Companies have various strategies to ensure that their competitive intelligence discoveries lead to growth, profitability, and a maintained advantage for their company. If a company hasn’t added machine learning to its competitive intelligence tool kit, it means it can lag behind.
Artificial Intelligence and Machine Learning are difficult challenges people have been working on for decades. But advances in computing power and the efforts of many creative and dedicated people seem poised to make more breakthroughs likely. To be actionable, the data that traditional search and reporting methods return must have relevant meaning. Companies can spend a lot of time milling and manipulating the data to extract substance. Or, they can begin their work with artificial intelligence at their fingertips, and derive meanings a lot faster.
Artificial intelligence accelerates the process of gathering data and putting it to work. More specifically, machine learning, as an application of artificial intelligence, uses algorithms to recognize patterns and trends to learn on its own. The machine has no explicit programming (i.e., expectations, pre-conceived ideas…) for what to find. So, in addition to faster processing, the output of an AI-based system does some of the interpretive work. It is not just a quantitative report of, say, a competitor’s profits and losses or a list of patents. Artificial intelligence unlocks insight into the movement of markets and players in those markets. It quickly goes from information gathering to automated analysis. When a company can see its significance, the data has more value.
This SlideShare explores the concept of Machine Learning for competitive market intelligence in brief.
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