When it comes to startup operations, one aspect that can often be overlooked in the early stages is the development of a comprehensive and robust policy library. This is especially important when considering information policies, which govern the use, management, and security of data and technology in your organization. Establishing these policies not only sets clear expectations for employees but also assures customers about your company’s commitment to security and reliability. Using AI like my GPT-4 GRC approach can streamline this process.
The process of creating these policies, however, can be time-consuming and potentially confusing for startups. This is where AI, specifically OpenAI’s GPT-4 model, can step in to streamline this process. In this post, we’re going to show you how we’ve used GPT-4, in the form of ChatGPT, to build a comprehensive information policy library for a small SaaS-based startup planning to achieve SOC 2 compliance. We spoken in more general terms about the use of ChatGPT in your infosec program, but in this post I wanted to try something more practical.
To start with, we drafted a general information security policy. This policy covered essential security practices like risk assessments, user training, access management, physical security, and data protection. All these areas were tailored to be accessible and understandable for employees while also providing strong assurances for customers.
Can you write an information security policy for a SaaS based startup? A company with about 50 employees. A company planning to do SOC 2 in the next 12 to 18 months. It should be easy to understand and set clear expectations for employees while giving strong assurances to customers about corporate and application security practices.
Next, we added details about disaster recovery and data encryption to strengthen the policy. We then created a specific policy for endpoint security, taking into account that the company provides Mac laptops to all employees while allowing the use of personal mobile devices.
We then moved on to write an incident response policy, detailing a step-by-step process to respond effectively and efficiently to security incidents.
Following that, we created a disaster recovery plan, outlining the steps the company would take to recover from a significant event that might disrupt its operations. This plan considered the company’s use of GitHub for code storage and AWS tools for service data backup.
Finally, we crafted a change management policy, considering the company’s use of GitHub and JIRA for managing changes to its IT infrastructure.
Throughout this process, ChatGPT helped us generate drafts for each policy, which we were able to customize and tailor to the specific needs of the company. This AI-based approach greatly reduced the time and effort typically required to create these important policy documents.
To make it easy for other startups to follow this process, we’ve shared all the policies created during this exercise on GitHub. These can serve as a good starting point for your own policies.
Harnessing the power of AI can significantly streamline the policy creation process for startups. We hope this post serves as a guide for leveraging AI in your own startup’s journey towards a comprehensive information policy library.
View the policies we wrote on GitHub.
As always, we’d love to hear your thoughts and experiences on this topic. Please feel free to leave a comment below!
Disclaimer: The policies created during this process are intended as a starting point and should be reviewed and customized based on the unique needs and legal requirements of your organization.