AI, DevSecOps, and the Future of Application Security: The Gartner® Report
None
<div class="feedwordpress-gaffer-full-text"> <div class="container"> <div class="body-grid"> <div class="body-content"> <span id="hs_cos_wrapper_post_body" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_rich_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="rich_text"> <p><span>Even as organizations recognize the importance of application security, most still struggle to operationalize it at scale. That gap becomes harder to ignore as development accelerates, AI becomes embedded in workflows, and software supply chains grow more complex.</span></p> <p><span id="more-2092667"></span></p> <p><span>At the same time, three major shifts are redefining how application security actually works in practice:</span></p> <ul> <li> <p><span>AI-augmented development.</span></p> </li> <li> <p><span>The growing role of developer experience in DevSecOps.</span></p> </li> <li> <p><span>The consolidation of security tooling into unified platforms.</span></p> </li> </ul> <p><span>Taken together, these trends point to a simple reality that application security is not only evolving, but also undergoing a fundamental restructure.</span></p> <h2 style="font-size: 30px; font-weight: normal;">AI Accelerates Development but Expands Risk</h2> <p><span>Generative AI has quickly moved from experimentation to everyday development.</span></p> <p><span>Teams using AI coding assistants write code faster, reduce manual effort, and streamline workflows. Despite the productivity gains, speed introduces a new challenge: more code, more dependencies, and more potential vulnerabilities entering the system.</span></p> <p><span>This isn’t a novel problem. It’s a scaling problem.</span></p> <p><span>Modern applications already rely heavily on open source packages, many of which contain known vulnerabilities. AI doesn’t change that dynamic. It amplifies it by increasing the volume and velocity of code being produced.</span></p> <p><span>There’s also a second layer of risk emerging. AI tools themselves introduce new attack surfaces, from insecure recommendations to unexpected behaviors. In some cases, models can suggest outdated, vulnerable, or even nonexistent dependencies — creating entirely new categories of supply chain risk.</span></p> <p><span>Development is getting faster, but the margin for error is shrinking.</span></p> <h2 style="font-size: 30px; font-weight: normal;">AI Also Becomes Part of the Solution</h2> <p><span>The same technology driving this acceleration is also starting to reshape how teams handle security.</span></p> <p><span>AI-assisted remediation tools are emerging to help developers understand vulnerabilities, prioritize fixes, and resolve issues more quickly. Instead of treating security as a separate step, these tools bring guidance directly into developer workflows.</span></p> <p><span>This shift matters because the bottleneck <a href="https://www.sonatype.com/blog/ai-devsecops-and-the-future-of-application-security-the-gartner-report">(Read more...)</a></span></p></span></div></div></div></div><p class="syndicated-attribution">*** This is a Security Bloggers Network syndicated blog from <a href="https://www.sonatype.com/blog">2024 Sonatype Blog</a> authored by <a href="https://securityboulevard.com/author/0/" title="Read other posts by Aaron Linskens">Aaron Linskens</a>. Read the original post at: <a href="https://www.sonatype.com/blog/ai-devsecops-and-the-future-of-application-security-the-gartner-report">https://www.sonatype.com/blog/ai-devsecops-and-the-future-of-application-security-the-gartner-report</a> </p>