During the cloud computing boom, innovation was abundant, but it also highlighted the importance of strategic planning to avoid costly mistakes like “shadow IT.” This refers to IT activities conducted without the knowledge of the IT department, leading to unexpected expenses and security risks. As generative AI continues to rise, IT leaders can use these lessons to prevent similar issues with “shadow AI,” the uncontrolled use of AI without proper planning.
Generative AI shows great potential for economic impact, but it requires meticulous strategic planning. Relying solely on public clouds for AI may not be the best option; considering on-premises deployments can also provide value. Although some may view this as controversial, opting for on-premises AI could save enterprises millions in the long run. Studies indicate that running AI on premises may be more cost-effective than using the cloud. This approach prioritizes data security, sovereignty, and efficient management, avoiding issues like data gravity and costly system reconfigurations.
Why cloud isn’t always the answer for AI
The cloud computing revolution brought about a new wave of innovation, offering unprecedented access to computing resources and facilitating massive digital transformation. However, the rapid adoption and rushed implementation also led to increased costs, security vulnerabilities, and governance challenges, reminiscent of the issues seen with shadow IT.
