The article discusses the upcoming significant changes in information management and analytics driven by recent advances in artificial intelligence (AI), particularly generative AI. Despite progress over the past three decades largely due to Moore's Law, the foundational architecture of analytics has largely remained unchanged since the early '90s. Companies are now recognizing the vital role of data quality in successful AI implementations, leading to a renewed focus on data governance. A key theme is the democratization of information management functions as AI technology matures.
In the past 30 years, advances in data management have been driven by Moore's Law, yet the basic architecture of analytics remains unchanged since 1992.
Recent artificial intelligence advancements, particularly generative AI, are poised to drive significant changes in information management, with democratization being a key ripple effect.
The recognition of the need for high-quality data to train AI models is significantly reviving interest in data quality and governance across companies.
Leadership often assumed their company's data quality was adequate for AI applications, revealing a gap in understanding the importance of clean data.
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