5 Software Testing Trends for 2025

Heads up: you won't see anything on our 'software testing trends for 2025' list you haven't seen before. AI and codeless testing automation, worries about cybersecurity, edge computing…

So, what gives? Why should you read our 'trends for 2025' article if the same old candidates crop up every December in tech blogs' yearly content schedules as reliably as a sweet, ugly-sweater wearing small-town love interest in a Hallmark movie?

It's a good question.

Our answer, in a nutshell: 2025, and the couple of years after, are when the emerging technologies we've read so much about the potential of will really come into their own.

The impact of these technologies maturing will have a huge knock-on effect on how businesses run their testing processes. What's going to seriously shake things up? Read on for our top picks.

1. More Automation, Driven by AI and Codeless Tools

Until recently, automation has been a double edged sword for complex test cases. Sure, automating the test means that it runs quicker, but when you have to write and maintain complex test scripts, how much time are you really saving?

With low-code, AI-driven testing solutions really coming into their own over the past couple of years, the percentage of testing you can automate effectively has shot up. Expect development teams to be ever keener to take advantage as AI testing tech arrives at full maturity - especially for longer, more complex tests like end-to-end testing.

Perhaps that's why AI adoption was the joint top investment priority for IT teams, according to GitHub's 2024 Global DevSecOPs Report, with 39% of respondents reporting some use of AI in their software development cycle already and (crucially) 39% more planning to implement it in the next year or two.

What benefits can teams expect from AI, low-code testing software? Here's a quick rundown of what they can do:

• Use machine learning to generate scripts based on plain English prompts, significantly reducing the time needed to prepare complex, end-to-end test cases
• Self heal or update test cases when changes are made to the application - say goodbye to flaky tests and tedious hours of script maintenance
• Analyze previous code to predict bugs and defects, allowing developers to take extra precautions when working on high-risk areas
• Search elements using plain English, so that you can pinpoint a particular component or snippet in seconds, rather than scrolling through endless lines of code
• Watch AI run your test in real time for ultimate insight into how users interact with your app - with automatic screenshots and recordings for reference.

2. Shift Left and Shift Right Testing

Traditionally, the testing phase sits towards the end of the software development cycle, after you've completed the majority of the development work and before your app goes live. Increasingly, software teams are seeing the benefits of moving past seeing testing as a distinct, self-contained phase - at both ends.

Shift left methodology integrates testing processes into the earliest stages of the development cycle for a continuous, 'little and often' approach to testing. This allows teams to fix issues earlier on in the process, when it is easier, faster (and by extension cheaper) to do so, reducing time to market.

Meanwhile, shift right methodology emphasizes the importance of continuous monitoring and testing once your app is in a production environment. A/B testing, feature toggling, and continuous monitoring tools all help you 'shift right' with your testing to catch errors quicker and respond faster than ever to user needs.

It's now easier than ever to integrate testing into every phase of the software development life cycle, thanks to a range of intuitive, affordable testing tools that use AI to speed up pre-production testing and offer post-production insights - which leads us to:

3. Saying Goodbye to External QA

Big Tech has been running just fine without dedicated testing teams for a while now. Other businesses are rapidly following suit.

The fact is that in a world where the ability to ship code quickly is a key competitive difference, separation between development and testing adds an unsustainable amount of delay and human error - particularly if you're outsourcing to an external QA team.

With so many more organizations shooting for absolute CI/CD, external QA is rapidly becoming an out-of-step relic that:

• Drains resources that could be spent on building new features or improving existing ones (would you say no to an extra $2m to spend on development talent?)
• Slows down release cycles, hampering high-performing development teams' agility and allowing your competitors to beat you to market
• Increases technical debt, because lack of developer involvement in testing produces hard-to-test code

Smaller tech firms have had to put up with the inconvenience of external QA a little longer (not everyone has a Google-sized pool of the best developers in the world, after all).

Now, however, increasingly advanced AI testing solutions have made fast, developer-led testing a conceivable reality for a much wider range of businesses. Expect more businesses to follow Big Tech's lead, into 2025 and beyond.

4. More Emphasis on Cybersecurity

Unfortunately, cyber attacks are getting larger, smarter, and more frequent.

With the probability of being targeted by cybercriminals becoming more of a 'when' than an 'if', your security practices have to be at the top of their game, all the time.

It's not surprising, given the state of play, that GitLab's 2024 Global DevSecOps Report suggests that 'security' (19%) and 'DevSecOps platforms' (17%) are the joint first and third investment priorities for IT teams worldwide.

Given the thousands of dollars in regulatory fines, lost business, and irreparable reputational damage a poorly managed security breach can cause, we reckon that security testing may well be the most visible software testing trend for the second half of the 2020s.

What will this look like?

Firstly, expect general testing practices to shift focus towards a 'security first' approach. Significantly more penetration testing, vulnerability scanning, and threat modelling will become increasingly common - especially with the ability to use AI to automate a larger percentage of your testing workload at minimal time cost.

DevSecOps - that's full integration of security practices into the DevOps pipeline - will also become more widespread. This will make it significantly easier to implement automated security checks at every stage of the software development life cycle, so that vulnerabilities are picked up early and fixed as soon as possible.

5. Adapting Testing Workflows to Edge Computing

Are we on the verge of another major shift in how businesses manage their IT infrastructure?

Driven by a thirst for ever faster performance, lower costs, and tighter security, businesses are moving increasing amounts of workload from cloud to edge computing. This moves data processing closer to the source (device) to minimize latency, maximize performance, and neutralize the impact a cyber security attack could have.

In fact, the technology is generating so much hype that, according to one report, the edge computing market size is set to double by 2029, to $32.2bn (from a base of $15.6bn in 2024), with some predicting that in the next few years, the vast majority of data will be generated outside of traditional data centers and cloud environments.

To really get the most out of edge computing, organizations need to make sure their applications can process data in real time, and work stably with or without an internet connection - so expect testing processes to evolve to accommodate more latency and resilience testing.

As many edge computing infrastructures will process real-time data from Internet of Things (IoT) devices, it's also likely that we'll see an increased focus on IoT testing concerns as a result - with more time dedicated to device security and interoperability.

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