Software testers’ AI adoption is at 78%, facing challenges in reliability and skills

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A new “Future of Quality Assurance 2023” study by LambdaTest of 1,615 software testing professionals from 70 different countries has shed new light on software testing practices in 2023, including finding that 78% have already adopted AI in their workflows.

LambdaTest’s new research has also shown that companies are working to respond to the need for greater software reliability with 72% of organizations involving testers in “sprint” planning sessions, signaling a substantial shift towards software quality being considered earlier in the software development lifecycle. However, small organizations are lagging in this metric with only 61.60% involving testers in every sprint.

Amongst these efficiency improvements, the survey shows that there has been rapid adoption of AI technologies. Uses of AI reported by software testers have included automating the creation of test data (51%), writing code for automated tests (45%), test result analysis and reporting (36%), and formulating test cases (46%).

Another key insight that the study revealed was even though 89% of organizations are automating the deployment and running of tests through CI/CD (Continuous Integration and Continuous Delivery) tools, only 45% of organizations are triggering their automated tests manually, and not effectively leveraging CI/CD tools to run tests.

The research has also highlighted that gaps continue to exist in software testing. 74% of teams lacked a structured approach towards running tests, thereby losing efficiency and potentially overlooking factors like risk levels and customer feedback. In addition, many teams lack data-driven insights in order to measure software reliability with more than 48% lacking even basic Test Intelligence and observability systems.

Asad Khan, CEO & Co-Founder of LambdaTest, said: “At LambdaTest, we understand that while the adoption of AI is a significant step forward, the journey doesn’t end here. For example; our study highlights the need to address bottlenecks affecting productivity like flaky tests alongside time wasted on setting up and maintaining test environments. This presents us with an opportunity as well as a challenge – to develop the right tooling that will empower teams to efficiently address these bottlenecks and drive software quality in their processes.”