In our recent blog post announcing GitHub Copilot X, we mentioned that generative AI represents the future of software development. This amazing technology will enable developers to stay in the flow while helping enterprises meet their business goals.
But as we have also mentioned in our blog series on compliance, generative AI may soon act as an enabler for developer-focused compliance programs that will drive optimization and keep your development, compliance and audit teams productive and happy.
Today, we’ll explore the potential for generative AI to help enable teams to optimize and automate some of the foundational compliance components of separation of duties that many enterprises still often manage and review manually.
|Generative AI has been dominating the news lately—but what exactly is it? Here’s what you need to know, and what it means for developers.
The concept of “separation of duties,” long used in the accounting world as a check and balance approach, is also adopted in other scenarios, including technology architecture and workflows. While helpful to address compliance, it can lead to additional manual steps that can slow down delivery and innovation.
Fortunately, the PCI-DSS requirements guide provides a more DevOps, cloud native, and AI-enabled approach to separation of duties by focusing on functions and accounts, as opposed to people:
“The purpose of this requirement is to separate the development and test functions from the production functions. For example, a developer can use an administrator-level account with elevated privileges in the development environment and have a separate account with user-level access to the production environment.”
There are many parts of a software delivery workflow that need to have separation of duties in place—but one of the core components that is key for any compliance program is the code review. Having a separate set of objective eyes reviewing your code, whether it’s human or AI-powered, helps to ensure risks, tech debt, and security vulnerabilities are found and mitigated as early as possible.
Code reviews also help enable the concept of separation of duties since it prohibits a single person or a single function, account, or process from moving code to the next part of your delivery workflow. Additionally, code reviews help enable separation of duties for Infrastructure as Code (IaC) workflows, Policy-as-Code configurations, and even Kubernetes declarative deployments.
As we mentioned in our previous blog, GitHub makes code review easy, since pull requests are part of the existing workflow that millions of developers use daily. Having a foundational piece of compliance built-in to the platform that developers know and love keeps them in the flow, while keeping compliance and audit teams happy as well.
Wouldn’t it be cool if one-day generative AI could be leveraged to enable more developer-friendly compliance programs which have traditionally been very labor and time intensive? Imagine if generative AI could help enable DevOps and cloud native approaches for separation of duties by automating tedious tasks and allowing humans to focus on key value-added tasks.
Bringing this back to compliance and separation of duties, wouldn’t it be great if a generative AI helper was available to provide an objective set of eyes on your pull requests? This is what the GitHub Next team has been working towards with GitHub Copilot for Pull Requests.
- Suggestions for your pull request descriptions. AI-powered tags are embedded into a pull request description and automatically filled out by GitHub Copilot based on the code which the developers changed. Going one step further, the GitHub Next team is also looking at the creation of descriptive sentences and paragraphs as developers create pull requests.
- Code reviews with AI. Taking pull requests and code reviews one step further, the GitHub Next team is looking at AI to help review the code and provide suggestions for changes. This will help enable human interactions and optimize existing processes. The AI would automate the creation of the descriptions, based on the code changes, as well as suggestions for improvements. The code reviewer will have everything they need to quickly review the change and decide to either move forward or send the change back.
When these capabilities are production ready, development teams and compliance programs will appreciate these features for a few reasons. First, the pull request and code review process would be driven by a conversation based on a neutral and independent description. Second, the description will be based on the actual code that was changed. Third, both development and compliance workflows will be optimized and allow humans to focus on value-added work.
While these capabilities are still a work in progress, there are features available now that may help enable compliance, audit, and security teams with GitHub Copilot for Business. The ability for developers to complete tasks faster and stay in the flow are truly amazing. But the ability for GitHub Copilot to provide AI-based security vulnerability filtering nowis a great place for compliance and audit teams within enterprises to get started on their journey to embracing generative AI into their day-to-day practices.
Generative AI will enable developers and enterprises to achieve success by reducing manual tasks and enabling developers to focus their creativity on business value–all while staying in the flow.
I hope this blog will help drive positive discussions regarding this topic and has provided a forward looking view into what will be possible in the future. The future ability of generative AI to help enable teams by automating tedious tasks will help humans focus on more value-added work and could eventually be an important part of a robust and risk-based compliance posture.