DEVOPSdigest

Enterprise technology has changed considerably over the last decade. Innovations such as AI, edge computing, and the IoT, once considered futuristic, are now part of everyday life. As technology advances, it's driving a shift in how applications are developed, tested, and maintained. Gone are the days when software testing was a checkbox mentality; today, it's a strategic imperative that requires stakeholder involvement from all business areas.

With that in mind, let's explore some key trends shaping the industry:

Test Cases Will Soon be Obsolete

Our complex technology environment means there are far too many possible tests for organizations to build and manage. Software testing companies are addressing this by enabling enterprises to run simulations and explore scenarios through a virtual model of the system or application. Generative AI technologies are taking this to the next level, allowing companies to define the full scope and letting the system determine how to perform the tests. This reduces the need for human involvement and ensures more comprehensive test coverage.

As with any AI application, trust and accountability are critical. For this to become more pervasive, the system must provide detailed reporting and analysis to demonstrate that it has performed exactly as intended and that its actions have thoroughly tested the system.

Enhanced Predictive Capabilities

Another area in which AI can assist is by mining the vast amount of data generated to help companies make more informed decisions. The intelligent algorithm can analyze these repositories and accurately identify patterns. From there, it can predict which areas are most prone to errors, enabling companies to prioritize their efforts. Additionally, AI-powered testing can spot issues or anomalies that manual approaches might miss — providing critical feedback that allows companies to rectify these problems before they impact users.

Testing AI with AI

As AI is increasingly embedded across enterprise applications, evaluating these systems via traditional methods will become more challenging. For example, you can't write fixed tests as the system is non-deterministic, so the only viable solution is to use an AI-based system to "chat" with the intelligent product.

Increasing regulatory scrutiny is another ramification of more widespread AI deployments. As this oversight continues, testing will increasingly be relied on to demonstrate compliance with the various global regulations. Expect to hear more about this in 2025 and beyond, with companies soon required to obtain an AI certification demonstrating what the technology in the system does — and that it works within the expected bounds. In addition, I think we'll see periodic assessments conducted to ensure the algorithm remains valid, that its findings are not biased, and that the outcomes meet specific country standards and policies.

The Sustainability Imperative

Sustainability is a driving factor in many procurement decisions, with 78% of executives(link is external) considering it very important. From a testing perspective, significant compute power is wasted when companies run a large volume of tests without determining whether they need to be performed in the first place. This is another area in which enhanced predictive capabilities can assist; if organizations can determine exactly which tests they need and run only those, they will save on energy consumption, better aligning with sustainability goals.

No-Code Systems Get a "Yes"

Low-code and no-code systems have become more common, and this trend will accelerate in 2025. There are various contributing factors, including the ongoing developer shortage, more complex technology necessitating domain-specific knowledge, and perennial cost-cutting. This is driving a shift to business testing, in which domain experts define the goals and rely on technology to perform the tests. No-code systems deliver collaboration and democratization benefits and help organizations align with Agile and DevOps methodologies.

The Road Ahead

These are just a few of the trends that are actively transforming software testing into a business priority. As they underscore, it's impossible to ignore AI's impact. At the same time, companies must be cautious to distinguish the hype from reality. There are certainly game-changing capabilities, but the term also describes technology bolt-ons that won't move the needle. And even when companies invest in the former, it's critical that they implement the necessary guardrails to ensure AI performs exactly as expected.

Software testing is a dynamic market that will continue to evolve as innovations like virtual and augmented reality, biometrics, and robotics become more mainstream. With change the only constant, companies must modernize their strategies to support current and future trends.