Enterprise Artificial Intelligence (AI) strategies could fail in 2024 due to over-reliance on cloud-based AI services. These services, while initially cost-effective and convenient, can lead to vendor lock-in, limiting flexibility and causing unexpected costs in the long run. A shift towards hybrid AI models, combining cloud and on-premises data storage, could mitigate these risks.
However, the adoption of hybrid AI models poses its own challenges. It necessitates the use of Kubernetes, a complex system that requires specialised knowledge to operate. Additionally, data privacy concerns may arise as sensitive data is moved between cloud and on-premises storage.
To address these issues, enterprises should consider adopting Kubernetes-native object storage solutions. These solutions are scalable, easy to use, and integrate seamlessly with AI and machine learning (ML) platforms. They also offer robust security features, ensuring data privacy and compliance. By adopting such solutions, enterprises can reap the benefits of hybrid AI models while avoiding potential pitfalls.
In essence, a successful enterprise AI strategy in 2024 will require a balanced approach, combining the convenience and scalability of cloud-based AI services with the flexibility and security of on-premises data storage.
Go to source article: https://blog.min.io/why-your-enterprise-ai-strategy-is-likely-to-fail-in-2024/