\nRight now: let the machines be machines\n\nWhere should CIOs focus their machine learning budgets and vision? Rather than looking for ways that technology can behave more like humans, CIOs can and should take more advantage of the some of the distinctly non-human capabilities computers have. For example, computers today can process and analyze large, complex data sets in milliseconds. Add machine learning capabilities to that colossal, rapid analytical ability and suddenly you have a business intelligence (BI) tool that can crawl ever-growing, complex business data, watch for trends, analyze what it finds and provide insights and potential solutions.\n\nBusiness intelligence: where the action is\n\nBusiness intelligence right now, with its ability to combine big data analytical work with machine learning capabilities, is where we are seeing several different industries make strategic forays into artificial intelligence. Here are a few examples of how machine learning is already hard at work across several industries:\n\nThe smart machines are here\n\nWhile they might not yet be driving our cars and building our houses, smart machines are hard at work turning the data we have into answers we need. For business leaders wondering where to begin with machine learning, the answer is in the question. What are the hardest questions your business is looking to answer? If there\u2019s data to explore, there are smart machines and business intelligence tools equipped to help your business with the answers.