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4 things executives should know about AI and data science Posted on : Apr 13 - 2018

Artificial intelligence, machine learning, and deep learning are buzzworthy terms in the world of business, ranging across channels from customer service to finance and beyond. Because big data is big news, companies want to implement AI to improve their businesses — but some are making the mistake of trying to layer in artificial intelligence without the basis in analytics and data that allows AI to make a true impact.

Other companies — those with a strong foundation in analytics, possessing a store of data to work from — can utilize AI with great success. According to the Harvard Business Review, “companies with strong basic analytics — such as sales data and market trends — make breakthroughs in complex and critical areas after layering in artificial intelligence.”

AI innovations like those aren’t possible without the right data and specialized data science staff who know how to use it. The following are four lessons that vanguard businesses have learned about the intersection between data and deep learning — lessons you can apply to your organization as you layer in your own artificial intelligence algorithms.

1. You have the data you need, but aren’t using it yet

If you have a successful business model making significant revenue, chances are you already have a ton of data available to you about your customers — what they’ve purchased, when they purchased it, how they prefer to be contacted — collected from common customer interactions. If you aren’t using this data or centrally collecting it for easy access, you’re wasting a resource that can add efficiency to your organization by providing a better, more personalized experience for your customers.

2. Creating new data is as important as using existing data

Too often, the traditional approach to analytics or data science is beholden to data you already have. As data science evolves, the creation of new, more applicable data and the capture of previously underutilized data are becoming more important. Business processes helped by artificial intelligence are only as good as the data you feed into that AI, which means locating and creating the right data is essential.

3. Data and information availability empowers autonomy

Historically, a business’ success has largely depended on in-company experts who knew the business model very well — high-level employees who have been with the company a long time, who understand the business and can act as resources, and who generate intuition from experience. This “executive intuition” is an incredibly valuable resource, but many employees in larger organizations do not have the experience necessary to garner this intuition, and not every employee has access to those veteran experts who do have the intuition. View More