Data Intelligence Leading the Next Wave of AI/ML Solutions: A Global Survey of AI/ML and Technology Professionals

Today, most companies believe AI/ML is delivering business value, increased agility, and improved productivity for employees. But what is AI/ML being used for? This white paper investigates new opportunities for AI/ML solutions, levels of autonomy being granted to these solutions, and current challenges and hurdles around AI/ML adoption and implementation.

Also learn more about:

-How AI/ML delivers strong business value, enables business agility, and reduces effort

-Why data intelligence tops the list for AI/ML related investments and projects

-The key role AI/ML plays with data governance, quality, and privacy


This white paper reviews key findings from a global research survey to understand AI/ML-enabled solution use cases, challenges, and their value to organizations.


Key Findings

AI/ML is delivering strong business value and positive perceptions leads to Increasing AI Autonomy

● Company perceptions of AI/ML solutions are positive: delivering increased value, enabling business agility, and reducing effort

● 77% cite positive experiences with AI/ML

● 49% already trust a machine-led based AI approach, and 20% have fully autonomous AI running at their company

Data intelligence tops the list for AI/ML related investments and projects

● The top use of AI/ML is data intelligence (51%) followed by IT operations (47%)

● Data intelligence tasks data quality (36%), governance (29%), and privacy (23%) are also being assigned to AI/ML programs

● AI/ML is utilized  by numerous teams: product management (32%), business operations (38%), customer management (31%), and marketing (28%).

AI/ML deployments on efficiency, decision-making, business insights data intelligence and governance 

● Top benefits expected from AI/ML involve efficiency, faster decision making, and improved business insights

● Data governance AI/ML focuses on efficiency, compliance, and security