New MasterControl Survey: Pharma Quality Teams Struggle to Get Employees Engaged With Quality Systems, a Hurdle for AI Ambitions

Research finds pharma leaders optimistic about AI's impact but cite system integration, data privacy, and persistent quality system adoption gaps as key hurdles

SALT LAKE CITY, May 6, 2026 /PRNewswire/ -- MasterControl today released findings from a new survey revealing that pharmaceutical organizations are confident in AI's potential but face a foundational challenge: getting employees to consistently use the quality systems AI will depend on. Ninety-four percent of pharma quality leaders identified poor employee adoption and utilization of their quality system as a significant pain point – compared to 83% of their biotech counterparts – raising questions about how cleanly AI can be layered onto workflows people already disengage from.

The research, conducted among 300 quality and manufacturing leaders in life sciences, suggests that AI's success in pharma won't be determined by the technology alone, but by whether organizations can resolve the human and system-level gaps that already exist.

AI Is Delivering, But Expectations Were Already High

Despite early-stage implementation challenges, pharmaceutical leaders broadly report that AI is living up to the promise. Eighty-six percent of pharmaceutical leaders rate AI's actual impact on their operations as exceeding or meeting initial expectations, with 40% saying performance has been better than anticipated. These figures track closely with the overall survey average of 82%, suggesting pharma is neither leading nor lagging the broader life sciences sector in satisfaction – but is firmly in the optimistic camp.

Data Privacy and Integration Challenges Top the List of Implementation Barriers

One area where pharmaceutical leaders stand out is data privacy. Twenty-five percent of pharma respondents identified data privacy and security concerns as their primary AI implementation challenge. As pharmaceutical organizations handle highly sensitive formulation, clinical, and patient-adjacent data, these concerns reflect both regulatory obligations and competitive risk.

Integration challenges surface prominently as a primary implementation barrier, consistent with the survey's overall finding that integrated systems are the single most important prerequisite for effective AI deployment, cited as the top priority by 59% of all respondents.

Quality Defect Prevention Is the Top Priority

When asked where they expect AI to deliver the most value, 43% of pharmaceutical leaders ranked quality defect prediction and prevention among their top three priorities - the highest-rated use case in the sector. On the quality management side, more than half (52%) of pharmaceutical quality leaders said they would most benefit from an intelligent system that improves end-user decision making through real-time smart assistants, and 50% cited improved integration and visibility across systems as a top desired capability.

For manufacturing leaders specifically, 44% said enhanced traceability and compliance through automated data capture and analysis would be among the top benefits of an intelligent manufacturing system, and 30% pointed to the prediction and prevention of quality issues.

Manual Processes Still Widespread in Manufacturing

On the manufacturing floor, 79% of pharmaceutical manufacturing leaders reported that manual and inefficient processes remain a significant pain point – a figure that underscores both the scale of the opportunity and the distance still to travel. Nearly half (47%) said that execution, data collection, and documentation at their organizations are at a digital or connected level, while 41% said the same for production planning and scheduling – leaving meaningful room for AI-driven uplift.

Technology Deployment: Strong in Some Areas, Uneven in Others

Pharmaceutical organizations present a mixed picture of technology deployment. While 84% have deployed QMS and 56% have a cloud data platform or data lakehouse in place, only 43% have deployed an industrial IoT analytics platform, and just 17% have Real-time Location Systems (RTLS) – pointing to gaps in the real-time data infrastructure that AI systems depend on.

Additionally, 48% of pharmaceutical quality leaders reported that new tools and systems could cause significant issues in their work, compared to 35% in biotech, suggesting a more cautious cultural posture toward technology change.

"The data tells a clear story: pharma leaders believe in AI, but integration gaps and legacy infrastructure are slowing them down," said David Edwards, CEO of MasterControl. "At MasterControl, we've seen this firsthand. AI is only as powerful as the systems it connects to, which is why building on a unified quality and manufacturing platform isn't just an IT decision – it's a strategic one."

About the Research
MasterControl commissioned this research using an online survey prepared by Method Research and distributed by RepData. The survey was fielded among n=300 full-time Quality and Manufacturing leaders in life sciences from November 5–21, 2025. Respondents were drawn from North America, Europe, and APAC.

About MasterControl
MasterControl Solutions Inc. is a leading provider of AI-enabled quality, manufacturing, and asset management software for life sciences and other regulated industries. For three decades, our mission has been the same as that of our customers – to bring life-changing products to more people sooner. MasterControl helps organizations digitize, automate, and connect quality, manufacturing, and asset management processes and has a proven track record of improving product quality, reducing costs, and accelerating time to market. Over 1,200 companies worldwide use MasterControl to streamline operations, maintain compliance, manage critical assets and equipment, easily analyze and interpret large amounts of data, and visualize business insights in real time.

SOURCE MasterControl