EDITOR’ S QUESTION
FADI KANAFANI, GENERAL MANAGER MIDDLE
EAST, SOFTSERVE
A critical step is implementing Zero Trust architecture to manage data access and sharing securely.
As the adoption of Generative AI spreads across the enterprises and shadow AI begins to emerge from various departments, how should the usage of data be managed to ensure it is available for Generative AI use cases and yet does not violate data privacy and data compliance policies?
To address the challenges and opportunities presented by Generative AI adoption across enterprises, particularly in managing data usage while upholding data privacy and compliance, businesses must consider the following principles.
With enterprises embracing Generative AI, shadow AI, which are AI solutions developed independently by other departments, can complicate data governance. It is, therefore, essential to establish robust frameworks that ensure data accessibility for innovation without compromising compliance.
SoftServe emphasises adopting synthetic data solutions as a privacy-preserving alternative. This approach enables organisations to share and utilise data for Generative AI use cases without exposing sensitive information, ensuring both compliance and innovation coexist seamlessly.
A critical step is implementing a Zero Trust Architecture to manage data access and sharing securely. This model enforces authentication at every interaction point, ensuring data integrity and reducing risks of unauthorised access.
Additionally, embedding data governance strategies at the outset of Generative AI initiatives ensures compliance with region-specific regulations such as GDPR or regional data protection laws.
AI and machine learning tools can automate compliance checks and monitor data flows to detect anomalies. Behavioural analytics, for instance, can identify deviations from normal data usage patterns, flagging potential breaches or misuse.
Departments often adopt shadow AI due to inefficiencies in centralised systems. Providing teams with AI-powered tools that integrate seamlessly with existing workflows reduces the need for unsanctioned solutions.
For example, SoftServe’ s co-development of tailored AI tools with clients ensures alignment with corporate governance while delivering operational value.
Integrating AI-driven cloud-native tools can further enhance scalability and data management. Multi-cloud environments allow enterprises to store sensitive data in compliance-safe zones while leveraging the scalability of other platforms for non-sensitive operations.
SoftServe’ s expertise in cloud-native and multicloud solutions ensures seamless data operations across platforms.
Partnerships with industry leaders like NVIDIA, AWS, and Google can empower organisations with cuttingedge tools and training to mitigate challenges related to ethical AI use, data privacy, and resource shortages, such as GPUs. This collaboration supports enterprises in achieving sustainable AI adoption.
Managing data for Generative AI requires a hybrid approach that combines innovation, ethical foresight, and compliance rigor. By adopting such a framework, enterprises can unlock the transformative potential of AI while safeguarding their digital assets and adhering to regulatory mandates.
34 INTELLIGENTCIO MIDDLE EAST www. intelligentcio. com