| Poor data governance threatens AI investments and business performance |
Businesses are being urged to strengthen data quality governance as growing investments in artificial intelligence (AI), cloud infrastructure, and advanced analytics expose weaknesses in enterprise data management. Kartik Pillai, global head of data and AI at Pizza Hut, argues that technology investments alone cannot ensure reliable data without a clear operating model establishing ownership, accountability, and remediation procedures. Drawing on experience in a global quick-service restaurant business with more than 60,000 locations, Mr. Pillai advocates combining automated data monitoring with defined quality standards, business ownership, and service-level agreements. His proposed framework prioritizes critical data assets according to their operational importance, measuring accuracy, completeness, consistency, timeliness, validity, and uniqueness where appropriate. A hybrid governance structure, with centralized standards and accountability assigned to individual business functions, can help prevent inconsistent reporting, inaccurate profitability calculations, and unreliable AI outputs. Pillai emphasizes that organizations should prioritize their most important datasets, establish clear procedures for resolving errors, and improve collaboration between business and technology teams to strengthen confidence in enterprise data and maximize returns on AI investments.