Championing data leadership: how can data strategy shape AI success? (www.techradar.com)

Recent insights reveal that over 75% of organizations are leveraging AI in at least one business function, illustrating a growing recognition of its transformative potential. However, many are struggling to realize tangible returns due to the critical dependence on high-quality data. Only 12% of organizations report having data sufficient for effective AI implementation, emphasizing the urgent need for robust data quality management and governance practices. Poor data can derail even advanced AI systems, particularly in areas like personalized recommendations, leading to costly missteps and customer dissatisfaction. To overcome these challenges, experts advocate for establishing a strong data governance framework that aligns with evolving regulations, such as the GDPR and the EU AI Act. By implementing data observability tools, organizations can proactively monitor their data pipelines for anomalies, ensuring integrity and accuracy in real time. The articles stress that prioritizing data quality, governance, and observability is essential for organizations aiming to fully harness the capabilities of AI, enhance decision-making, and improve operational efficiency in an increasingly competitive landscape.