Published: 04 January 2024
Analytics and AI continue to collide, with repercussions in multiple domains. To leverage emerging opportunities and mitigate unknown risks, data and analytics leaders must address the impact of artificial intelligence analytics and data science ecosystems, user behavior, roles, and decisions.
Artificial intelligence (AI) is rapidly changing how line-of-business users interact with analytics platforms to make decisions, increasing their adoption through augmented analytics capabilities.
The distinction between analytics content creators and consumers is becoming blurred as AI enables both to gain insight that is optimally aligned and integrated with their workflows.
AI is reshaping responsibilities across the data science workforce. The augmentation and automation of more sophisticated decisions allow less technical users to assume more complex tasks, thereby increasing the value of their work.
AI-enabled analytics experiences are becoming more composable by integrating intelligent applications with a headless architecture and action frameworks
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Analysts:
Edgar Macari, Peter Krensky, Afraz Jaffri, David Pidsley, Aura Popa, Mike Fang, Rita Sallam, Julian Sun, Radu Miclaus
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