Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

TestRail Releases Landmark Report on AI’s Role in Quality Assurance

Related Posts
1 of 41,242

The first-of-its-kind survey of over 1,000 QA professionals highlights AI adoption, productivity gains, and the future outlook of AI-driven testing strategies.

TestRail, the leading dedicated QA test management platform, today announced its latest report, “Exploring the Impact of AI in QA.” Based on the QA industry’s first AI-focused research survey, this comprehensive report draws on insights from over 1,000 QA professionals and aims to cut through the hype surrounding artificial intelligence, offering a clear and accurate picture of how QA teams are adopting, planning for, and responding to AI technology.

“Although it’s still early to gauge AI’s full impact on QA, we think the future looks bright”

The research explores AI’s applications in areas such as regression testing, test automation, and performance testing, revealing how AI is helping teams increase efficiency, improve test coverage, and enhance overall quality.

Also Read: alt.ai Revamps Generative AI–based Qualitative Research Tool “Asclone

Key Insights from the Report:

  • AI Adoption and Success: A significant 65% of survey respondents reported using AI in their QA processes, with AI being applied uniformly across various testing types. However, certain use cases show more potential than others.
  • AI-Driven Productivity Gains: Over 50% of respondents reported increased productivity and improved test coverage, underscoring AI’s potential to enhance testing efficiency.
  • AI’s Versatility: AI is proving effective across various testing types, including regression, smoke, and performance testing. It is being used to generate test cases, execute tests, and analyze results, allowing human testers to focus on strategic tasks.
  • Barriers to Adoption: Despite high adoption rates, challenges like AI’s complexity, concerns about data privacy and security, and uncertainty about its benefits continue to hinder broader implementation.
  • Actionable Tips: The report also offers practical tips, strategies, and prompt ideas from industry experts and survey respondents, empowering QA managers to start leveraging AI in their own processes today.

Most importantly, the report also details the QA community’s overwhelmingly optimistic outlook on the future of AI, despite adoption challenges—a perspective that TestRail fully supports.

“Although it’s still early to gauge AI’s full impact on QA, we think the future looks bright,” said Judy Bossi, VP of Product at Idera. “Like test automation before it, we’re optimistic that AI will not only speed up release cycles and improve software quality but also empower testers to spend more time on tasks that require human insight and intuition. As long as software is made for people, the human element in testing will remain essential.”

TestRail invites you to download “Exploring the Impact of AI in QA” and gain valuable insights from 1,000 QA professionals about how artificial intelligence is transforming their current QA processes and future strategies.

Also Read: Why Responsible AI Principles Matter for Advertisers

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

Comments are closed.