It’s still early enough in the new year to add on to your resolutions, and prepping your enterprise for artificial intelligence (AI) should be at the top of your list. In fact, simply getting started is the most important thing you can do since only half of current business leaders actually have developed a plan. Today, 84% of enterprise overseers give credit to AI when discussing how they stay one foot ahead of their competition. Similarly, the top businesses in the consumer market consider data science pivotal to their successful outcomes. For instance, 55% of business leaders in the education and manufacturing sectors believe this. Similarly, 65% of technology, wholesale, and retailers say the same.
However, data science technology is universal in business, carrying the ability to be useful across many sectors unmentioned. Enterprise AI uses customized machine learning models and AI-based software solutions to refine efficiency, reduce waste, and discover lost value across departments.
For example, an automotive supplier lowered scrap by 50% by using artificial intelligence to monitor their product’s quality. This reduced rework and growing profits. Similarly, Big River Steel uses AI to make recommended corrections, maximize production, and sense potential overlap.
Saying this, the gainable benefits from artificial intelligence are broad. With the help of AI, enterprise leaders can make quicker, stronger decisions, lower overhead costs, and increase their production results. Even more, AI can help enterprise leaders reduce or eliminate wasted energy, excess inventory, equipment downtime, and more.
Although it was previously mentioned that the most important step is just getting started, it is first important to understand how AI can fit into your business. In the words of Lee Blackstone, founder of Blackstone+Cullen, “You need to understand what you really need to automate and how it’s going to benefit you.
Prolonging AI implementation puts your company at risk of falling behind the competition. Find the information you need for drafting your Enterprise AI Resolution in the attached graphic.
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