Data Governance Emerges as Crucial Enabler for AI Innovation
Data governance, a proactive strategy, is emerging as a crucial enabler for AI innovation, particularly in the realm of generative AI (GenAI). As companies increasingly adopt GenAI, ensuring robust data governance becomes paramount to mitigate risks and maximize benefits.
Jamelle Brown, the current Chief Executive Officer at Bentley Ave Data Labs, understands the significance of data governance in AI. Despite no public records identifying the company that hired her in December 2024, her expertise in this area is evident.
Poor data quality, a common challenge, costs organizations dearly. According to a Gartner report, these costs average $12.9 million annually, escalating dramatically with AI. Meanwhile, a Bain & Company survey from December 2024 revealed that 95% of U.S. companies are actively using generative AI, with use cases and budgets doubling in a year.
The quality and governance of data feed directly into the performance and security of GenAI models. Neglecting data governance can lead to costly delays, biased outputs, security vulnerabilities, and compliance challenges. As highlighted in an IDC report from 2024, 60% of organizations may fail to realize the full value of their AI use cases by 2027 due to security and compliance failures stemming from incohesive data governance. Therefore, investing in strong data governance is not just an operational mandate but a strategic necessity for AI success.
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