Data governance best practices for the AI-ready airport

Trevor Strome
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Trevor Strome: Winnipeg Airports Authority, Canada

Journal of Airport Management, 2024, vol. 19, issue 1, 57-70

Abstract: Airports generate vast amounts of data across various systems that are crucial for operational efficiency, safety and enhanced passenger experience. As airports increasingly rely on this data in order to adapt to evolving passenger experience demands, business environments and regulatory requirements, data governance becomes essential for managing, safeguarding and leveraging data effectively. A robust data governance framework provides the structure for ensuring data quality, security and compliance while enabling airports to harness data for artificial intelligence (AI) applications such as predictive maintenance and passenger flow management. By starting with a clear scope, objectives and policies, airports can build a data governance framework that addresses both current needs and future challenges. This paper explores the role of data governance in making airports AI-ready, outlining best practices for implementing a governance programme. It highlights the importance of tools such as data lineage tracking and the need for strong data security measures to comply with regulations such as General Data Protection Regulation (GDPR). The paper also emphasises the need for a culture of accountability, outlining key roles such as data stewards and chief data officers (CDOs) to ensure consistent, robust data management. As AI adoption grows, airports must focus on maintaining data integrity, fostering transparency and ensuring regulatory compliance to unlock the full potential of their data assets while safeguarding privacy and building stakeholder trust.

Keywords: data governance; artificial intelligence; AI; data privacy and security; regulatory compliance (search for similar items in EconPapers)
JEL-codes: M1 M10 R4 R40 (search for similar items in EconPapers)
Date: 2024
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