In the end there will be two kinds of organizations, those which are powered by artificial intelligence (AI) and those which have been left behind to wither and fade away; it's called the algorithmic competitive advantage. If you're thinking that this is far off into the future, let me tell you that the future is right now. From influencing who you vote for, to where you would like to travel this summer or which stocks to invest in, AI has become inexorably entwined in our lives and it has been happening for quite some time now; let's say since 1914. The enhanced use of algorithms is certainly happening at a staggering pace. In an example from the financial world, a venture capital firm now has an algorithm sitting on its board of directors. Hong Kong-based Deep Knowledge Ventures appointed an algorithm as a director in 2014 so it can vote on whether the VC fund should invest in a certain company or not. Deep Knowledge Ventures' algorithm director analyses data from sources such as clinical trials, financial records and previous funding rounds before casting its vote.

The power of AI and its subset Machine Learning is sweeping across all industry verticals, disrupting ways or working, processes, jobs, professions and our lives. Whether it is talking to Siri, choosing a product to buy online, riding a diverless vehicle, or using Google Maps to find our way in a strange city; AI has become ubiquitous. At times we don't even realize that AI is silently guiding us through our lives each day, influencing, coxing, cajoling or simply directing us to take certain decisions.

From our health to our education, relationships and financial fortunes, AI has an influence in everything. It is therefore imperative for businesses to understand and leverage AI, Machine Learning (ML) and Deep Learning (DL) to stay relevant.

AI will be and is already being used to sharply define customer preferences, design products, launch new services, enter into collaborations, foray into new markets backed by solid research, helping in mergers & acquisitions and reshape organizations. Our skills and competencies in AI will determine whether we succeed or fail.

Such is the overwhelming power of AI, and the limitless possibilities of how it can be used for both good and evil, that OECD's Directorate of Financial & Enterprise Affairs Competition Committee has come out with a paper which suggests that there could be a need to regulate the unfair use of algorithms for firms to collude to fix prices. We are already seeing signs of it when we search for air tickets or hotel bookings. Once airlines and hoteliers have data about your possible travel dates obtained from your search patterns they can fix the price either way.

Before we dive deep into AI let's first clear certain fuzzy thoughts about three terms which we will use in this article ­ Artificial Intelligence (AI), Machine Learning (ML) Deep Learning (DL); these are not to be used interchangeably as there are inherent difference between them as is seen in the graphic.
As we move into the higher levels of the second wave in Machine Learning, we are encountering management issues that we never thought before. Not only is AI and ML disrupting the workforce, it is trans-forming the competitive landscape by lowering entry barriers for new and nimble competitors, they are fueled by data analytics a key component of AI & ML.

Senior managers across organizations agree that changes, such as automation, AI, the rise of non-traditional competitors and advances in manufacturing, were imminent, few had conceived strategies for how their organizations might respond. It is surprising because mainstream management thinking assumes that managers reign supreme in determining the affairs of their company. The manager, as homo economicus -- the "rational agent" beloved of economists and finance theorists -- chooses the most preferential strategic option from a range of scenarios based on rational calculation of what will achieve the optimal economic outcome.

The business case of Algorithmic Competitive Advantage is compelling as the sheer volume of in-formation and data being churned out is impossible for human managers to process and take decisions. Managers are not leading the disruption (primarily from technological innovation), but merely responding to it as best as they can. Herbert Simon, winner of the 1978 Nobel Prize for economics, challenged the notion of homo economicus by recognizing the cognitive limitations of managers: we can only partially know our options or their outcomes in any given situation. The complexity, turbulence and uncertainty of the contemporary business environment, fueled in large part by more and better information (and therefore transparency), is defeating the contemporary manager because the 20th century model of how we govern organizations has not changed to reflect the realities of the 21st century. It is time now for the AI-Powered CEO of tomorrow!