AIAdoptionFramework

Availability and Access Ensuring the availability of data and ease of access is a fundamental requirement for any entity to effec­ tively and securely benefit from AI. Data is the core component on which models and algorithms rely to make accurate, evidence-based decisions. This includes: Using a Flexible Access Permissions System: Adopting a Role-Based Access Control (RBAC) mod­ el ensures the distribution of permissions according to business needs without compromising sensi­ tive data. This system enables precise control over who can access, modify, or share data, thereby enhancing the protection of information assets and supporting security compliance and governance. 4. Enablers ໟ AI Adoption Framework Using Data Discovery Tools: Data catalog tools allow users to explore and understand the data as­ sets within an entity. They enable various teams to locate data, understand its context (metadata), as­ sess its quality, and determine its readiness for use in analytics or models. This contributes to reducing duplication, enhancing collaboration, and accelerating data-driven decision-making. Automating Data Updates: Maintaining data freshness and accuracy is essential for the efficiency of analytical models and AI. This is achieved through periodic and automated update mechanisms that synchronize databases with actual changes in the sources, ensuring that decisions are based on cur­ rent and reliable information. These updates also help reduce human error and increase the reliability of data in supporting business operations. Complying with National Privacy Regulations: Ensuring compliance with the Personal Data Pro­ tection Law (PDPL) and relevant regulatory frameworks is a strategic priority for protecting individu­ al rights and enhancing trust in digital platforms. This includes implementing strict data processing policies, obtaining legal approvals when necessary, defining and managing access permissions, and enforcing cybersecurity controls according to best recognized practices. Activating Data Governance Office: The Data Governance Office serves as a centralized supervisory entity responsible for policy development, monitoring implementation, and ensuring that various teams adhere to data management controls. The office plays a pivotal role in organizing access processes, documenting data usage, and conducting regular audits to ensure compliance, thereby achieving a balance between effective data use and maintaining its security and confidentiality. Simplified Practical Example The entity implements an internal data management platform that allows relevant employees to search data sources using a central data catalog. Their access permissions are automatically defined based on their roles, with periodic audit reports to verify that no violations have occurred. ໟ ໟ ໟ AI Adoption Framework