AI Readiness Hindered by Data Quality and Governance Issues

Wednesday, 18 September 2024, 06:00

AI readiness is significantly impacted by data quality and governance issues, according to a recent study. The research highlights challenges organizations face in utilizing AI technologies. Understanding these obstacles is crucial for future advancements in AI deployment.

AI Readiness Hindered by Data Quality and Governance Issues

AI Deployment and Data Quality Challenges

In the journey towards AI readiness, organizations are grappling with critical issues related to data quality and governance. A recent study released globally emphasizes that the deficiencies in these areas can considerably hinder the effective implementation of AI technologies. With precise insights gained from collaboration with the Center for Applied AI and Business Analytics at Drexel University’s LeBow College, this research brings to light significant implications for businesses striving for a competitive edge.

Key Findings of the Study

Data Integrity Challenges: Issues concerning data accuracy and consistency are rampant.
Governance Deficiencies: Lack of proper governance frameworks complicates AI readiness.
Impact on Innovation: Without data quality, innovation in AI suffers.

This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.

AI Deployment and Data Quality Challenges

Key Findings of the Study

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