Data Security by Environment: Considerations for Safely Using AI in the Cloud

Generative artificial intelligence technology is providing a competitive advantage for early adopters across many industries, while businesses that haven't made the transition yet are at risk of falling behind. To integrate AI into their tech stacks without compromising data security, business leaders must carefully consider how to deploy this technology in a way that protects sensitive information. Consumer-facing versions of large language model tools like ChatGPT offer a convenient way to explore the capabilities of LLMs, but using these tools at the enterprise level carries significant privacy concerns due to potential breaches and exposure of sensitive data. To mitigate these risks, businesses should consider accessing LLM tools through an API or hosting them on premises, which offers greater protection and control over data encryption and access controls. Enterprises that want to safely use AI tools in the cloud can explore options like Azure OpenAI and Amazon Bedrock, which offer secure infrastructure designed with enterprises in mind, and comply with applicable laws and regulations by devising thorough acceptable use policies and providing training on the risks associated with using AI.

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