Generative AI technology is advancing but remains immature in enterprise settings, frequently not meeting expectations upon deployment. To ensure success, organizations must prioritize detailed planning that establishes a robust data and infrastructure foundation. This month's coverage of generative AI highlights various pitfalls that can occur when AI tools are inadequately prepared for integration, while also showcasing successful implementations that exemplify effective strategies for leveraging these emerging technologies in a corporate environment.
Generative AI is still in its infancy within enterprises, often failing to meet expectations when deployed, pointing to the need for foundational planning.
Success with generative AI requires careful planning and a cohesive data infrastructure, which allows AI tools and agents to operate at their best.
Many enterprises face challenges with generative AI due to inadequate phase tests and integration, indicating a need for improved deployment strategies.
This month's highlighted stories focus on both the failures and successes of generative AI, offering insights on how to avoid common pitfalls.
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