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Break Through the AI Analysis Paralysis

by; Jo Ann M Stadtmueller, SR Director, Marketing



AI Analysis Paralysis

All enterprises use intelligent tools in order to create positive outcomes. AI is one of those tools that organizations are implementing in their digital transformation. AI is not necessarily new, its genesis is now over 50 years old. However, the application of enterprise artificial intelligence is fairly new and can help businesses compete in areas such as organizational operations, customer experiences, predicting applications, sales and revenue growth, naming just a few.


Like anything new there is a starting point and exploration follows. After all the investigation, reading hundreds of reports, attending events, listening to analysis, viewing demos and talking expenditures you might still be left with questions. What intelligent tools does my business need? How does a business buy AI? How do I bring AI into the company to become part of our digital transformation? What are my objectives for using AI? What departments need AI? Where will the value be created? What are the costs? The list of questions becomes longer and longer and analysis paralysis can ensue possibly leaving your organization to fall behind its competitors. The business value of AI and the value we can extract are monumental. Getting past all the questions and paralysis and to the point of implementation can be a long road. The AI journey should not start here rather it should start when a pilot program is implemented.


Let’s face it your organization has been sitting on and paying for a gold mine of stored data in your data warehouse. This data is valuable and can manifest itself in all sorts of ways that can give your organization the competitive edge it needs. Unlocking that data needs Enterprise AI and a platform that allows you to put your top talent to work as AI professionals. These employees know your business better than anyone else and can recognize value when it presented itself since they know your business and it nuances the best.


Best plan of action to start down this road is to start small, start quick, get results fast and then scale. Once the right solution rises to the top of your list, start a pilot program. Start with a certain department, capture your data, ingest (making sure of compliance), then start your discovery and build models…training them. Next is to put those models to use, scale the process and duplicate this in more departments. Putting your data to work with an efficiently scalable and dynamic machine learning capability will help you find positive outcomes and enable you to monetize your AI investment.

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