Generative AI for Retail and CPG: Balancing Core Value and Innovation

Generative AI (GenAI) is rapidly transforming the retail and consumer packaged goods (CPG) sectors, offering both the promise of operational efficiency and the potential for customer-centric innovation. Yet, for many industry leaders, the path to value is anything but straightforward. Data complexity, organizational inertia, and the pressure to deliver both immediate results and future-facing breakthroughs create a unique set of challenges—and opportunities.

The Dual Imperative: Core Value and Innovation

Retail and CPG companies operate in a world where margins are tight, customer expectations are evolving, and the pace of change is relentless. GenAI offers a powerful lever to address these realities, but success requires a careful balance:

The most forward-thinking organizations are not choosing between these goals—they are pursuing both, using GenAI to improve business-as-usual (BAU) while simultaneously investing in innovation.

Navigating Data Challenges: Don’t Wait for Perfection

Data is the lifeblood of GenAI, but in retail and CPG, it is rarely perfect. Mergers, acquisitions, legacy systems, and fragmented operations mean that data estates are often messy and incomplete. Leaders at recent industry roundtables, including those convened by Publicis Sapient, were clear: waiting for perfect data is a fool’s errand.

Instead, the recommendation is to:

This pragmatic approach enables organizations to make progress, build momentum, and demonstrate value—while incrementally improving their data foundations.

Use Case Selection: Practical Advice from the Front Lines

Retail and CPG leaders are seeing tangible benefits from GenAI in a range of areas. Insights from industry roundtables and client engagements highlight several practical strategies for use case selection:

  1. Start Small, Educate, and Build Trust
    • Begin with pilot projects that address clear business pain points—such as automating product content creation, optimizing supply chain forecasts, or enhancing customer support.
    • Use these early wins to build organizational confidence and educate teams about GenAI’s capabilities and limitations.
  2. Balance Productivity and Innovation
    • Many organizations initially focus on productivity and efficiency gains—streamlining legal document formatting, automating responses to procurement questionnaires, or predicting component failures in manufacturing.
    • However, the most ambitious leaders are also exploring GenAI’s potential for competitive differentiation: real-time customer segmentation, hyper-personalized marketing, and new digital business models.
  3. Ground GenAI Strategy in Business Objectives
    • Avoid the trap of deploying GenAI as a technology in search of a problem. Instead, align use cases with strategic business goals—whether that’s improving customer engagement, accelerating product development, or unlocking new revenue streams.
    • Involve business stakeholders early and often to ensure relevance and buy-in.
  4. Experiment and Iterate
    • GenAI is still an emerging field. Organizations should embrace a test-and-learn mindset, using proofs of concept (POCs) to validate ideas and refine approaches before scaling.
    • Don’t be paralyzed by the need for a perfect business case—some of the most transformative opportunities will only become clear through experimentation.

Scaling GenAI: From Pilots to Enterprise Value

While most retail and CPG companies are still in the pilot or early deployment stages, the leaders are already moving beyond isolated experiments. The key to scaling GenAI lies in:

Real-World Examples: GenAI in Action

Overcoming Barriers: Data, Talent, and ROI

Despite the momentum, significant barriers remain:

Other challenges include uncertainty about ROI, technology maturity, security, and ethical concerns. The advice from industry leaders is clear: don’t let these barriers become excuses for inaction. Instead, focus on building a portfolio of use cases, investing in talent development, and iteratively improving data and technology foundations.

The Path Forward: Balancing BAU and Innovation

The most successful retail and CPG organizations are those that:

As one CPG executive put it, “Don’t be obsessed with a [traditional] business case—make sure you’re future-proof. AI is a new business engine with no one business case.”

How Publicis Sapient Can Help

Publicis Sapient is recognized as a market leader in helping retail and CPG companies move from GenAI experimentation to value at scale. Our SPEED (Strategy, Product, Experience, Engineering, Data & AI) approach integrates business strategy with technical execution, enabling clients to:

With deep industry expertise and a proven track record of delivering both operational efficiency and customer-centric innovation, Publicis Sapient is your partner for the GenAI journey—helping you balance core value with bold experimentation, and turning today’s pilots into tomorrow’s competitive advantage.