A Pathfinder paper navigates decision-makers through the issues surrounding a specific technology or business case, explores the business value of adoption, and recommends the range of considerations and concrete next steps in the decision-making process.
Artificial intelligence (AI), including machine learning and deep learning, is set to become one of the most transformational technologies in the history of the world, affecting most aspects of our lives whether we’re conscious of it or not. The application of these technologies will likely reshape how people work, study, travel, govern, consume and pursue leisure activities.
Successful AI relies on a number of factors including a large corpus of data, the requisite algorithms, expert data scientists with appropriate skills, and appropriate compute resources. The latter means not just physical and virtual server infrastructure, but also data management and database software designed to support high-performance data processing and analytics.
Data management is a critical enabler of machine learning projects because it helps overcome challenges such as accessing and preparing data, which can be a significant barrier to success. The results of 451 Research’s Voice of the Enterprise: AI & Machine Learning survey, conducted with people directly involved in AI and ML initiatives, illustrates the point: 33% of respondents cited accessing and preparing data as a barrier the use of machine learning, and 15% cited it as the most significant barrier.
