You’ll need a lot of detailed prompts to get solid output - and even then it may have errors and typos
The proliferation of generative AI tools is leading organizations like Cisco to experiment with their practical application for internal processes, testing the limits and requirements for effective AI integration.
This highlights the current challenges and limitations of applying AI to critical tasks like security incident reporting, underscoring the need for careful prompt engineering and human oversight.
Organizations are learning that while AI can assist in mundane tasks, its current capabilities in nuanced, fact-sensitive areas require significant human guidance and validation.
- · AI prompt engineers
- · Cybersecurity training providers
- · AI model developers focused on accuracy
- · Companies adopting AI without verification
- · Entry-level report writers
Security teams can draft incident reports more quickly, but with a higher need for human review to correct errors and inaccuracies.
This could lead to the development of more specialized AI models specifically trained on security incident data, potentially improving accuracy.
Future cybersecurity roles may shift towards managing AI tools and validating their output, rather than solely generating reports from scratch.
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Read at The Register