In the new era of testing, where AI support is prevalent, demands on individual testers are increasing. Instead of focusing on one skill, the expectation is increasingly that people will have comb-shaped skill sets, with multiple areas of specialist knowledge arising from a single broad base.
Potential over-reliance on AI means that domain knowledge specialization is crucial. To effectively utilize information provided by LLMs – and to avoid AI hallucinations – you need to clearly understand your objectives. Only then can you leverage the vast amounts of information to improve your work.
Another aspect of being a multiskilled tester is adapting to the steady flow of new tools. You need to determine which tools are worth learning, which are useful for your project, and which are merely trending online. This year will see the introduction of completely new frameworks that will reshape testing, requiring an elastic approach to your toolset.
Always cited as one of the most important skills in QA, communication will become even more vital, along with a learning mindset that will improve your position in a team.