Quality at scale: How PwC’s AI toolkit automates quality management systems

A: It’s more difficult than ever to operate a business efficiently. Companies spend millions of dollars on QMS each year. With constantly changing regulations, unpredictable supply chains, fast-changing world events, and rapid advances in technology, it’s essential to continually rethink processes and workflows. AI can unlock agility, flexibility, and speed in several critical ways.

• It can identify narratives as adverse events, product complaints, compliance issues, etc.
• It can automatically classify and close product complaints for known issues.
• It can auto-generate responses and executive summaries to product complaints.
• It can detect and identify deviations and underlying issues at manufacturing sites and plants.
• It can automatically apply corrective and preventative action (CAPA) plans.
• It can assist in investigation processes, including writing detailed investigation reports.
• It can find hidden trends and signals in your historical complaints and deviations.

These processes typically require a high level of manual oversight. Narrative reviews, complaint assessments, and related tasks are time-consuming and prone to human error. Making matters worse, an inability to identify root causes can allow issues to continually resurface as your teams respond to symptoms rather than fixing their underlying causes. This is where AI can deliver the greatest value, and it’s a core strength of the QMS AI toolkit.

A: Rather than competing with your traditional eQMS, the QMS AI toolkit complements them. It’s an AI sidekick that can ingest data from traditional QM systems and then provide intelligent automation capabilities, like the identification and classification of complaints or the root cause of deviations.

The AI toolkit also displays results in near-real time. And when a user accepts or corrects AI-generated answers, that data flows back to the system of record. Using this side-by-side approach, it’s possible to reduce cycle times for QMS processes by upwards of 80%.

Smaller organizations that lack sophisticated or expensive QM systems can also take advantage of the platform. The QMS AI toolkit can work independently by ingesting data from other source systems. With automation in place, companies of various sizes can build highly automated, user-centric workflows that condense processing cycle times.

A: The QMS AI toolkit can enable you to work faster and more precisely. AI can detect and classify thousands of incoming reports—ranging from adverse events to product complaints—in minutes. It replaces processes that may have previously taken days while reducing human error and misclassification. It can streamline critical investigation workflows, enhance decision consistency, and free up valuable capacity across quality and compliance teams—enabling you to operate with greater speed, precision, and efficiency.

PwC clients report that traditional root cause analysis (RCA) misclassifies 70% or even 80% of deviations due to human errors. The vast number of possible root causes makes it difficult, if not impossible, to review or consistently select correct root cause categories for the issues at hand. When underlying issues at manufacturing sites haven’t been properly addressed, inaccurate categorization can lead to recurrence rates as high as 20%. Instead, the QMS AI toolkit can analyze deviation reports and investigation summaries based on known categories, pinpointing root causes quickly and precisely. This can reduce RCA cycle times from days to minutes.

PwC has found that the AI-enabled classification engine typically delivers a four-fold volume increase in processing complaints. It analyzes incoming data to help detect and automatically classify product complaints into key reported issues, ranking severity and identifying which issues merit priority investigations. This efficiency gain helps quality professionals and their teams shift focus to higher-value work.

A: Yes. The QMS AI toolkit is an intelligent, complementary layer that enhances the capabilities of your existing eQMS. It can integrate seamlessly with leading eQMS platforms, ingesting data and applying advanced AI to help generate actionable insights, automate labor-intensive processes, and accelerate decision-making. Whether your eQMS is already operational or still in the configuration stage, the QMS AI toolkit can plug in and deliver immediate value.

Put simply, the QMS AI toolkit doesn’t replace your eQMS—it can supercharge it.

A: Amazon Bedrock is the engine that powers the QMS toolkit. It provides a highly secure and ultra-scalable enterprise-grade generative AI foundation. Through a serverless environment and a single API, Bedrock supports sophisticated language models from multiple providers as well as advanced data processing and analytics capabilities. It also supports customized agents and connects to other AWS services. Real-time predictive insights, along with PwC’s expertise in consulting and operational excellence, result in an agile, flexible and reliable platform that can generate tangible value and return on investment.

A: No. The QMS AI toolkit integrates directly with existing quality management systems, so there’s little or no disruption to your business processes, increasing ROI.

A: Flexibility and scalability are at the foundation of the QMS AI toolkit. As a result, the platform can excel across a wide range of industries and applications. It can be a particularly powerful solution in highly regulated sectors like pharmaceuticals, biotechnology, medical devices, food and beverage, automotive, and aerospace—anywhere managing deviations or nonconformances, complaints, or other quality events is critical.

Another feature that appeals to users is the ability to customize the QMS AI toolkit for different user groups, putting your organizations firmly in control of your quality data.

• Quality professionals can use the toolkit to reduce manual workload and improve investigation accuracy.

• Compliance or data integrity professionals can gain better traceability and faster access to audit-ready insights.

• Manufacturing and operations groups can benefit from reduced downtime and fewer recurring deviations.

• Executives and decision-makers can gain real-time visibility into quality trends to achieve data-driven decision-making at scale.

A: The launch of our QMS AI toolkit marks a foundational shift in how quality is managed in regulated industries. By implementing AI in time-consuming quality processes like complaint triage and deviation investigations, we’re laying the groundwork for an intelligent quality management ecosystem. This is only the first step.

We envision a rapid expansion of intelligent automation across the extended manufacturing and quality value chain. Future enhancements will likely include:

• AI-driven deviation detection
• Automated SOP optimization and rewriting
• Intelligent CAPA planning and applicability checks
• Real-time signal detection from manufacturing data

Our QMS AI toolkit can evolve from an automation assistant to a strategic advisor that helps drive early detection of quality events. The future of intelligent automation isn’t simply doing things faster—it’s your organization becoming smarter, more reliable, and more nimble.