SmartBear announced AI enhancements for API testing, UI test automation, and test management across its product suite, the SmartBear Application Integrity Core™.
Almost All Teams Use AI in Testing, but Only 12% Have Reached Full Autonomy
March 13, 2026
AI has become central to modern testing, but practical gaps are slowing adoption, according to State of AI in Software Testing 2026 from BrowserStack.
Based on insights from over 250 software testing leaders, the findings point to a widening gap between AI adoption and operational maturity. While most teams embraced AI, many remain constrained by fragmented workflows and uneven integration, limiting scalability and business impact.
"Too many teams think adopting AI is the finish line, when it's really the starting point," said Nakul Aggarwal, Co-founder and CTO of BrowserStack. "The real work is integrating it into everyday workflows, training teams well, and building systems that scale. That separates meaningful progress from surface-level automation."
Key findings:
Integration is the biggest barrier
30% of teams cite integrating AI tools as their primary challenge, surpassing concerns around cost and skills.
Investment is accelerating
80% of teams plan to increase AI testing budgets by more than 10 percent next year, with nearly one in four planning increases exceeding 25%.
ROI validates the investment
64% of companies report returns exceeding 51% from AI testing, with organizations using AI for four or more years 83% more likely to see returns over 100%.
Meanwhile, the report shows momentum in how teams are putting AI to work. Test case generation, test data creation, and automated maintenance are the most adopted use cases, helping organizations reduce manual effort and accelerate releases.
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