Recent years have seen the expansion of artificial intelligence into an array of industries with varying levels of disruption. Once a horizon-technology (perhaps similar to how we now view quantum computing) AI has officially breached everyday life, and informed opinions are no longer reserved for tech enthusiasts and elite data scientists. Now, stakeholders include executives, investors, managers, the government, and ultimately customers. While conversations regarding Explainable AI (xAI) date back decades, the concept emerged with renewed vigor in late 2019 when Google announced its new set of xAI tools for developers. The concept of xAI is relatively simple: historically, machine learning models have operated within a "black box," with outcomes determined by an astounding number of interwoven parameters so complex (in the millions) that explaining them proved impossible.

Machine learning falls into a category of technology currently experiencing hyper-exponential growth as enterprises capitalize on its ability to transform data into insightful action. Like any hyped technology, machine learning is not without current limitations; however, companies operating on the cutting-edge are finding innovative ways to integrate machine learning into an impressive bottom-line. And it's no longer just pet projects for elite Fortune 500 brands--everyone is joining the fun. With this rapid evolution, the role of data professionals is being reconceptualized; leaders increasingly understand data-related infrastructure in terms of the factory model, giving rise to the notion of a data science factory. Data goes in, actionable insights come out, and everything happening in-between falls into the "making the sausage" category--nobody wants to know too much. On one end of the factory, you have the dizzying collection of platforms to manipulate data (Python, H2O, TensorFlow, R, Scikit-Learn, Keras, SAS, Openface, Caffe2, Watson, Google, Azure, AWS ML cloud APIs, and the list goes on).

According to Gartner's 2019 CIO Survey, AI adoption by businesses grew 270% over the last four years, and over 37% of businesses have implemented AI in some facet. Businesses are adopting the technology at staggering rates, and Chief Information Officers and data scientists are facing difficult decisions regarding which speed of AI fits their business needs. AI can be broken down into three scoring patterns: batch, event-driven, and real-time. Each scoring pattern provides different capabilities, depending on the goal of the model. For example, while batch computing may work ideally in a payroll setting, it would not be an effective way to track fraud in banking transactions.

"Machine Learning excels at taking all rich signals, detecting patterns within them, and providing algorithms to optimize outcomes to the desired target.

Today, consumers encounter artificial intelligence continuously through smartphones, customer service centers, websites, and appliances. Surveys show that nearly nine in 10 Americans use some form of artificial intelligence device, and 79% of people report AI having a perceived positive impact on their lives. Despite the overwhelmingly positive uptake of the technology, films, art, and literature have long warned about the potential dangers of AI in science fiction storytelling. So, how much of this is based on reality? In order to answer these questions, it's important to look at the facts, where AI really stands and why many of these AI projects are untrue (at least in our lifetime).

With tech giants announcing "AI-first" business models and investment in intelligent technology skyrocketing, it may come as a surprise to learn that only 20% of surveyed enterprises are actually implementing AI this year. While there's a prevailing sentiment among business leaders that they have missed the AI boat, the reality is that the boat is still in the harbor, and there's still plenty of room aboard. Early adopters of any technology do bystanders a great service by working out the kinks. Now that products have been tested and consumers introduced, contemporary businesses braving the AI waters will be known historically as the first generation to wield this promising technology to revolutionize industries. Certain companies are expecting returns on their AI investments to reach 30% in the coming years.