Data Modernization in Retail and CPG: Balancing Core Operations and Innovation with GenAI

Navigating Complexity: The Retail and CPG Data Challenge

Retail and consumer packaged goods (CPG) companies operate in a world defined by complexity. From sprawling supply chains and omnichannel customer touchpoints to fragmented data estates shaped by years of acquisitions and legacy systems, these organizations face a unique set of data challenges. The imperative is clear: to remain competitive, retailers and CPGs must modernize their data foundations while simultaneously embracing innovation—especially the transformative potential of generative AI (GenAI).

Yet, the path forward is not straightforward. Leaders must balance foundational improvements—such as data quality, integration, and governance—with the need to experiment, scale, and embed GenAI-driven capabilities that can unlock new value across the business. The question is not whether to modernize, but how to do so in a way that delivers both operational efficiency and competitive differentiation.

The Dual Mandate: Strengthen the Core, Enable Innovation

1. Modernizing the Data Foundation

For many retail and CPG organizations, the first step is to address the fragmented, siloed, and often outdated data architectures that limit agility and insight. This means:

• Integrating Disparate Data Sources: Merging data from legacy systems, recent acquisitions, and new digital channels to create a unified, accessible data estate.
• Improving Data Quality and Governance: Establishing robust data management practices to ensure accuracy, consistency, and compliance—critical for both operational reporting and advanced analytics.
• Enabling Real-Time Data Access: Moving toward cloud-native architectures and modern data platforms that support real-time decision-making and customer engagement.

These foundational moves are not just about cost reduction or technical optimization. They are essential enablers for the next wave of innovation, including GenAI.

2. Embracing GenAI for Business Transformation

GenAI offers radical new opportunities for retail and CPG companies:

• Personalized Customer Experiences: GenAI can analyze real-time and historical data to create dynamic, hyper-personalized customer journeys—moving beyond static personas to data-driven, adaptive engagement.
• Supply Chain Optimization: AI-driven insights can predict demand, optimize inventory, and streamline logistics, even in the face of imperfect or incomplete data.
• New Business Models and Revenue Streams: GenAI enables the creation of new products, services, and data monetization strategies, from intelligent product recommendations to automated content generation and dynamic pricing.

However, the journey to GenAI value is rarely linear. Data quality, talent shortages, and organizational silos remain significant barriers. The most successful organizations are those that accept the messiness of real-world data, start small with targeted use cases, and scale what works—without waiting for perfection.

Practical Guidance for Retail and CPG Leaders

Don’t Wait for Data Perfection—Act Now

A recurring theme among industry leaders is the danger of waiting for perfect data before acting. In retail and CPG, data will always be messy—acquisitions, legacy systems, and rapid business change guarantee it. The key is to focus on use cases where GenAI can deliver value even with imperfect data, and to iterate quickly:

• Start with High-Impact, Feasible Use Cases: Identify areas where GenAI can drive measurable improvements—such as automating product content creation, enhancing customer support, or optimizing replenishment.
• Build Trust Through Proofs of Concept: Use pilots to demonstrate value, educate stakeholders, and build organizational confidence in AI-driven approaches.
• Iterate and Scale: Move from pilot to production by refining models, improving data quality where it matters most, and embedding AI into business processes.

Balance Core Modernization with Innovation

While GenAI captures headlines, foundational data modernization remains critical. Leaders must:

• Invest in Data Governance and Security: As AI models become more pervasive, ensuring data privacy, compliance, and ethical use is non-negotiable.
• Modernize Infrastructure for Agility: Cloud-native data platforms, data fabrics, and real-time integration are essential for supporting both operational needs and AI innovation.
• Foster a Culture of Experimentation: Encourage cross-functional teams to collaborate, experiment, and learn from both successes and failures.

Align Technology and Business Objectives

One of the biggest challenges in retail and CPG data modernization is aligning technology investments with business strategy. Too often, technology teams focus on tools and platforms, while business leaders seek outcomes—growth, efficiency, and customer loyalty. Success requires:

• Clear Business Cases for Data and AI Initiatives: Tie every modernization and GenAI investment to specific business outcomes, such as increased sales, reduced stockouts, or improved customer satisfaction.
• Cross-Functional Governance: Establish joint ownership of data and AI initiatives across IT, business, and analytics teams.
• Continuous Measurement and Adaptation: Use analytics to track progress, measure ROI, and adapt strategies as the business and technology landscape evolves.

The Role of Partners: Accelerating the Journey

Given the complexity of retail and CPG data estates, few organizations can modernize alone. Leading service partners bring:

• Industry-Specific Expertise: Deep understanding of retail and CPG business models, regulatory requirements, and customer expectations.
• Proven Tools and Accelerators: Frameworks, platforms, and IP that speed up data integration, governance, and AI deployment.
• Co-Innovation and Change Management: The ability to work alongside clients to define outcomes, build capabilities, and drive adoption at scale.

Publicis Sapient, recognized as a market leader in data modernization and GenAI services, combines digital business strategy, customer experience, and advanced data and AI expertise to help retail and CPG clients unlock new sources of value. Our SPEED (Strategy, Product, Experience, Engineering, Data & AI) approach ensures that modernization is always tied to business outcomes, and that innovation is embedded across the value chain.

Looking Ahead: From Pilot to Scale, from Efficiency to Differentiation

The future of retail and CPG will be defined by those who can balance the demands of core modernization with the promise of GenAI-driven innovation. The journey is not about choosing between operational efficiency and bold new business models—it’s about doing both, in parallel.

• Accept Imperfection: Don’t let the pursuit of perfect data stall progress. Use GenAI to make sense of what you have, and improve as you go.
• Focus on Use Cases That Matter: Prioritize initiatives that deliver tangible business value, and scale what works.
• Invest in Foundations and Culture: Modernize data, foster collaboration, and build the skills needed to thrive in a GenAI-powered world.

By taking a pragmatic, outcome-driven approach to data modernization, retail and CPG leaders can unlock the full potential of GenAI—transforming not just how they operate, but how they compete and grow in a rapidly changing market.

Ready to modernize your data and unlock GenAI’s potential?

Publicis Sapient partners with retail and CPG organizations to deliver end-to-end data modernization and AI transformation—balancing operational excellence with innovation. Contact us to learn how we can help you build a future-ready, data-driven business.