With more and more data available to analyze, organizations are realizing the value that sophisticated analyses using artificial intelligence and machine learning (AI/ML) can provide. The benefits of these analyses are significant: our Dynamic Insights research on machine learning finds that organizations most often benefit through competitive advantage, but also improved customer experiences, increased sales, the ability to respond quickly to opportunities in the market, and lower costs. However, the need for specialized skills to deploy AI/ML models can stall data science initiatives. An organization’s efforts to scale data science and apply models are often complicated by a lack of self-service access to infrastructure, tools and data.
Business improvement stems from technology investments that advance automation and apply intelligence to your work and processes, increasing the potential achievement of desired outcomes. Assessing vendors and utilizing technology for optimization and innovation is the foundation for digital transformation, and our chief research officer asserts that by 2025, over one-half of organizations will determine that the chaos of digital technology usage requires a rationalization of vendors to ensure operational excellence.
The virtualization of business and the evolution of digital transformation to applications and systems that operate in cloud computing — or the “as-a-service” environment — has fragmented enterprise and data architectures. The role of cloud computing has become a utility to provide elastic resources in support of operational needs. For example, data in the cloud requirements are provided by third-party vendors, managing security and storage of data outside the organization.
The artificial intelligence industry is unique in that it has evolved to the point of making dramatic impacts across other markets. AI is used to help businesses scale, improve customer experiences, decrease waste and streamline cumbersome tasks. Ventana Research sees the need for AI innovation for the future of technology and the many other industries it influences, but making such tools available to everyone at fairly low costs can be difficult. It is no surprise that nearly two-thirds (62%) of organizations report using machine learning today, and nearly three-quarters (72%) of organizations participating in our research say they plan to increase ML use.