ROI Looks Different in the AI Era LLMs now accelerate how code is written, refactored, and merged. Traditional “scan-and-fix later” workflows can’t keep up with that pace; they push findings downstream, inflate rework, and slow releases. The financial impact shows up as extra PR rewrites, pipeline reruns, context switching, and escalations. The fix is to move AppSec to the point of creation, inside the IDE, so issues are prevented or remediated while the developer’s mental stack is fresh. Agentic AppSec is autonomous, context-aware assistance that validates and remediates during coding, not after the commit. Gartner frames this category as AI Code Security Assistance (ACSA); Checkmarx One Assist operationalizes it through Developer Assist. A Practical ROI Model You Can Take to Your CFO For all the talk about developer productivity and AI acceleration, most AppSec leaders still struggle to express value in the language of finance. Your CFO doesn’t want “shift left” jargon and vulnerability counts, they want a structured model that translates engineering efficiency into measurable return. When we analyze ROI for Checkmarx One Developer Assist, we focus on five value buckets that both finance and engineering already recognize. Each ties directly to operational metrics your leadership team tracks, making it easy to build a defensible business case for Agentic AppSec: 1. Mean Time to Remediate (MTTR) Inline findings and explainable fixes inside the IDE compress triage and remediation from hours to minutes. Since developers resolve vulnerabilities in context, fewer issues escape to late-stage testing or production, where every fix costs exponentially more. The result is measurable improvement in DORA MTTR and a more predictable release cadence. 2. Throughput (Features per Period) and Lead Time for Changes Every context switch, jumping from IDE to portal, waiting on a review, or rerunning a build, creates friction that slows throughput. When developers fix in-place, PR churn decreases and pipelines stabilize. That efficiency shows up directly as more completed work per sprint and a measurable reduction in Lead Time for Changes, one of the most visible metrics to executives tracking delivery velocity. 3. False-Positive Drag Noise has a cost. Each false positive wastes time erodes trust in tools, and slows adoption. By combining high-fidelity detection with explainable remediation, Developer Assist reduces alert fatigue across the SDLC. A Checkmarx case study found that Best Buy reduced false positive by 80%, illustrating the real economic drag of noisy security and the ROI of precision. 4. Rework and Failure Cost Rework is one of the most underestimated drains on engineering productivity. Every post-merge defect triggers retesting, re-review, and sometimes a full CI/CD rerun. By catching vulnerabilities inside the IDE, Developer Assist prevents this expensive cycle before it begins. The result is fewer failed builds, lower operational overhead, and more stable release plans, which are benefits that directly translate into reduced operational expenses (OpEx) and improved predictability. 5. Developer Experience (Retention and Flow) Security tools succeed or fail on adoption. If they slow engineers down, they’re disabled or ignored. Developer Assist meets developers where they work, offering AI-powered help that feels like collaboration, not interruption. Tools that improve flow and reduce cognitive friction boost both sentiment and retention, gains that compound over time into sustainable throughput and morale. A CFO’s Takeaway When you put it all together, these five metrics – TTR, throughput, false-positive drag, rework cost, and developer experience – form a complete Agentic AppSec ROI model. It ties productivity, quality, and cost together in one narrative that resonates from the engineering floor to the boardroom. Agentic AppSec is a measurable accelerator of business outcomes. The data is already in your DevOps pipeline, and the only question is whether you’re ready to quantify it. Mechanics, Not Magic, Make Value Every second counts when prevention happens in the IDE. By embedding detection, validation, and remediation directly where developers work, the result is measurable productivity and stronger security posture at the same time. Detect earlier, fix faster (MTTR and failure avoidance) Developer Assist analyzes source, manifests, IaC, and container descriptors as you type, surfacing explainable findings and one-click “Fix with Assist” flows right in the editor. Early detection reduces “late discovery” work and lowers the chance of broken builds. Explainable AI remediation (trust drives adoption) Structured prompts plus verified remediation data mean developers see why a change is needed, not just a diff. That “explain then apply” pattern speeds reviews and keeps security aligned to developer intent: critical for sustained adoption. Integrated coverage (fewer tools, fewer gaps) Because Developer Assist is powered by the Checkmarx platform, teams benefit from proven detection across SAST, SCA, IaC, secrets and container risks delivered in a consistent, IDE-first workflow. Reducing tool switches and consolidating signals also simplifies reporting upstream. When AppSec becomes an active participant in development, not a passive gate at the end of it, security scales with the speed of code creation. Developer Assist bridges that gap, merging developer efficiency with enterprise-grade validation. The impact is cumulative: fewer missed vulnerabilities, faster clean builds, and quantifiable time savings that turn secure coding into a measurable business advantage. Estimate Your ROI in Two Steps Step 1: Time saved per issue Without IDE-level remediation: assume ~1–3 hours per issue (triage, rework, rebuilds). With Developer Assist: much of that time collapses into minutes because context is fresh and changes are applied inline. Step 2: Multiply by avoided rework Count how many security-related build failures/reruns you had last quarter. Apply your blended engineering hourly rate to the time you didn’t spend reworking those PRs. Want a walkthrough? Our team can map DORA metrics to pre- vs post-Assist performance using your pipeline data. Let’s talk. What Makes a Tool Actually Agentic? And Does It Matter for ROI? Gartner’s AI Code Security Assistance (ACSA) lens emphasizes pre-commit, intent-aware control vs reactive scanning. In practice, this means fewer defects make it to late stages (where each fix is 3–10x more expensive than in development) and the ones that do arrive are already annotated with context. That’s why agentic beats “scan later” in cost curves. Developer Assist pays for itself by eliminating rework at the source. When security happens in the IDE, you fix faster, ship faster, and report outcomes that resonate from dev teams to the board. Read More: The Executive’s Guide to Quantifying Agentic AppSec ROI, From IDE Metrics to Board-Ready Numbers. Download: The Agentic AI Buyer’s Guide
