For executives, proving the ROI of security investments has always been complex. Traditional AppSec tools report on vulnerabilities, found and fixed, but those metrics rarely translate into tangible business value. Agentic AI AppSec, led by Checkmarx One Developer Assist, changes that equation. By embedding explainable, real-time remediation directly into the IDE, Developer Assist helps enterprises measure impact in terms that matter to both engineering and finance: time saved, quality improved, and cost avoided. Here’s how to make that case with metrics your business already trusts. Start With Metrics Your Business Already Trusts The first rule of security ROI: your CFO doesn’t buy “scan accuracy”. They buy measurable outcomes that improve throughput, reduce cost, or accelerate delivery. That’s why the most credible ROI models for Agentic AppSec align with the DORA metrics engineering leaders already track, and extend them with quality and cost indicators. Lead Time for Changes (Cycle Time) Inline, IDE-level guidance shortens the time between code commit and deployment. By surfacing vulnerabilities and fixes as developers code, teams spend less time revisiting PRs or waiting on security reviews. Fewer bottlenecks mean faster feature delivery and shorter feedback loops. Change Failure Rate Agentic AppSec catches misconfigurations, insecure dependencies, and code smells before a commit, not after a build breaks. Fewer failed builds and hot-fixes translate directly to higher release stability and lower unplanned work, which impacts both velocity and engineering morale. Mean Time to Remediate (MTTR) Traditional tools force developers to context-switch between security reports and code. Developer Assist embeds explainable remediation right inside the IDE. Developers understand why a fix matters and can resolve it immediately, reducing MTTR across sprints and improving compliance reporting accuracy. False-Positive Rate Precision isn’t just a technical metric, it’s an economic one. Every false positive consumes developer time. Best Buy, a Checkmarx customer, reduced false positives by 80% with Checkmarx One, reclaiming hundreds of developer hours per quarter. That reclaimed time is a quantifiable efficiency gain. Translate Engineering Signals into Dollars Once you’ve anchored your metrics, it’s time to connect them to financial impact. The key is reframing engineering efficiency as cost avoidance and productivity gain. Here’s how to quantify each dimension: Rework Avoided Rework is the silent tax on software delivery. Every time a vulnerability is caught post-merge, the fix requires retesting, redeploying, and re-reviewing. To calculate the value of avoiding that rework: Gather last quarter’s data on security-related build failures or reruns. Estimate the average time spent on each (triage + fix + retest). Multiply that time by your blended engineering hourly rate. Attribute the reduction in failures after Developer Assist adoption as the savings delta. What you’ll find is that even a modest 10% reduction in rework yields measurable ROI: because rework compounds across builds, QA cycles, and deployment delays. Time-To-Value Acceleration Time is revenue. Faster, cleaner releases mean features reach customers sooner, accelerating the revenue recognition timeline. Developer Assist’s inline guidance prevents bottlenecks that block PRs or delay merges. Tie your improvement in Lead Time for Changes directly to your product roadmap milestones. Finance already understands the concept of time-to-market; now they’ll see how in-IDE AppSec directly impacts it. Alert Fatigue Reduction Noise doesn’t just frustrate developers, it drains resources. Every false positive triggers a triage cycle that adds no business value. By reducing false positives through explainable AI and high-fidelity scanning, Developer Assist saves real hours. Use the Best Buy 80% reduction benchmark as a directional proxy in your initial model, and replace it with your own metrics after a 30-day pilot. What “Agentic” Changes in the Cost Model Executives are hearing the term Agentic AI more often, but what it really means for ROI is straightforward: it shifts AppSec from a reactive process to an autonomous, context-aware assistant. As Gartner’s framing of AI Code Security Assistance (ACSA) describes, these systems assist developers with policy-aware validation in real time, closing the gap between development and security. That shift has two major financial effects: Defect prevention instead of post-factum correction. Fewer defects reach production, and those that do carry richer metadata for faster triage. Cost compression. The cost of fixing a defect late in the lifecycle is 3–10x higher than fixing it during development. By detecting and resolving issues at the creation point, Developer Assist drives a direct cost avoidance multiple. In essence, agentic AppSec redefines security from a cost center into a throughput engine, one that pays dividends in efficiency, developer satisfaction, and customer trust. From Metrics to Board-Ready Outcomes Agentic AI AppSec doesn’t just change how developers work; it changes how executives justify security investment. By reframing technical metrics into measurable outcomes like reduced rework, accelerated delivery, fewer false positives, and higher developer efficiency, Developer Assist gives both CISOs and CFOs a clear ROI narrative supported by real data. Security isn’t slowing you down anymore. It’s making every release faster, safer, and smarter. How Checkmarx One Developer Assist Implements Agentic for ROI Inline Prevention and Explainable Fixes The combination of IDE-native detection and explainable remediation shortens MTTR and reduces Change Failure Rate, two Google DORA metrics with direct Operating Expenses impact. Fewer Tools to Juggle, Clearer Reporting Up the Stack Because Developer Assist is powered by the Checkmarx platform, you get consistent detection across SAST/SCA/IaC/Secrets/Containers with in-IDE guidance, and unified reporting for execs. That reduces swivel-chair time and makes trend reporting credible. Adoption That Sticks If developers don’t trust a tool, it won’t move metrics. Checkmarx content emphasizes just-in-time, in-flow assistance that teaches while fixing, which is critical for sustained adoption and compounding ROI. Your 30-Day Proof Plan (Feel Free to Copy/Paste) Week 1 – Baseline Extract last-quarter DORA metrics (Lead Time, Change Failure Rate, MTTR). Pull counts for security-related build failures and average time per failure. Week 2 – Pilot Enable Developer Assist for 1–2 active teams in VS Code/Cursor/Windsurf. Track: inline fixes applied, PRs with fewer revisions, build failures avoided. Week 3 – Compare Contrast pilot teams vs. control on DORA metrics + failure counts. Capture anecdotal feedback on explainability and dev flow. Week 4 – Roll-up Convert time deltas into dollar savings. Exec slide: “From IDE events → DORA improvement → cost avoided.” FAQs Execs Will Ask (and Concise Answers) Is this just SCA in the editor? No. Developer Assist brings in-IDE guidance backed by the Checkmarx platform across code, dependencies, IaC, secrets, and container descriptors with explainable remediation, not just alerts. How is this different from reactive scanning? It prevents issues before they hit the repo/CI and annotates fixes with context developers understand, improving both MTTR and adoption. Is there analyst alignment for this approach? Yes! Gartner’s AI Coding Security Assistant (ACSA) concept describes exactly this: policy-aware assistants validating code at creation. Close the Loop Between the IDE and the Boardroom Agentic AppSec isn’t a cost center; it’s a throughput engine. With Developer Assist, leaders see cleaner sprints, fewer reruns, faster releases, and measurable MTTR gains, all traceable to in-IDE prevention and explainable remediation. Download: The Agentic AI Buyer’s Guide Read: The ROI of Agentic AI AppSec Tags: Agentic AI AI generated code AppSec AppSec Maturity
