Software development is evolving at a breakneck pace, and 2025 is ushering in a new era for Quality Assurance. 

Software testing and QA are not just about ‘detecting bugs’ anymore. New technologies introduced regularly highlight the importance of QA on a whole new level. And thanks to its increasingly important status, software testing represents a fertile field for innovation and experimentation, which leads to a regular induction of new technologies into the fold.

In this guide, we will introduce some of the most notable trends in technology that are expected to make waves in the industry this year. Explore the new trends for software testing in 2025 and see how the technologies are designed to reduce risks, boost quality, and optimize performance in a faster and easier way.

Testing Evolution

Software testing has come a long way.

From the waterfall methodology and manual methods to automated, AI-driven software, it’s hardly recognizable to experts who pioneered testing processes back in the day.

What started as a reactive process, performed only after software development, now is an integral part of the development.

The past few decades were all about the bulky tools and experimental methods designed for trial and error.

Today, however, the situation is a bit different. In the last few years, the focus has shifted to automation, cloud computing, and artificial intelligence, with ‘smart technology’ as the keyword.

That’s why AI and machine learning (ML) are one of the imminent trends in software testing. But that’s just one of many trends set to dominate the industry and global markets in 2025.  All technologies share two main goals: scalability and cost-effectiveness.

Software testing is an integral part of software development, so there’s a huge demand for refining and optimizing testing processes. Hence, new technologies and platforms emerge every year, each designed to shorten the process and make lives easier for testers and developers.

Here’s an overview of testing trends expected to go viral in 2025:

Let’s review each trend and see how it could affect the software testing industry in 2025.

AI & ML Integrated Testing

AI and ML changed the game when they were first introduced in software testing. They also continue to impact the industry – so much so that 2025 is lauded as a key year for innovation in AI-based testing.

The main three roles of AI & ML integration are smart test case generation, anomaly detection, and predictive analytics.

AI is already essential for generating test cases, but a combination of AI and ML can further push the process to a new level.

So far, ML has found its purpose in the detection of patterns and defects. When combined with AI, ML testing gains traction and could grow beyond its limits, offering better prediction that is not only faster, but also more accurate.

As a result, a blend of ML and AI offers a slew of benefits, including but not limited to the automation of scripts, more efficiency in detecting anomalies, a wider scope and better speed of testing, and more flexibility overall.

AI testing can crunch huge amounts of data in less time than ever before, which helps expand the scope and accuracy. On the other hand, the defect detection algorithms are more sophisticated, which means they can predict potential points of failure faster and better.

AI-based tools such as Testim, Applitools, and Functionize are expected to spearhead AI and ML testing in the future.

IoT Testing

The Internet of Things (IoT) global market size was estimated at $500.86bn in 2024. Plus, it is predicted to grow from $618.37bn in 2025 to $3,644.20bn by 2034. In other words, not only is the IoT market not slowing down, but it’s actually accelerating in growth year by year.

A large portion of that is IoT testing. In fact, the IoT testing market is expected to grow to $30

40bn by 2032, reaching a compound annual growth rate of 32.6% from 2023 to 2032.

What all this translates to is an array of complex challenges for IoT testing, because of the diversity in devices and platforms. As the number of devices grows, so does the need for efficient testing methods that can ensure and maintain security and functionalism.

Simply put, IoT testing ensures that devices are working properly, and in harmony with each other, all the while maintaining security across all networks.

Some of the main strategies for IoT testing are:

  • Security validation
  • Functional testing
  • Compatibility checks
  • Real-time monitoring

In 2025, most of the focus with regards to IoT testing lies on security testing services which are backed by methods such as penetration testing and vulnerability analysis.

Another great way to optimize IoT testing is to prioritize edge computing. Processing data closer to the source decreases latency and shortens response times.

Tools such as Mobot, QA Wolf, and Bevywise IoT Simulator are expected to become the go-to tools in 2025 and onwards.

Accessibility Testing

Accessibility testing is a subsection of usability testing focusing on ensuring content is adjusted for people with disabilities. In simple terms, accessibility testing ensures that online (mobile/web-based) content and apps are suitable for people with various disabilities – visual, speech, learning, auditory, physical, etc.

Unlike usability testing, which greatly focuses on the ease of use and efficiency of the product, favoring a user-centric configuration, accessibility testing is oriented towards assistive technologies and how end-users access the content. Not to mention, accessibility testing is limited by accessibility laws.

One of the main goals of testing is to ensure everything is working in compliance with WCAG (Web Content Accessibility Guidelines), the Americans with Disabilities Act (ADA), and similar relevant accessibility regulations.

Although this is actually not a new trend, it is slowly becoming a priority. In fact, the accessibility testing market has noted a steady growth progression, with estimations of a CAGR of 4.32% for the 2024-2032 period. By 2032, the global market is expected to reach $825.43m.

Today, accessibility testing covers several strategies and methodologies, including testing for screen reader compatibility, keyboard navigation, and color contrast for visually impaired end-users. However, because accessibility is expected to become an even bigger priority, testing will surely expand to cover other methodologies.

Some of the ways in which accessibility testing might go are AI testing tools, as well as automation testing.  These can provide support for testing functionalities such as captions and magnifiers.

Shift-Left Testing

Shift-left testing includes introducing testing in the earliest stages of the software development lifecycle. The name was introduced in 2001 and refers to the practice of moving testing to the left side of the timeline if the development process is perceived as linear.

As a result of incorporating testing early on, the anomalies are dealt with right from the start, which positively affects the quality of software.

Because of this, shift-left testing is an approach that is widespread today.

And with good reason. Shift-left testing has a few perks.

For starters, it’s great for avoiding the pitfalls of delayed testing. That includes the mistake of leaving insufficient funds for testing during the projects. If testing starts early (on time), it’s easier to ensure there are enough funds for the testing phase. It also tackles the issues of defects in design, difficulty debugging, and many other flaws that could easily result in project delays.

Introducing testing at an early stage and performing it often improves the overall software quality, expands test coverage, and provides ample feedback, allowing companies to market the products faster.

Four Types of Shift-Left Testing

There are four shift-left approaches to software testing. Here are the four ways to move testing to an earlier stage of the lifecycle.

  • Traditional shift-left testing (Standard testing practices introduced early)
  • Incremental shift-left testing (Testing in increments during development)
  • Agile/DevOps shift-left testing (Testing used continuously in Agile and DevOps)
  • Model-based shift-left testing (Testing executable models)

Agile/Dev Ops and Model-based shift testing are the newer variants of shift-left testing. Thanks to their methodology, both approaches allow a faster start of testing, with model-based shift-left testing starting almost immediately instead of waiting for a large part of the software to be developed first and only then tested. Because it’s nearly instant, model-based shift-left testing is currently the most popular.

Scriptless Test Automation

Automated testing is a major part of the reason why we have fast and cost-effective software testing.

Thanks to test automation, manual tests became obsolete. Automated testing shortens testing times and eliminates the need to use human, mistake-prone testing that’s not only slow but also expensive.

Moreover, newer trends in software testing like shift-left testing have influenced test automation as well.

One of the focus approaches in 2025 will be scriptless test automation, which allows testers to test software without substantial coding.

In simple words, low-code or no-code testing is a form of automated testing that requires little to no script writing, completely changing the game in software testing.

There are a few major benefits to this approach.

First of all, this method does not use record and playback. Instead, a model of the product is built, and the tester can simply incorporate parameters and conditions to generate test cases. The tester does not need any special skill in scriptwriting.

Hence, it broadens the scope by allowing testers who are not well-versed in code writing to participate in testing, further shortening the process of testing and making it faster.

Hyper Automation

Scriptless test automation is just the beginning. Other forms of automation testing that we could see grow in 2025 and onwards follow the hyper-automation trend and include End-to-End Automation, Robotic Process Automation in QA, and continuous testing.

Repetitive tasks are handed over to bots to execute efficiently with increased accuracy. Popular RPA tools include UiPath, Automation Anywhere, Blue Prism, etc.

Regression Testing

Another trend for 2025 is an increased focus on regression testing. As apps continue updating, it’s important to ensure that new code changes do not introduce anomalies in existing functionalities. It’s virtually a never-ending process that’s always in demand, considering the pace of launching and updating apps and features. In 2025, it’s going to become even more pronounced.

The importance of regression testing is both a blessing and a curse for developers. It’s crucial, but it’s also quite delicate, and there are so many things that can go wrong during the testing process. However, the first and biggest issue developers must tackle is speed.

Simply put, regression testing is time-consuming, as it requires resources, trained staff, knowledge, and skills with complex systems to be executed properly.

It is believed that 2025 is bringing in a revolution for regression testing that could shorten the process and make testing easier for everyone.

Currently, the most popular automated regression testing tools include Watir and Testlio, as well as Katalon.

Automated Mobile Testing

Mobile technology keeps growing with each new day. With new technology come new challenges, as well as problems that need to be tested and ultimately fixed.

However, as the pace of progress keeps accelerating, so does the need to optimize mobile testing. This brings us to mobile testing automation.

Mobile app testing ensures applications for portable devices function correctly across different devices, operating systems, and network conditions. However, as apps become increasingly more complex, so do the market demands. They highlight the importance of mobile testing not only with coverage but is also fast and efficient.

An obvious solution to the problem is cloud-based mobile testing. Keep an eye out for these tools:

  • AWS Device Farm
  • Sauce Labs
  • BrowserStack

These tools are the key to elevating mobile testing to new heights. Cloud-based testing is an excellent method because it provides unmatched flexibility, speed, and most importantly, scalability.

Since the global mobile application market size is growing – it was valued at $252.89bn in 2023,  and is projected to grow at a CAGR of 14.3% from 2024 to 2030 – having infinite scalability could be a fantastic way to balance out such explosive growth.

Security Testing

Security is always in focus, but recent years have shown us that the demand for safety and privacy is now bigger than ever.

Not only that, but it will keep growing, especially online.

Cybersecurity threats, data breaches, and other similar events have encouraged developers to bolster their efforts in designing safety-first testing methodologies, such as:

  • Penetration testing
  • Risk assessment
  • Vulnerability scanning
  • Ethical hacking
  • API testing

As companies cast more attention to security, experts also expect to see growth in hiring in-house or outsourced security testing teams, too.

DevSecOps goes hand in hand with increased security testing efforts. The main goal of DevSecOps is to incorporate a bigger emphasis on security during the developmental lifecycle. This is just one of many changes expected in the future when it comes to cybersecurity.

Blockchain Testing

Blockchain QA is evolving too.

In the next few years, we can expect to see growth in AI-powered tools that focus on smart blockchain testing. Mythril, OpenZeppelin Defender, and Certik AI are key tools for smart contract audits focusing on contract verification and similar procedures.

Other key areas include regulatory compliance, advanced simulations, inoperability testing, and Zero-Knowledge Proof (ZKP) testing.

Some of the tools that could become prevalent are:

  • Tenderly, Hardhat (Advanced simulations)
  • Circom, SnarkJS, and Zokrates (ZKP)
  • LayerZero, Cosmos IBC, and Polkadot XCM (Inoperability testing)

Integration Testing

Integration is integral to software development. Therefore, integration testing is the final piece of the puzzle ensuring even the tiniest piece is working properly together with other elements.

Right now, there are two main approaches to integrated testing:

  1. The Big Bang Approach
  2. Incremental Approach

Integration testing validates data flow and how different system components interact with each other. To create a smoother experience, integration testing focuses on processes such as:

  • Broken module identification
  • Issue detection
  • Early testing problem detection

It’s far from being a new practice, but experts predict it will become one of the main trends in the next few years as software becomes more sophisticated and complex.

Crowdtesting

Crowdtesting is another method that is probably going to become big in 2025.

Crowdtesting refers to testing performed by a group of testers who are not employed by the company’s QA team. It’s actually a diverse group of testers that are testing products in real-world conditions. In a way, it’s the complete opposite of outsourcing.

This is actually a very good practice as all participating testers are experienced and can access different platforms/devices to test. Organizers – the companies that require crowdtesting – enlist the help of testers and communicate with them using various crowdtesting platforms such as Global App Testing, Testlio, Cobalt, and others.

Thanks to these platforms, the testing process is shorter. The testers go through test cycles rather quickly, and often before the product hits the market and end-users. Not to mention, it’s cost-efficient, which makes it a perfect candidate for a software testing trend in 2025. There is also the fact that these platforms cover a variety of testing technologies and methods, which might suit companies from different walks of life.

However, crowdtesting is not without its challenges. Although it sounds like a perfect solution to many problems – it could result in a lower-than-expected quality of the results.

Testers may be beginners and/or inexperienced with the product, which leaves room for making mistakes. And if testers change often, the issues will persist.

Crowdsourcing vs Outsourcing

Crowdsourcing and outsourcing are two different things. See below the main differences between crowdsourcing and outsourcing testing.

Crowdsourcing Outsourcing
Team working worldwide Team employed in-house
Testers are independent Testing delegated to third-party companies
Diverse, real-user experiences Dedicated, professional testing services
No schedule, work anytime Work hours and shifts set
No fixed costs Fixed costs
Flexible staff, employed separately Fixed staff, employed as a team

While outsourcing offers companies a more professional testing service, crowdsourcing expands the scope and coverage, making it faster and cheaper. But in the end, the choice will depend on the type of product that is being tested.

While all mentioned testing trends offer increased efficiency, not all are geared towards optimization. In other words, some challenges arise with all testing methods, especially those that are still mostly unfamiliar to wider audiences.

AI and ML testing is great for improving test coverage and accuracy. However, one of the biggest challenges for testers is currently the lack of specialized knowledge and expertise. Simply put, there’s a high learning curve. What is more, testing also requires large datasets, which may not always be available.

IoT testing comes with its own set of obstacles. The first and major one is the complex ecosystem of platforms, devices, and communication protocols which is not easy to navigate. Not only that, but it’s also very prone to cyberattacks, which is when security methodologies are paramount.

Speaking of security, cloud-based testing is very vulnerable too. Because of data privacy concerns, compliance with industry regulations and data protection laws is the first step in ensuring safety – especially when storing sensitive data in the cloud.

Taking all this into consideration, it’s evident that software testing has a long way to go and lots of room for improvement – especially when it comes to testing speed, cost-efficiency, data privacy, and staff training.

Here are some tips on how to stay ahead in testing and ensure you are always picking the optimal solution in software testing.

  • Staying in the loop: Keep your ear to the ground and try to stay on top of all new tools and methodologies that emerge.
  • Shifting to early testing: If you can, try to implement shift-left testing practices, especially if you are interested in trying new methods.  
  • Hybrid testing: If one or two methods don’t work, try a combination. Combine manual, automated, and AI-driven testing for optimal results.
  • Opt for scalability for test environments: Cloud-based testing allows scalability which is perfect for systems that are continuously expanding.
  • Security is paramount: Integrate security into every phase of development and switch to security-first methods to ensure data privacy and safety.

Conclusion

It’s hard to tell where exactly the evolution of software testing is headed, but one thing is obvious: faster, more efficient, and user-centric testing methodologies are the go-to answer.

AI is certainly going to take over an even bigger role in software testing, and combined with ML, could push the market forward with better security, accuracy, and scope.

Wherever the future takes us, the TechTailors team is sure to be ahead of the curve.