Democratized, operationalized, responsible: the 3 keys to successful AI and ML outcomes


Artificial intelligence (AI) and machine learning (ML) are among the most transformative technologies of all generations. That helps explain why AI and ML adoption is on the agenda of so many business and technical leaders. Organizations everywhere are investing in AI and ML for a variety of reasons. Most notably, they fuel rapid innovation. They also drive competitive advantage by adding intelligence to existing processes, automating time-intensive manual tasks, and accelerating the creation of new products and services.

Although specific estimates on the growth of AI and ML vary, there is no debate about the impact of these technologies on the global economy. Gartner predicts that the size of the AI and ML market will reach $134.8 billion by 2025, considerably outpacing the growth of the worldwide software market. Likewise, IDC forecasts that AI and ML investments will jump from $85.3 billion in 2021 to $204 billion in 2025, resulting in a compound annual growth rate (CAGR) of 24.5 percent for the 2021–2025 period. The effects of these numbers are (potentially) staggering—both for the organizations that make the investments and for those that do not.

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