QualiZeal-HFS Study: 57% of Enterprises Use GenAI in Production, Only 15% Have Dedicated Testing
Hyderabad, November 11, 2026: A new joint study by QualiZeal and HFS Research has revealed a significant gap between the rapid adoption of Artificial Intelligence (AI) by enterprises and their preparedness to ensure its quality, safety and reliability. According to the study, 57% of enterprises have generative AI applications running in production, while only 15% have a purpose-built approach to AI testing.
The study, titled HFS Take 5 x QualiZeal, surveyed 101 enterprise quality and technology leaders in the United States to assess how organisations are validating AI systems and adapting Quality Engineering (QE) practices to the evolving AI landscape.
The findings reveal that 36% of enterprises already have agentic AI systems in production, while 52% continue to test probabilistic AI systems using conventional software testing frameworks. Further, 37% of enterprises running AI in production do not have a specifically designated function accountable for AI quality.
Commenting on the findings, Kalyan Konda, Co-Founder, Executive Director and CEO of QualiZeal, said enterprises had adopted AI much faster than they had developed the necessary governance and quality assurance mechanisms. He emphasised the need for clear accountability and specialised validation frameworks as organisations expand their AI initiatives.
The study also highlighted a gap between measuring AI accuracy and establishing trust. While 88% of enterprises measure model accuracy, only 47% assess bias and fairness, 37% measure explainability, and 35% can provide evidence of regulatory compliance.
Madhu Murty, Co-Founder and Head of India Operations, QualiZeal, said Quality Engineering was undergoing a fundamental transformation, with engineers increasingly expected to ensure the reliability and trustworthiness of AI systems. According to the study, 82% of enterprises expect the role of Quality Engineering to grow significantly. He added that AI and automation would elevate the responsibilities of quality engineers rather than replace them.
Despite the expanding responsibilities, investment in the sector remains limited. Only 24% of enterprises reported receiving resources proportionate to the expanded Quality Engineering mandate.
QualiZeal’s AI ecosystem, including QMentisAI™ and ValidAIte™, aims to help enterprises address these challenges by integrating AI-led quality assurance and validation into their delivery and governance processes.
Hansa Iyengar, Practice Leader at HFS Research, said that while most enterprises could demonstrate AI accuracy, significantly fewer could establish that their systems were fair, explainable and compliant. She stressed that building trust in AI requires clear ownership of quality, testing frameworks designed for probabilistic systems and adequate investment in Quality Engineering.
The study provides enterprise leaders with insights into the growing challenges of AI assurance and highlights the need to move beyond AI adoption towards trusted, reliable and production-ready AI systems.
