The other day I was reading an article by QActions written by Alfonsina Morgavi titledQA/QC and RPA with AI Are Revolutionizing Software Testing (2026)and there’s a concept that stuck with me: the transformation of the tester’s role in the era of automation and artificial intelligence.
It’s not the first time I’ve heard that “testing is changing,” but the way it’s presented there is concrete, grounded, and—above all—actionable.
The evolution of QA: from manual testing to intelligent automation
For years, a tester’s job was to design and execute test cases: manual and functional testing, regressions, checklists, and bug reports. A meticulous, repetitive task that was often underestimated within software development teams.
Today, that model is falling short. Not because testers are no longer needed, but because QA/QC tools, automation, and AI-driven testing have evolved dramatically:
- Artificial intelligence can automatically generate test cases
- Automation platforms run regression tests without human intervention
- QA dashboards report real-time metrics
- Predictive testing tools detect risks before they occur
This completely redefines the role.
The new tester role: strategic thinking and decision-making
So, what’s left for testers today? The hardest (and most valuable) part: thinking strategically. The modern tester:
- Interprets results generated by automated systems
- Defines what to automate, in what order, when, and why
- Prioritizes risks based on business impact
- Collaborates with development, product, and operations
- Designs software quality strategies
It’s no longer just about finding bugs, but preventing failures and optimizing processes. Understanding business risks, collaborating across teams. The tester shifts from being an executor to becoming a quality orchestrator—managing processes, integrations, and intelligent agents to maximize QA/QC efficiency.
It’s a clear identity shift. The tester becomes a strategist. And that requires new skills.
QA + RPA + AI: the new architecture of software testing
As part of this transformation, QActions proposes combining RPA (Robotic Process Automation) with Artificial Intelligence as a core approach.
This creates a stronger blend of:
- QA/QC (Quality Assurance & Quality Control)
- RPA (Robotic Process Automation)
- AI applied to testing
In this model:
- RPA handles repetitive and structured tasks
- AI brings analysis, learning, and decision-making
- The human team focuses on quality strategy, analysis, and continuous improvement
This enables scaling testing processes, reducing operational costs, and sustainably improving software quality. This is not theoretical—real implementations already exist in companies of different sizes, including SMEs, showing significantly better results than traditional approaches.
Why this shift matters for companies and QA teams
Adopting AI-driven testing and automation is not just a technical improvement—it’s a strategic decision. It directly impacts:
- Time-to-market for digital products
- Reduction of production errors
- IT team efficiency
- End-user experience
- Scalability of quality processes
Companies that understand this early gain a clear competitive advantage.
The future of testing: testers as quality architects
We’re entering a phase where QA is no longer just a stage in the process, but a transversal system. The tester of the future:
- Designs testing ecosystems
- Orchestrates tools, bots, and AI
- Aligns quality with business goals
- Works with data, not just test cases
It’s a shift in professional identity—and a major opportunity for those who adapt.
Conclusion: measurable results in modern QA
If you’re thinking about how to move your team or company in this direction, it’s important to understand that this is no longer a future trend—it’s a current competitive advantage that requires immediate attention. Organizations that have adopted automated testing, RPA, and AI applied to software quality are already seeing concrete results. For example, solutions powered by Tricentis have shown the following KPIs across different success cases:
- Up to 90% reduction in test execution time
- Up to 85% increase in testing coverage
- Up to 50% reduction in QA operational costs
- Significant acceleration in delivery cycles (CI/CD)
- Reduced production risks in critical environments such as banking, retail, and telecommunications
Global companies such as Vodafone, Allianz, and Siemens have used these solutions to scale their quality processes, achieving faster testing cycles, more stable releases, and measurable improvements in customer experience.
But the most important factor is not the technology itself—it’s how it’s implemented. QActions not only understands tooling but also the business context in LATAM and global markets. Their approach combines strategic QA/QC consulting, automation implementation with leading tools like Tricentis, RPA + AI integration with platforms like Automation Anywhere, and end-to-end support in team transformation (not just technology).
This allows companies—including SMEs—not only to adopt new tools but to truly evolve their quality model. Because the real differentiator is not automation for the sake of automation, but automation driven by criteria, prioritization, and business alignment.
In a context where development speed is increasing and tolerance for errors is decreasing, continuing with traditional testing models is no longer sustainable. Moving toward modern QA is not just an operational improvement—it’s a strategic decision that directly impacts competitiveness, scalability, and growth.
FAQs about QA, testing, and AI-driven automation
What does a tester do today?
A modern tester no longer just executes tests but designs quality strategies, automates processes, analyzes results, and collaborates across multiple business areas.
Does artificial intelligence replace testers?
No. AI automates repetitive tasks, but the human role evolves toward analysis, strategy, and decision-making.
What is RPA (Robotic Process Automation)?
RPA enables the automation of structured tasks such as test execution, data loading, repetitive validations, and even operational/manual processes—reducing work that used to take days, weeks, or months to seconds or minutes.
What are the benefits of AI-driven automated testing?
- Faster execution
- Reduced human error
- Continuous testing (CI/CD)
- Improved test coverage
- Cost optimization
Is it only for large companies?
No. More and more SMEs are adopting automated QA and AI solutions to improve their competitiveness.
Adapt or fall behind
The change is already happening. Testing is no longer just execution—it’s strategy, automation, and intelligence.
If you’re considering how to move your team or company toward this modern QA model, exploring the QActions approach can be a concrete first step.
Get in touch with QActions.