To mark the beginning of the new year, Athentic Consulting invites you to explore the key trends in Data Governance for 2026. These trends are intended to help organizations prepare, adapt, and move forward with confidence in a world increasingly driven by data and artificial intelligence (AI).
Data Governance continues to evolve amid growing challenges—balancing innovation, regulatory compliance, and trust in data usage. This is especially critical in an era where AI plays a central role in operations, data volumes are growing exponentially, and data-related regulations are becoming more complex. As a result, Data Governance today is no longer solely about control or oversight; it has become a vital mechanism for enabling Data-driven Transformation, while ensuring data accuracy, transparency, and trustworthiness.
Organizations should strengthen their readiness for Data Classification, as it is a fundamental component of effective data management. Data classification clearly defines access rights and usage boundaries, reduces data security risks, and supports appropriate data sharing both within and across organizations. In general, data can be categorized into five levels: Open, Private, Confidential, Secret, and Top Secret. Organizations should establish clear policies, standards, and guidelines for data classification to ensure operational efficiency while protecting organizational interests and the privacy of relevant stakeholders.
Organizations should enhance their capabilities in data sharing, which involves transferring data from source owners to authorized recipients who require the data for legitimate purposes. This process must comply with applicable laws and regulations. Data sharing can occur both internally and externally across organizations. Proper data classification enables organizations to clearly define access rights and usage conditions, ensuring that data sharing is secure, efficient, and delivers maximum value.
Data quality is a critical factor in realizing the value of data—whether for decision-making, dashboard development, data analytics, or AI-driven applications. High-quality data must be accurate, complete, and reliable. Organizations can improve data quality through various measures, such as developing metadata and data descriptions, defining data quality metrics and evaluation criteria, and regularly monitoring and assessing data quality.
Currently, the Digital Government Development Agency (DGA) of Thailand has drafted notifications and digital government standards aligned with the Cloud First Policy. These standards aim to establish a framework for managing government cloud services, covering key areas such as data classification, cloud service selection, and cloud service provider standards. The objective of these digital government standards is to provide guidance and recommendations for public sector agencies to effectively plan and implement cloud-based initiatives. Leveraging cloud technology as a core enabler will help enhance public service delivery and improve resource management in a tangible and sustainable manner.
Artificial Intelligence (AI) plays an increasingly important role in organizational operations, making it essential for organizations to establish a strong foundation for AI Governance. Effective AI Governance helps ensure that AI is adopted and used responsibly, delivers tangible value, and appropriately manages risks while adhering to ethical principles. In Thailand, the Electronic Transactions Development Agency (ETDA) has developed guidelines for the ethical and responsible adoption of AI, which are structured around three core components: establishing AI governance structures to clearly define roles and responsibilities of relevant stakeholders; defining AI strategies that encompass both value creation and risk management considerations; and governing AI operations throughout the entire AI system lifecycle. Together, these measures aim to ensure that AI usage is transparent, secure, trustworthy, and aligned with organizational objectives.
Based on the data governance trends in 2026, it is evident that data governance has become increasingly challenging. This includes data classification, data sharing, data quality management, cloud-first policy standards, and the governance of artificial intelligence (AI) applications. All of these elements are closely interconnected and must be implemented in a systematic and integrated manner to enable organizations to maximize the value of data and support policy-level decision-making in a world where data and AI have become key drivers of organizational development in the future.
Athentic Consulting is ready to share its experience and provide approaches tailored to your organization’s specific context—from laying a strong foundation for data governance to strengthening and enhancing existing processes in a sustainable manner. Our consulting team is committed to supporting organizations in leveraging data effectively and securely, while also delivering end-to-end data management platform development services that comply with relevant laws and standards. With a dedicated team of system developers and data experts providing continuous support, we enable organizations to confidently and sustainably drive data-driven decision-making.
📩 Contact us: https://www.athenticconsulting.co.th/
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