[{"data":1,"prerenderedAt":1210},["ShallowReactive",2],{"/en-us/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity":3,"footer-en-us":49,"the-source-banner-en-us":392,"the-source-navigation-en-us":404,"the-source-newsletter-en-us":432,"footer-source-/en-us/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity/":443,"article-site-categories-en-us":454,"how-ai-helps-devsecops-teams-improve-productivity-article-hero-category-en-us":456,"how-ai-helps-devsecops-teams-improve-productivity-the-source-source-cta-en-us":480,"how-ai-helps-devsecops-teams-improve-productivity-category-en-us":496,"how-ai-helps-devsecops-teams-improve-productivity-the-source-resources-en-us":508,"how-ai-helps-devsecops-teams-improve-productivity-article-hero-author-en-us":547},{"_path":4,"_dir":5,"_draft":6,"_partial":6,"_locale":7,"config":8,"seo":12,"content":16,"type":40,"slug":41,"category":5,"_id":42,"_type":43,"title":44,"_source":45,"_file":46,"_stem":47,"_extension":48},"/en-us/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity","ai",false,"",{"layout":9,"template":10,"author":11,"featured":6},"the-source","TheSourceArticle","kristina-weis",{"title":13,"description":14,"ogImage":15},"How AI helps DevSecOps teams improve productivity","Learn how DevOps teams are using AI to save time and improve efficiency.","https://res.cloudinary.com/about-gitlab-com/image/upload/v1751464559/fbvzbz6vxppsblv8sngf.png",{"title":13,"date":17,"description":14,"timeToRead":18,"heroImage":15,"keyTakeaways":19,"articleBody":23,"faq":24},"2024-01-02","6 min read",[20,21,22],"Utilizing AI in DevSecOps workflows significantly boosts efficiency and productivity by automating repetitive tasks, reducing context switching, and providing intelligent assistance.","AI tools can enhance code quality and security by offering real-time suggestions, summarizing potential threats, and providing remediation strategies.","Organizations should develop strategies addressing privacy, intellectual property, and data security concerns, ensuring AI implementations align with legal and ethical standards.","Artificial intelligence (AI) and machine learning (ML) in software development are here to stay, and DevSecOps teams are using them in many different ways to save time and improve productivity and efficiency.\n\nHere are a few ways development, security, and operations teams can incorporate AI into their DevOps processes.\n\n## 9 ways DevSecOps teams use AI\n\n### Ask questions in documentation using chatbots\nTo find answers faster and reduce context switching, DevSecOps teams can use AI-powered chatbots to ask questions and get relevant answers in real time from documentation or other large volumes of text. Instead of leaving the IDE or platform where they’re writing and deploying code to go search the web, developers can ask a built-in chatbot a question and get one concise answer without disrupting their flow.\n\n### Suggest tests and test files\nDevelopers can use AI to suggest tests and generate test files for their code, right in the merge request. This can help them enhance their testing, ensure they have appropriate test coverage for their changes, and reduce the time they have to spend writing and thinking about tests.\n\n### Summarize code changes\nWhen making a commit or merge request, developers can use AI to generate a written summary of the code changes. This can help developers save time when they’re committing changes and asking for code reviews, and AI can also help code reviewers save time - and likely provide a better review - by giving them more context on the changes made before they dive into the code.\n\n### Get suggestions for who can review code\nCode review is an important, but sometimes frustrating and time-consuming, process - especially if the right reviewer isn’t asked the first time.\n\nBy looking at the code changes and the project’s contribution graph, AI can automatically suggest a code reviewer who can provide faster and higher-quality feedback and catch potential issues. AI also can help save time by suggesting someone else to review the code if a suggested reviewer doesn't respond or if their review isn’t sufficient.\n\n### Summarize discussions\nWhen discussions get lengthy or convoluted, teams can use AI to summarize all the comments in an issue or ticket. This can help everyone get on the same page and efficiently understand the status of a project and what the next steps are, leading to more seamless collaboration and faster results.\n\n### Suggest code\n[AI-powered code suggestions](https://about.gitlab.com/blog/top-tips-for-efficient-ai-powered-code-suggestions-with-gitlab-duo/) can help developers write code more efficiently by suggesting code right in their IDE while they’re developing. Developers can use AI to complete blocks of code, define and generate logic for function declarations, generate unit tests, suggest common code like regex patterns, and more. These capabilities can certainly make developers more efficient, but because less than 25% of developers’ time is spent on code development [according to our research](https://about.gitlab.com/developer-survey/), it’s just one piece of the puzzle.\n\n### Explain how a piece of code works\nDevelopers (or anyone on the DevOps team) can use AI to get a quick explanation of what a block of code does and why it's behaving the way it is – without leaving their workflow.\n\nAn AI-generated code explanation can be particularly helpful for developers trying to understand pieces of code that others have created or that’s written in a language they’re less familiar with. And according to [our research](https://about.gitlab.com/developer-survey/), developers spend 13% of their time understanding what code does, so time savings here can really add up.\n\n### Summarize vulnerabilities in code\nUnderstanding a newly detected security vulnerability and how to fix it isn’t trivial, but AI-powered security tools can make it simpler and more efficient. An [AI-generated summary of a vulnerability](https://about.gitlab.com/blog/developing-gitlab-duo-use-ai-to-remediate-security-vulnerabilities/) helps developers and security professionals understand the vulnerability, how it could be exploited, and how to fix it. Some AI-powered tools can even provide a suggested mitigation with sample code. This can go a long way in [helping teams avoid potential security threats and security risks](https://about.gitlab.com/the-source/ai/4-ways-ai-can-help-devops-teams-improve-security/) with less effort.\n\n### Forecast productivity metrics\nUsing AI, software leaders can [forecast or predict productivity metrics](https://about.gitlab.com/blog/developing-gitlab-duo-ai-impact-analytics-dashboard-measures-the-roi-of-ai/) - such as deployment frequency - to identify trends and anomalies across the software development lifecycle. These actionable insights can help teams implement changes to improve their efficiency and DevSecOps processes.\n\n## The benefits of using AI in software development\nDevSecOps teams are using AI - or plan to use AI - to help them do many things, including:\n\n* Improve efficiency of their software delivery lifecycle\n* Speed up cycle times\n* Streamline compliance checks\n* Improve employee productivity\n* Improve security posture\n* Improve code quality\n* Improve customer satisfaction\n* Improve employee satisfaction and the developer experience\n* Improve collaboration between teams\n* Improve application performance\n* Automate repetitive tasks\n* Reduce operational costs\n* Reduce context switching and cognitive load\n* Reduce human error\n* Get new hires up to speed faster\n* Help employees [learn new programming languages](https://about.gitlab.com/blog/learn-advanced-rust-programming-with-a-little-help-from-ai-code-suggestions/)\n\n## Avoiding privacy and security issues\nWhile there are numerous benefits to integrating AI into the software development process, it’s important to be aware of the potential risks as well as common issues and obstacles.\n\nAccording to our [research](https://about.gitlab.com/developer-survey/2024/ai/), privacy, security, and a lack of familiarity with AI-driven solutions were common obstacles respondents said they encountered or expect to encounter while implementing AI in the software development lifecycle. Of all the obstacles identified, concerns around privacy and data security was the most common response (34%), followed by the lack of appropriate skills (31%) and the lack of AI knowledge (30%).\n\nBusiness leaders should ensure that AI implementations adhere to established privacy and security standards. This involves integrating compliance checks and balances throughout the AI lifecycle to protect sensitive data and maintain user trust. It's also key to ensure you adopt AI tools that are transparent about how their machine learning models use your organization's data.\n\n## Get to know GitLab Duo\nAll the capabilities mentioned above - from code explanations to suggested tests - are part of [GitLab Duo](https://about.gitlab.com/gitlab-duo/), the suite of AI capabilities built into GitLab’s DevSecOps platform. GitLab Duo helps DevSecOps teams boost efficiency, reduce cycle times, and prevent context switching with AI-assisted workflows in every phase of the software development lifecycle, all in a single application.\n\n> Learn why GitLab was named a Leader in the 2024 Gartner® Magic Quadrant™ for AI Code Assistants.\n> [Access the report](https://about.gitlab.com/gartner-mq-ai-code-assistants/){class=\"button\" data-ga-name=\"gartner magic quadrant\" data-ga-location=\"thesource\"}",[25,28,31,34,37],{"header":26,"content":27},"How does AI contribute to better code security in DevOps?","AI-powered security tools identify, summarize, and suggest fixes for vulnerabilities in real time. They provide automated risk assessments and mitigation recommendations, helping teams detect threats earlier in the software development lifecycle and reduce security blind spots.",{"header":29,"content":30},"How can AI forecasting improve software development performance?","AI-driven analytics predict deployment frequency, cycle times, and productivity trends, allowing teams to identify inefficiencies, improve DevOps strategies, and proactively address bottlenecks before they impact performance.",{"header":32,"content":33},"How can AI improve the efficiency of DevSecOps teams?","AI enhances DevSecOps efficiency by automating repetitive tasks, suggesting code improvements, summarizing vulnerabilities, and streamlining compliance checks. It reduces context switching, speeds up workflows, and allows teams to focus on higher-value development and security efforts.",{"header":35,"content":36},"What are the key privacy and security risks when using AI in DevSecOps?","The primary risks include data privacy concerns, AI-generated code vulnerabilities, and a lack of transparency in how AI models handle proprietary data. Organizations should vet AI providers for compliance with security standards and ensure AI-powered workflows align with internal governance policies.",{"header":38,"content":39},"Can AI help developers understand complex or unfamiliar codebases?","Yes, AI-powered assistants explain code logic in natural language, making it easier for developers to quickly grasp existing code structures and dependencies. This is particularly useful when onboarding new developers or working with legacy code written in unfamiliar programming languages.","article","how-ai-helps-devsecops-teams-improve-productivity","content:en-us:the-source:ai:how-ai-helps-devsecops-teams-improve-productivity.yml","yaml","How Ai Helps Devsecops Teams Improve Productivity","content","en-us/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity.yml","en-us/the-source/ai/how-ai-helps-devsecops-teams-improve-productivity","yml",{"_path":50,"_dir":51,"_draft":6,"_partial":6,"_locale":7,"data":52,"_id":388,"_type":43,"title":389,"_source":45,"_file":390,"_stem":391,"_extension":48},"/shared/en-us/main-footer","en-us",{"text":53,"source":54,"edit":60,"contribute":65,"config":70,"items":75,"minimal":380},"Git is a trademark of Software Freedom Conservancy and our use of 'GitLab' is under license",{"text":55,"config":56},"View page 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