Beyond the Pilot: How Retail and CPG Leaders Make AI Operational

AI Has Moved From Curiosity to Conviction

Artificial intelligence is no longer a fringe topic in executive conversations. Recent research shows that belief in AI’s value is now widespread among business leaders, including those running mid-sized organizations that sit at the heart of the retail and consumer goods ecosystem.

A survey of more than 300 mid-market CEOs conducted by Virtuous AI in partnership with Chief Executive Group found that 98.5 percent of respondents said AI has already generated value for their businesses (Retail Dive). The same research showed that most CEOs are no longer debating whether AI matters. Instead, they are grappling with how to apply it in a way that scales beyond individual projects.

That distinction is important. While nearly all respondents expressed confidence in AI’s potential, only 7 percent reported having a company-wide AI strategy that includes multiple initiatives. More than half said they are still running pilots, and roughly one-third said they have explored AI but have not yet applied it in a meaningful way (Retail Dive).

For retail and CPG leaders, this gap between confidence and execution is becoming increasingly visible.

Why Retail and CPG Feel the Gap More Sharply

Retail and CPG organizations are structurally complex. They operate across physical and digital environments, manage large assortments, and rely on tightly coordinated supply chains. These characteristics make AI attractive, but they also make adoption harder.

The Virtuous AI survey identified three primary barriers to broader AI adoption: lack of AI expertise, difficulty integrating AI with existing systems, and data quality or accessibility challenges (Retail Dive). These same issues frequently surface in retail-specific research.

A Berkeley Research Group study focused on North American retailers found that AI adoption is most mature in functions that already rely heavily on data and analytics, such as marketing and digital operations. Integration into planning, supply chain, sourcing, and enterprise decision-making remains more limited (CIO Dive).

This functional imbalance helps explain why many organizations see early wins without achieving enterprise-level transformation.

Where AI Is Gaining Real Traction Today

Despite uneven progress, AI use in retail and CPG is no longer hypothetical. Multiple independent studies point to consistent patterns in where companies are focusing their efforts.

Marketing, Merchandising, and Pricing

Retailers are most actively applying AI to marketing personalization, promotion planning, and pricing strategy. Berkeley Research Group found that about 70 percent of surveyed retailers use AI in marketing functions, followed by IT and digital operations at 62 percent, and merchandising and pricing at 54 percent (CIO Dive).

These use cases tend to deliver faster returns because they sit closer to revenue and often require fewer changes to core operational systems.

Operations and Supply Chain

Adoption is accelerating in operational areas, though from a lower base. Demand forecasting, inventory optimization, and logistics planning are increasingly supported by AI models that can respond more quickly to volatility. Nvidia reports that 58 percent of retail and CPG organizations surveyed are now actively deploying AI, up from 42 percent the prior year (Retail TouchPoints).

While these deployments are still evolving, they signal growing confidence in AI’s role beyond customer-facing applications.

Decision Support for Employees

Another area gaining momentum is AI-enabled decision support. Rather than fully automating decisions, many retailers are experimenting with tools that help merchants, planners, and store associates prioritize work and interpret complex data. These systems aim to improve judgment and speed rather than replace human oversight.

Walmart as a Directional Signal

Large retailers often provide useful signals about where technology adoption may be headed, even if their scale makes them imperfect comparisons.

Walmart has publicly outlined an AI framework built around multiple specialized agents designed to support both customers and associates. These include AI-assisted shopping experiences, agent-based forecasting in fulfillment centers, and AI tools that help store associates with tasks like restocking and prioritization (Retail Dive).

Speaking at the ICR Conference, Walmart executive vice president Daniel Danker described AI as a productivity multiplier, comparing it to a power tool that enables work that was previously difficult or inefficient to do at scale (Walmart ICR Conference transcript).

For most retail and CPG organizations, the takeaway is not to replicate Walmart’s approach. It is to recognize that AI delivers the most value when it is embedded into everyday workflows rather than treated as a standalone experiment.

Why Pilots Stall

One of the more telling findings from the Virtuous AI research is that six in ten CEOs said they are already executing AI projects even without an enterprise-wide strategy (Retail Dive). This suggests that the issue is not lack of interest or activity.

In retail and CPG, stalled pilots often reflect deeper organizational challenges:

• Data ownership spread across functions
• Technology decisions made in isolation
• Success measured by tool adoption rather than business outcomes
• AI expertise concentrated in small teams with limited influence

AI tends to surface these issues quickly because it depends on coordination across systems, teams, and data sources.

What This Means for Retail and CPG Leaders

The research points to a sector that is early, not late, in its AI journey. Most organizations are still learning where AI fits best and how to support it operationally.

Patterns are beginning to emerge among companies making progress:

• AI initiatives are increasingly tied to clear financial or operational outcomes such as efficiency, cost reduction, or inventory performance.
• Data readiness is treated as a strategic priority, not just a technical one.
• AI is positioned as decision support that enhances human judgment rather than automation for its own sake.

These shifts reflect a more pragmatic view of AI, one that aligns with the realities of retail and CPG operations.

An Industry at a Turning Point

Retail and CPG leaders are no longer asking whether AI belongs in their organizations. They are deciding how deeply it should be woven into the way decisions get made.

As more companies move from pilots to production, the competitive advantage will increasingly come from execution rather than experimentation. The organizations that succeed will likely be those that focus less on adopting tools and more on integrating AI into the rhythms of planning, operations, and execution.

In that transition, belief becomes infrastructure, and infrastructure is what ultimately turns AI’s promise into measurable impact.

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