2026年零售与快消品行业AI应用状况与趋势报告_17页_1mb

State of AI in Retail and Consumer Package Goods: 2026 Trends Summary

Core Content

The NVIDIA State of AI in Retail and Consumer Package Goods: 2026 Trends report provides a comprehensive overview of the current state and future direction of AI adoption in the retail and CPG industries. It highlights how AI is transforming operations, customer experiences, and supply chain management, while also addressing the challenges of implementation and optimization.

Key Trends and Insights

AI Adoption and Business Impact

• 91% of retail and CPG organizations are now engaged with AI, reflecting near-universal adoption.
• 58% actively use AI, up from 42% in 2024, indicating a shift from experimentation to implementation.
• AI is delivering measurable impact on the bottom line:
  • 89% said AI increases annual revenue.
  • 95% said AI decreases annual costs.
  • 58% reported cost reductions of 5% or more.
  • 57% achieved revenue growth of 5% or more.

Strategic Objectives

• Organizations initially adopted AI for:
  • Operational efficiencies (45%)
  • Customer experience (38%)
  • Employee productivity (29%)
• AI has exceeded these expectations, with:
  • 54% reporting increased productivity.
  • 52% noting improved operational efficiency.
  • 41% observing better customer experiences.

Investment Trends

• 90% of executives expect AI investment to grow in 2026.
• 58% anticipate growth of more than 10%.
• Investment priorities include:
  • Optimizing AI workflows and production (36%)
  • Identifying new use cases (33%)
  • Training existing staff (32%)

Open-Source AI

• Open-source models and tools are gaining strategic importance.
• 48% consider open-source integration very to extremely important.
• 31% see it as moderately important.
• Open-source enables flexibility and innovation, allowing companies to tailor AI to their specific needs.

Agentic AI

• Agentic AI, which autonomously reasons, plans, and executes tasks, is on the rise.
• 47% are using or assessing AI agents.
• 20% are actively deploying them.
• 54% of smaller companies are using or assessing agentic AI compared to 40% of larger ones.
• Key objectives for agentic AI include:
  • Increasing process speed and efficiency (57%)
  • Enhancing customer experiences and personalization (40%)
  • Improving decision-making with real-time data (40%)

AI Across the Value Chain

• AI is being leveraged across all areas of the business value chain:
  • Digital commerce (61%): Focused on customer-facing applications such as marketing, personalization, and shopping assistants.
  • Back office (54%): Emphasizing automation, analytics, and efficiency.
  • Supply chain (45%): Addressing optimization, traceability, and resilience.
  • Physical stores (24%): Leveraging analytics and customer insights.

Supply Chain Resilience

• 64% of respondents cited increased supply chain challenges.
• AI is critical for operational excellence, with 45% using it to achieve this.
• AI is being used to address:
  • Operational efficiency and throughput (51%)
  • Meeting customer expectations (45%)
  • Traceability and transparency (38%)

Inference Optimization

• AI inference is a critical factor in translating AI investments into business value.
• Key considerations for inference optimization:
  • Cost efficiency and total cost of ownership (41%)
  • Latency, accuracy, and throughput (35%)
  • Model performance and benchmarking (32%)
• Only 13% of respondents cited training data as a top challenge.
• 46% identified the AI talent gap as the top barrier to implementation.

Future Outlook

The retail and CPG industry is at a transformative moment, with AI becoming a core component of strategic planning. The focus is shifting from experimentation to execution, with an emphasis on:

• Open and flexible AI stacks
• Agentic AI for autonomous decision-making and customer engagement
• Physical AI and robotics for next-gen supply chain operations
• Inference optimization to ensure cost efficiency and performance

Organizations that successfully scale agentic AI and address the talent gap will gain a competitive edge in an environment of increasing customer expectations and supply chain complexity.

Conclusion

AI is no longer an experimental tool but a strategic imperative for the retail and CPG industries. With increasing investment, proven business impact, and the adoption of advanced technologies like agentic AI and open-source models, the industry is poised for unprecedented innovation and efficiency. The next twelve months will be crucial for deeper integration of AI into operations, ensuring that AI remains a profit driver rather than a cost center.

Methodology

• Survey conducted from August to September 2025.
• Responses collected from hundreds of executives, managers, and practitioners across various retail and CPG segments.
• Segments included: apparel and footwear, auto parts and accessories, cleaning and toiletries, convenience stores, cosmetics and beauty, department stores, ecommerce, food and drink, home improvement, home goods, office supplies, pharmacy, specialty and sporting goods, supermarkets and grocers, and warehouse clubs and supercenters.
• Survey distributed via NVIDIA's distribution lists and social media globally.

Forward-Looking Implications

• The industry is moving beyond the question of whether to invest in AI to how to deploy it effectively.
• Open-source stacks, agentic AI, and physical AI are expected to drive next-generation supply chain and customer experiences.
• Talent development and inference optimization will be key to sustaining AI momentum and achieving long-term competitive advantage.