For companies to not fail and make the most of the machine learning models, it is important to lay a strong base in the first place. Checking on the data quality, recruiting the right talent, paying them well in combination with the management’s support can help achieve the desired results.

The survey, which includes 1,870 organizations in a variety of industries, including manufacturing, finance, retail, government, and healthcare, shows that only 20 percent of companies have mature AI/machine learning initiatives. The rest are still trying to figure out how to make it work. Lower costs, improved precision, better customer experience, and new features are some of the benefits of applying machine learning models to real-world applications. But machine learning is not a magic wand. And as many organizations and companies are learning, before you can apply the power of machine learning to your business and operations, you must overcome several barriers. Three key challenges companies face when integrating AI technologies into their operations are in the areas of skills, data, and strategy, and Rackspace's survey paints a clear picture of why most machine learning strategies fail.