From Compliance to Competitive Advantage: Quality in the AI Era
Against a backdrop of rising operational costs, volatile supply chains, and competitive pressure, organizations are increasingly turning to AI capabilities to adapt. As leaders consider which functions to prioritize, the usual examples tend to dominate the conversation: marketing, product development, manufacturing, customer service.
The potential impact of AI-enabled quality is substantial, but often overlooked. As issues such as shrinkflation and cost-driven reformulations impact consumer trust, true product quality naturally stands out as a differentiator. Quality can become a strategic advantage for companies that thoughtfully embed AI into their operating models.
Yet while businesses are being drawn to AI, many of them are now also moving through the disillusionment phase of the hype cycle.
Veeva’s quality masterclass in 2025 revealed that most consumer goods quality executives (60%) aren’t confident their teams have the skills and mindset to leverage AI-enabled quality, while 39% have not yet moved their digital quality transformation past the pilot stage.
Laying the groundwork for AI-enabled quality — and making quality a strategic differentiator — requires the integration of people, data and processes across the value chain.
Standardized Processes as the Bedrock
Inconsistent processes create inefficiencies, duplication and risk. And without common governance, digital platforms struggle to scale, integrate or deliver consistent value.
Sixty-one percent of executives say their quality processes remain disconnected or paper-based. Standardizing and connecting them is therefore a critical first step toward an AI-centric future.
“On the scale that we operate, a key challenge was… consistency within categories and regions. We've structured HACCP through standardized modules, and the results are very promising. In terms of the administrative burden that's being lifted, it’s a huge win for us.”
- David Clifford, Director, Food Safety, Nestlé
Leading organizations are establishing clear ownership and governance frameworks while redesigning processes: rather than simply digitizing existing workflows, they are reimagining them to be leaner, faster and more connected.
Successful companies balance consistency with flexibility, creating processes that are “as common as possible and as different as necessary” while embedding clear accountability.
Building a Clear Data Strategy
Seventy-one percent of quality leaders rate their data quality, connectivity and AI readiness as very poor to fair.
Leading executives recognize that trusted, connected data is the foundation for AI-enabled quality.
“Data is one of the biggest elements that defines the destination and speed of a transformation journey. The more data, the cleaner the data that you have, the more it’s structured; this will make the journey an easy one rather than a hard one.”
- Ahmed Maklad, Global Digital Quality Transformation Director, Unilever
A "progress over perfection" approach here is essential. Focusing on building the perfect dataset can cause delays and prevent benefit realization. Incremental improvements through practical, targeted use cases help build momentum, confidence and measurable value.
Mature organizations are defining longer-term quality data strategies, too. Connecting and centralizing sources of truth creates the visibility needed for enterprise-wide insights and data-driven decision-making.
People, Culture, Trust
Digitization projects fail without a clear vision and workforce engagement. Resistance to change and low confidence in new technologies remain some of the biggest barriers to successful adoption.
Veeva’s recent survey of consumer goods leaders found that executive sponsorship is one of the most critical success factors for AI initiatives. Successful leaders are those who actively advocate for change and communicate a compelling vision to ensure widespread support.
Transformation succeeds when employees understand the personal benefits of change. Teams should be able to articulate “what’s in it for me” as they develop the skills needed for an AI-enabled environment.
The companies best positioned for success are those building cultures that encourage curiosity and innovation. These organizations craft compelling change stories that resonate with both personal value and broader strategic goals.
Quality as a Strategic Differentiator
A robust quality management system can deliver:
- Faster time to market
- Better insights for continuous improvement
- Enhanced supplier relationships and efficient sourcing
- Reduced compliance burden
- Lower waste and improved margins
The ultimate outcome is an elevated consumer experience built on greater trust and satisfaction.
Organizations that successfully modernize quality operations gain more than efficiency. Optimized quality ecosystems drive faster decisions and greater agility, transforming quality into a competitive edge.
“Quality is not what we think it is, but what is perceived by the consumer.”
- Ana Rita Rezende Debiazzi, Head of Group Quality, Excellence & QMS, DSM
Quality for Competitive Advantage
AI is undoubtedly here to stay. The question is which quality departments ignore it, and which use it as a force for improvement.
Companies that delay their transformation journeys face accumulating data debt and escalating costs of poor quality. Those that embrace them can reposition quality not only as a safeguard for consumers but as a catalyst for resilience, growth and long-term performance.
Read the full Digital Quality Transformation and AI Readiness Playbook for nine high-impact plays to begin your transformation journey today.
