Software is now the front door of your business, and when it fails, revenue and trust are on the line. Yet quality assurance is still too often treated as a cost center instead of a growth driver. The AI mandate is raising the stakes: boards expect faster delivery through AI and low-code, but that speed creates more complexity to test. Most QA teams still rely on manual processes, leaving quality as the bottleneck. Katalon TrueTest changes that equation by combining AI-driven test generation with real-user insights, turning QA into a board-level catalyst for growth.
When executives look at testing budgets, they often focus on headcount. Traditional automation can deliver meaningful efficiency, reducing manual effort and producing strong returns. The challenge is that these benefits only go so far. Most organizations plateau at 20 to 40 percent test coverage. Pushing past that ceiling typically means adding more QA staff, which is neither cost effective nor scalable. In an environment where AI is accelerating the volume of code produced, relying solely on traditional automation leaves teams under constant pressure and unable to keep up.
Testing also influences customer satisfaction and revenue. Research shows that higher test accuracy and wider coverage are among the top benefits companies gain from automation. Better coverage reduces defect leakage and protects your brand. When you ship higher-quality software sooner, you generate revenue faster and minimize churn.
Yet quality is still too often treated as an expense rather than an investment. This mindset persists even though the cost of fixing defects rises sharply the later they are found, often causing significant business disruption. Bringing quality into the boardroom means recognizing that test automation drives both top-line growth and bottom-line efficiency.
The increase of AI-generated code puts QA teams in a bind. According to the 2025 State of Software Quality Report, the majority of teams are still at low levels of maturity, relying heavily on manual testing. Only 34 percent of companies have reached advanced maturity where AI boosts performance. Hybrid testers, who blend manual expertise with automation and AI, are emerging as the future of QA. They report 35 percent higher efficiency in defect detection and shorter cycle times compared with traditional testers.
The data also highlights a disconnect between aspirations and execution. While manual testing is used by 82 percent of respondents, only 45 percent practice automated regression testing. Teams that leverage AI tools are 2x more likely to invest heavily in automation compared with non‑AI teams. These gaps suggest that manual processes and limited automation are major barriers to scale.
At the same time, code volume is exploding. Low-code platforms and AI assistants accelerate delivery and unlock new levels of productivity. But with greater speed comes more integration points and edge cases to validate. Without matching advances in test automation, QA struggles to keep pace, turning into the bottleneck that slows releases and adds cost.
This ROI model illustrates how automation can transform QA economics. The model assumes an hourly engineering cost of $45, a 40‑hour work week and 48 work weeks per year. When you replace manual script development with TrueTest’s AI‑generated tests, effort savings range from 50 to 60 percent. For example:
Scenario |
Team size |
Effort saving |
Before TrueTest |
After TrueTest |
Savings |
ROI |
1 |
5 engineers |
50% |
$432,000 |
$266,000 |
$166,000 |
232% |
2 |
10 engineers |
50% |
$864,000 |
$482,000 |
$382,000 |
664% |
3 |
5 engineers |
60% |
$432,000 |
$222,800 |
$209,200 |
318.4% |
4 |
10 engineers |
60% |
$864,000 |
$395,600 |
$468,400 |
836.8% |
Source: Katalon TrueTest ROI template built based on actual customer results
These numbers are conservative because they only account for labor savings from script creation and maintenance. They do not include the cost of late defects, rework, customer churn or lost market opportunities. When you factor those in, automation with TrueTest becomes even more compelling.
In traditional sprints, teams typically rely on expensive test engineers who combine subject matter expertise with technical skills to create and maintain scripts. In the TrueTest model, sprint testers can focus on designing tests and executing them manually. TrueTest automatically generates the corresponding automated scripts, which eliminates the need for high‑cost software development engineers in test (SDETs) and reduces headcount. Because scripts are ready without manual coding, regression teams can shift from a maintenance function to a simple run‑and‑report role. This not only lowers labor costs but also frees up the budget for innovation.
Test automation script development often spills over into the next sprint because the automation engineers are juggling between automating tests for new features, maintaining tests from previous sprints and finishing the automation of new features from the past sprint.
TrueTest removes that bottleneck. Once manual tests are executed in the sprint, TrueTest generates automation artifacts instantly, enabling teams to finish within the sprint. Regression runs can start immediately after each sprint (or even before it ends) because there is no waiting for script development or maintenance.
By achieving in-sprint test automation, teams are effectively shifting left test automation, which leads to faster detection of defects and significantly lower remediation costs. Over time, shorter feedback loops translate to quicker releases and a more agile organization.
Manual testing teams often struggle to determine which scenarios truly reflect how users behave in production. When deployed to production, TrueTest monitors real user interactions and ensures that regression suites mirror actual usage rather than a team’s best guess. This approach closes the gap between real usage and test coverage. High‑risk business scenarios are validated before release, which reduces defect escape and protects revenue.
Beyond capturing common real user paths in production, TrueTest allows testers to focus on testing edge cases and negative scenarios in their normal testing in pre-production (DEV, QA, UAT, etc.) because they are no longer consumed by script writing.
By deploying TrueTest to applications running in pre-production and production environments the team is able to expand their requirements-based coverage and user-based coverage. This leads mature teams to deliver higher quality and prevent surprises post‑release.
Many tools promise automation, but TrueTest offers an AI‑augmented approach that aligns closely with how your users behave. Three capabilities set it apart:
These capabilities translate directly into strategic outcomes. You shorten time‑to‑market because testers spend less time maintaining scripts. You reduce costs by shifting automation work from highly compensated SDETs to SMEs and business analysts. You improve coverage and decrease the risk of revenue‑impacting bugs in production.
To unlock TrueTest’s full ROI, decision‑makers must treat automation as a strategic initiative. Here are steps to maximize impact:
Quality assurance is no longer a back-office function. It is becoming a board-level priority. TrueTest proves that AI-driven test automation delivers returns well beyond cost savings. Small teams can see ROI above 200 percent, and larger teams can exceed 800 percent, with additional gains from faster releases, fewer production incidents, and higher customer satisfaction.
The future of QA will be hybrid. Manual testing will continue to matter for exploratory work and human judgment, while automation and AI take on repetitive tasks and scale coverage. Mature teams are already moving in this direction. Organizations that act now will be better positioned to compete in an environment where speed and reliability are non-negotiable.
TrueTest is your partner in this shift. By closing the gap between pre-production and production, reducing maintenance, and aligning tests with real user behavior, it turns QA into a competitive advantage. Instead of slowing releases, QA becomes a catalyst for innovation. Bringing test automation ROI into the boardroom makes clear that software quality is not just an operational concern, but a cornerstone of your growth strategy.