A-Step-by-Step Guide: How to Mitigate the Risks of Using Generative AI

While Generative AI is shaping up to be the next big-ticket driver of productivity and creativity, it comes with several risks that need to be managed, to protect businesses and their customers from harm.

Common Generative AI risks include:

• Inaccuracy: Generating misinformation or inaccurate content Data bias: Generating harmful outputs that are biased or discriminatory.
• Cyber security: Generative AI models could accidentally access sensitive customer and business data
• Lack of control: One potential challenge with Generative AI outputs is identifying potential issues, like the utilisation of copyrighted material.
• Insufficient user training: Employees may accidentally expose sensitive and business enterprise data when using Generative AI.

In this guide, we will take you through a step-by-step approach on how to mitigate the risks of using Generative AI for your business and explain what measures you can put in place to ensure safe and successful use of Generative AI.

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