Key Automation Testing Trends Transforming Australia’s Tech Industry in 2026

Small & medium-sized businesses across Australia are more concerned about the product as they stay ahead into 2026. According to the report, IT spending in Australia will reach $172.3 billion by 2026. The latest QA testing trend in Australia focuses on the quality validation, improved automation & utilization of AI to drive testing workflows. Australia is making steady progress as it is expected to grow by 12.3% in the next 4 years.

Australian companies are shifting from traditional QA to automated continuous testing. Automation testing services in software development are frequently evolving at a rapid pace. The worldwide software industry is rapidly driven by modern technologies. Organizations concentrate on driving security, flexibility & real-time processing abilities to keep current.

QA automation is making a significant revolution as we are moving into the year 2026. The demand for fastest deployment, seamless user experience & test automation framework is pushing enterprises to embrace cutting-edge technologies. By adopting this approach, businesses can speed up bug detection & drive software quality. As enterprises are frequently adopting future QA trends, they are ensuring to stay ahead in the evolving landscape.

In the following blog, we’ll explore the latest trends in automation testing that support businesses in limiting costs and speeding up software deployment.

1. Rise of AI-Driven Test Automation

● Smarter Test Case Generation

AI test generation is becoming a buzzword in the upcoming years. It’s a quick shift how the modern QA team ends up with designing, validating & maintaining tests. The QA automated software testing services team depends on the automated test case generation due to LLM. It includes changing app behavior, user stories & well-structured test cases with necessary steps. This methodology offers improved test coverage, decreased human errors, and app speed.

Earlier, the manual QA team reviewed various design documents to describe the steps & expected results. However, with the emergence of test case automation generation, the advanced systems have removed the manual burden of optimizing & maintaining test cases automatically. AI-driven test automation testing trends expand test coverage, transform requirements into executable tests, and lower maintenance by self-healing with a person in the loop to guarantee accuracy.

AI test generation is revolutionary, but in order to guarantee value, maintainability, and correctness, QA automation testing services teams must manage some risks. This analysis greatly lowers the requirement for manual labor and the possibility of human error by automatically generating test cases that span a variety of scenarios and edge cases. Additionally, AI is essential for improving bug tracking. The bug tracking technologies have the ability to prioritize problems, forecast their severity, and even recommend fixes. Find out more about how ML & AI affect bug tracking.

● Predictive Defect Analysis

In addition to increasing dependability, AI defect prediction in software testing enables teams to allocate resources more efficiently, concentrate on the most important components, and speed up release cycles. Predictive AI agents are emerging as an important component of proactive QA automation services strategies, ensuring that quality is included in the product from the start, as businesses progressively adopt DevOps and agile methodologies.

The application of modern data-driven methods and algorithms to identify defects before they manifest in production is known as AI defect prediction in software testing. It uses intelligent models to examine code metrics, historical information, and patterns of previous problems rather than depending exclusively on human testing or reactive fault discovery.

The goal of early identification of high-risk software components is to help QA teams strategically concentrate their testing efforts. These algorithms proactively detect and avoid future errors by recognizing current problems and future failure areas, improving the overall efficacy of AI in automation testing procedures. AI-powered security testing skills, for instance, are included in sophisticated software testing tools to enable proactive vulnerability detection in crucial domains like cloud-based apps, blockchain networks, and APIs.

Also Read : Automation Testing Frameworks That Help Enterprises & Startups

2. Expansion of Low-Code / No-Code Test Automation

● Democratizing Test Automation

Low-code/no-code platforms enable non-technical employees, such as product owners and business analysts, to take part in testing. This change speeds up feedback loops and eliminates bottlenecks, particularly for smaller teams with fewer QA resources. Low-code automation is used by 84% of businesses to expedite delivery and lessen the load of IT.

Low-code QA automation technologies are being used in Australia’s logistics and agriculture tech sectors to enhance testing without the need for specialized testers. These tools increase testing’s speed, scalability, and accessibility for all parties. Automation is created by any member of your QA team. Automation contributors replace manual testers. Business analysts use automated tests to verify their own requirements. Your automation capacity is multiplied five to ten times by this democratization.

Automated tests can now be designed and maintained by business analysts, manual QAs, and even product owners who are familiar with the functionality of the application but do not know how to code. By increasing the number of automation contributors, this relieves strain on specialized automation engineers and frees them up to concentrate on more difficult, complicated automation jobs.

● Rapid Prototyping and Deployment

You can construct an MVP, test it with people, and improve it in a matter of minutes rather than waiting for lengthy development cycles. These current trends in automation testing improve user experience while lowering risk. LCNC platforms enable a wider group of stakeholders, such as business analysts and product owners, to take part in the testing process by democratizing test automation.

Better communication between the development, quality assurance, and business teams results in shorter iterations and feedback loops. Numerous platforms have one-click deployment options, performance monitoring, and automatic quality checks that minimize human mistakes and manual labor. Applications are guaranteed to uphold quality standards throughout their development lifecycle thanks to continuous integration and delivery features.

➢ Testim

Testim is a low-code/no-code test automation solution driven by AI that makes it easier and faster to create, run, and maintain automated tests, especially for mobile and online apps. It seeks to make test automation available to more people, even those who don’t have a lot of programming experience.

➢ Katalon

Katalon is an all-inclusive, AI-enhanced test automation platform that facilitates no-code and low-code testing methodologies. It is designed to serve a range of users, from novice programmers to seasoned professionals.

➢ Leapwork

The goal of Leapwork, a no-code test automation platform, is to streamline and expedite the development, implementation, and upkeep of automated software tests. Both technical and non-technical users can create automation flows without writing code because of its visual, flowchart-style interface.

3. Increased Adoption of Cloud-Based Testing Platforms

☢ Scalability and Flexibility

A change in QA software test automation services techniques is being driven by Australia’s use of cloud-native system apps. The volume and complexity of these distributed systems are simply too much for traditional testing techniques to handle. As more companies use cloud-based testing, many are witnessing 10x faster test cycle times and 60–70% lower infrastructure expenses. You can use the cloud to do automated software tests.

You can execute test scripts, simulate tests, and receive real-time results in cloud-based test environments. You can test many setups at once using the majority of cloud-based test automation solutions because they allow you to run tests in parallel.

Additionally, you may incorporate your cloud testing solution into your continuous integration and deployment (CI/CD) pipeline so that each code change is automatically tested before going online. Testing teams may dynamically scale their environments up or down based on project requirements, thanks to cloud platforms and the latest automation testing trends. This removes the physical constraints of internal labs and is particularly helpful for load and performance testing, which requires replicating large volumes of traffic.

➢ BrowserStack

Automation testing service developers can test websites and mobile applications on a variety of genuine browsers, devices, and OS using BrowserStack, a cloud-based testing platform. This reduces infrastructure expenses by removing the requirement for developers.

➢ Sauce Labs

Web and mobile application testing may be done both automatically and manually with Sauce Labs, a cloud-based tool. It gives team access to a variety of real devices, browsers, simulators, and emulators, enabling them to test for performance and compatibility in numerous scenarios at once.

☢ Cost Efficiency for Startups and Enterprises

Because cloud-based testing platforms eliminate the need for costly physical infrastructure and employ a pay-as-you-go model that aligns expenses with real usage, they are becoming more and more popular among startups and corporations. Additionally, by lowering maintenance costs and enabling businesses to adjust their testing resources in response to demand, this strategy further optimizes expenses and enhances scalability. Organizations won’t invest in servers, licensing software/hardware for testing environments.

All required resources are provided by the cloud provider, converting a significant initial capital expenditure into an ongoing expense. Both startups and companies gain from quicker deployment and lower operating expenses, while startups’ initial capital expenditure is greatly reduced. Hardware upkeep, updates, and management are essentially eliminated because the cloud provider takes care of these things. This lowers operating overhead and frees up IT staff.

4. Shift-Left and Shift-Right Testing Integration

☢ Emphasis on Early Testing (Shift-Left)

An approach to change in software development, shift-left testing emphasizes the value of early and ongoing testing. Teams may find and fix problems more quickly, enhance teamwork, and produce software of a higher quality by incorporating QA activities earlier in the development cycle. Although shift-left testing can be difficult to execute, the advantages greatly exceed the disadvantages.

Adopting this strategy can greatly increase the efficacy and efficiency of the QA process, which will ultimately result in more successful software projects when combined with the appropriate tactics and resources. Mobile app developers can lower the risk of security breaches and make the application more resilient to potential attackers by integrating security testing into the shift-left strategy.

The mobile application’s overall security and dependability are enhanced by this proactive strategy for automated software testing services. The shift left testing approach is a desirable choice for mobile app developers wishing to improve their software development processes since it helps ensure that software is of high quality and satisfies end users’ needs while reducing the expenses and time needed for software testing.

➢ Jenkins

By automating early and frequent assessments in the SDLC, such as building, testing, and security inspections, Jenkins acts as a key tool for putting a “shift-left” method into practice. It enables automatic validation and interfaces with other programs.

➢ GitLab CI/CD

As part of the CI/CD pipeline, GitLab has integrated security scanning technologies that can be set up to operate automatically, frequently in response to merge requests. This makes it possible for engineers to get quick feedback on code vulnerabilities.

☢ Focus on User Experience (Shift-Right)

Shift Right testing stresses ongoing testing and validation in production settings, whereas Shift Left testing concentrates on early problem discovery. This strategy entails keeping an eye on how the program behaves, getting feedback from users in the real world, and using user insights to inform incremental post-release enhancements. Shift Right testing has a revolutionary effect on contemporary software development, which makes it significant. After release, testing in real-world settings offers vital insights into performance and user experience.

Shift Right testing assists companies in producing goods that closely match customer expectations by continuously observing and improving the user experience throughout production. In today’s software sector, keeping a competitive edge requires a focus on customer pleasure and retention. Gaining a competitive edge in the current market requirements offers an impressive user experience.

➢ Dynatrace

By offering observability and AI-driven insights into applications following production deployment, Dynatrace functions as a potent “Shift Right” tool. It enables teams to swiftly identify and fix real-world problems that can go unnoticed during pre-production testing, confirm releases, and continuously monitor performance.

➢ New Relic

The New Relic platform offers performance insights, real-time statistics, and post-release user behavior tracking.

5. Hyperautomation in QA Processes

● Integrating RPA with Test Automation

QA procedures can become more proactive rather than reactive with the use of hyper-automation technology. In order to anticipate such errors before they happen, tools incorporating AI and ML algorithms can examine past data, user behavior, and code modifications. The demands of constant delivery and deployment pipelines are ideally aligned with this move towards predictive quality management. Hyper-automation also guarantees security and compliance as companies depend more and more on digital ecosystems.

Automated procedures protect sensitive data and keep an eye on regulatory compliance in real time. By integrating several cutting-edge technologies to automate and optimize the full testing lifecycle, hyperautomation in QA, one of the top test automation trends, goes beyond conventional test automation. RPA is the foundation of hyperautomation testing. RPA bots can execute test cases, enter data, and generate reports, freeing up human testers to concentrate on tasks requiring planning.

● End-to-End Test Lifecycle Automation

Complex digital ecosystems with numerous integrations may be tested smoothly thanks to hyper-automation. For instance, booking systems in the travel sector need to interface with payment gateways, hotels, and airlines. End-to-end workflows can be automated with RPA bots and API testing tools, guaranteeing that itinerary modifications, payment validations, and booking confirmations go smoothly. This shortens time-to-market and improves operational efficiency by doing away with manual intervention in multi-layered testing scenarios.

User experience testing becomes more dynamic and informative with hyper-automation. AI systems create test cases that mimic genuine usage patterns by analyzing user behavior in the real world. A streaming service like Netflix, for instance, might mimic user activities during periods of high traffic by using AI-driven technologies.

By automatically detecting bottlenecks and suggesting improvements, these tools keep an eye on performance measures like load times and streaming quality. In today’s rapidly evolving digital environment, QA test automation trends can produce software that satisfies both functional and experiential requirements by refocusing on strategic decision-making rather than routine tasks.

6. Greater Focus on Security Testing Automation

● DevSecOps Practices

Only 29% of businesses have successfully switched from DevOps to DevSecOps. The DevSecOps best practices enable you to create secure software without slowing development. Most of the IT team finds it difficult to smoothly incorporate security into workflows. Agility and quickness are given priority in traditional DevOps. However, vulnerabilities accumulate when security is neglected, raising risks and compliance issues.

DevSecOps, on the other hand, integrates security throughout the entire process from design to coding, testing, and deployment to assist you in mitigating risks before they become time-consuming issues. It is now essential to switch from DevOps to DevSecOps due to the constantly changing cyber threats and more stringent requirements. Manual code reviews and compliance checks are examples of security testing that might take days or weeks to complete.

In order to speed up vulnerability assessment without impacting application development, automation in security testing is a must. To conduct automatic scans and spot problems as they arise, select a security testing platform that provides automated testing. You can continuously evaluate vulnerabilities, get real-time alerts, and reduce interruptions with these automated security testing tools for DevSecOps teams.

➢ Snyk

Snyk is a security platform that prioritizes developers and automates security testing at every stage of the SDLC. It seeks to shift security left in the development process by assisting developers with identifying and resolving vulnerabilities quickly and effectively.

➢ OWASP ZAP

The OWASP created OWASP ZAP, a popular open-source online application security scanner and penetration testing tool. It is designed to assist in measuring security errors in a web app.

● Compliance-Driven Testing

Using automated techniques to continuously confirm that software satisfies security and regulatory requirements throughout the development lifecycle is known as security testing automation for compliance-driven testing.

Organizations may automate checks to identify and address security breaches early. It guarantees policy compliance and upholds compliance with international requirements by incorporating technologies into the CI/CD pipeline. This method ensures constant adherence to security and compliance requirements and provides real-time feedback by automating the development methodologies.

Also Read : Top Performance Testing Companies in Australia

7. Surge in Mobile Test Automation

☢ Growth of Mobile-First Apps in Australia

Australia’s rapidly expanding mobile-first app industry, which is supported by high smartphone penetration and rising corporate investment in mobile solutions, is the driving force behind the rise in mobile test automation. In order to stay up with shorter development cycles and satisfy customer demand for seamless experiences, quality assurance has become increasingly important. Due to this expansion, especially in industries like healthcare and fintech, it is getting popular. This has led to new trends in automation testing towards more automation, including AI-driven testing.

☢ Popular Tools and Frameworks

➢ Appium

Appium, the open-source program, serves as a server that makes use of the Selenium WebDriver API, enabling programmers to create tests in a variety of languages, including JavaScript, Python, and Java. It is a versatile and effective option for mobile app test automation because of its cross-platform compatibility. It has the ability to test without recompiling the app, and connection with well-known testing frameworks.

➢ Espresso

Espresso testing is crucial because it makes it possible to create trustworthy Android UI tests. Espresso Android automatically synchronizes your test actions with your application’s user interface. Developers can create a test suite as a stand-alone APK with Espresso testing. This APK can be instantly installed on the target devices along with the application being tested.

➢ XCUITest

XCode includes the XCUITest framework. This makes it simple to create UI tests that mimic how users interact with the program. A powerful automated UI testing solution for iOS automation testing, the XCUITest framework was introduced by Apple in 2015.

Is your QA team ready for 2026? Contact us to stay ahead of the curve.

Test automation brings a comprehensive change, ensuring software quality and performance. Some of the most common practices nowadays that enterprises are adopting are AI-powered testing, 5G network testing, and IoT automation. By embracing these automation testing trends, enterprises can deliver scalable, reliable software.

Companies are integrating a security-first framework and low-code development practices to dominate the future of the software landscape. If you are ready to optimize the QA trends in automation testing strategy, accelerate the release cycle, you must embrace these technologies to scale your organization, ensure reliability & minimize time to market.

The future of QA automation is promising thanks to the cloud platforms, AI, ML, IoT, and low-code/no-code approach. As businesses are expecting faster release, QA teams are finding ways to optimize the testing process, ensure error detection & regular feedback. Integrate the above-discussed trends into your software test automation services to make your QA testing journey future-proof.