Management teams often assume they can leapfrog best practices for basic data analytics by going directly to adopting artificial intelligence and other advanced technologies. But companies that rush into sophisticated artificial intelligence before reaching a critical mass of automated processes and structured analytics can end up paralyzed. They can become saddled with expensive start-up partnerships, impenetrable black-box systems, cumbersome cloud computational clusters, and open-source toolkits without programmers to write code for them.
If Your Company Isn’t Good at Analytics, It’s Not Ready for AI
Be honest about your capabilities.
June 07, 2017
Summary.
Companies are just beginning to discover the many different ways that AI technologies can potentially reinvent businesses. But how can companies tell if they are really ready for these advanced technologies? First, managers should ask themselves if they have automated processes in problem areas that cost significant money and slow down operations. Next, they should ensure they have structured analytics as well as centralized data processes so that the way data is collected is standardized and can be entered only once. After these standard structured analytics are in place, they can be integrated with artificial intelligence.
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Accelerate your career with Harvard ManageMentor®. HBR Learning’s online leadership training helps you hone your skills with courses like Digital Intelligence . Earn badges to share on LinkedIn and your resume. Access more than 40 courses trusted by Fortune 500 companies.
Excel in a world that's being continually transformed by technology.