Why machine learning strategies fail

According to a recent survey by Rackspace Technology, from more than 1,800 organizations in a variety of industries, only 20 percent of organizations succeed in implementing machine learning strategies.

Why such small success rates? There are three key areas where companies meet challenges:

• Solving problems related to data

• Acquiring the right talent to perform research and deployment of machine learning solutions

• Developing an AI strategy that provides value, ROI, and buy-in from executives and decision-makers

To find out more, read my latest on TechTalks, where I explore these challenges and provide some tips on how to avoid the pitfalls of designing and implementing machine learning strategies.

To learn more about the challenges of AI in real-world applications, read our series on “The business of artificial intelligence.”

Book recommendations:

• Prediction Machines discusses the business value of machine learning

• The AI Advantage explores the sectors and companies that have been successful in applying machine learning

• Competing in the Age of AI highlights the role of solid data infrastructures in developing successful AI strategies