Redefining the QA Role in the Age of AI

Artificial intelligence is rapidly transforming Quality Management Systems, from automating document reviews to supporting inspection readiness and risk prediction. While these innovations bring speed and scale, they also introduce new questions around oversight, accountability, and regulatory compliance. 

Our team at EVERSANA believes this moment represents a critical evolution in the role of Quality Assurance (QA). 

EVERSANA’s perspective was selected by the broader quality for the 42nd Annual Society of Quality Assurance (SQA) Meeting, through a poster authored by Dr. Sheeba Nair,  Director, PV Quality Systems, titled “Redefining the QA Role in the Age of AI: Building Human‑AI Collaboration for Smarter Quality Systems.” 

Why does the role of Quality Assurance need to evolve in the age of AI? 

As AI becomes embedded in quality workflows, the role of QA is expanding beyond traditional compliance oversight. QA leaders are increasingly acting as trusted navigators, guiding how AI is responsibly introduced into regulated environments. 

When implemented with the right guardrails, AI can support QA teams by enhancing: 

• Inspection readiness through earlier risk signals 

• Supplier oversight using data‑driven trend detection 

• Deviation management with faster root‑cause identification 

• Knowledge management across complex regulatory documentation 

The most effective quality systems treat AI not as a replacement for human judgment, but as a collaborator. 

What guardrails are required to ensure trust, transparency, and regulatory compliance? 

AI‑enabled quality systems must remain explainable, auditable, and accountable. Dr. Nair’s work highlights the critical role QA professionals play in defining governance models, validating AI‑supported outputs, and ensuring that ethical and regulatory expectations are met. 

Human‑in‑the‑Loop oversight remains essential, preserving reliability while allowing organizations to benefit from automation and predictive insights. 

What new skills will QA professionals need to succeed in AI‑enabled quality systems? 

As quality systems evolve, so too must the QA skillset. Data literacy, AI governance, and risk‑based thinking are becoming core competencies. These capabilities complement the foundational principles of quality and auditing, helping QA professionals remain stewards of trust while enabling innovation. 

Through real‑world scenarios and practical examples, our team’s perspective reflects a simple truth: the future of Quality Management is collaborative, where human expertise and AI insights work together to strengthen assurance. 

Learn more about how EVERSANA supports smarter, future‑ready quality systems 

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