The widespread adoption of generative AI (GenAI) has led to a significant increase in productivity, with up to 66% improvement reported. However, this increased use also brings security risks and spiraling costs if not implemented correctly. A staggering 75% of global knowledge workers are using GenAI applications, with more than 78% bringing their own GenAI tools to work. This raises concerns, as 71% of organizations do not provide employees with guidance on when, where, or how to use AI. To avoid mistakes, organizations must develop a comprehensive AI strategy, weighing security and cost factors, and considering options such as building a large language model from scratch, accessing an LLM through an API, building applications on public cloud infrastructure, or downloading and customizing an open-source LLM. By making the right strategic decisions, organizations can maximize control while optimizing cost efficiencies and avoiding the pitfalls of shadow AI.

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