The State Of AI In Retail And Consumer Packaged Goods (CPG) In 2025: An NVIDIA Survey Report

• NVIDIA’s second annual State of AI in Retail and CPG survey report provides insights into the adoption and investment of AI, the specific adoption of generative AI, the top use cases and challenges, and how the industry is using AI in the supply chain. 
• 89% of respondents reported actively using or evaluating AI projects, 87% highlighted AI's positive impact on revenue growth, and 97% anticipated increased AI spending in the next fiscal year.

From September to November 2024, NVIDIA conducted a comprehensive survey to explore the adoption and impact of artificial intelligence (AI) within the retail and consumer packaged goods (CPG) sectors. 

The survey, which gathered insights from hundreds of industry professionals, aimed to understand how AI technologies are being integrated into business operations, identify opportunities and challenges, and measure the maturity of AI adoption. 

The results revealed that AI adoption is widespread, with 90% of respondents reporting that their companies are either actively using AI in their operations or assessing AI projects, including trials and pilots. 

Generative AI has emerged as a key tool, particularly for marketing, advertising, and customer analytics, while over half of respondents are leveraging AI across more than six use cases, ranging from content creation to demand forecasting and personalisation. 

According to the State of AI in Retail and CPG survey report, despite multiple advancements, challenges remain, particularly in the supply chain, where 59% of executives and professionals reported increased difficulties over the past year. Companies are now focusing on improving operational performance and meeting customer expectations.

Here we bring to you the detailed overview of the report: 

AI impact and investment in retail and CPG

Artificial intelligence (AI) is increasingly shaping the retail and consumer packaged goods (CPG) sectors, delivering measurable benefits across a range of business operations. 

From digital retail and supply chain management to physical store operations and back-office functions, companies are leveraging AI to drive revenue growth, reduce costs, and improve operational efficiencies. 

Key insights on AI adoption, investment, and impact

Adoption of AI in operations: A majority of companies in the retail and consumer packaged goods (CPG) sectors are actively engaging with artificial intelligence (AI) technologies. 

• 42% of respondents are actively implementing AI in their operations.
• 47% are in the assessment phase, exploring the capabilities of AI and its potential applications within their organisations.
• Only 11% of respondents indicated that they are not using AI. 

Revenue growth driven by AI: 

• 87% of companies that have adopted AI reported an increase in their annual revenue.
• 25% of respondents attributed a revenue increase of more than 20% directly to the implementation of AI technologies.

Reduction in operational costs: 

• 94% of respondents stated that AI has helped reduce their operational costs.
• More than 25% of these companies reported cost reductions exceeding 20%.

Year-on-year growth in AI adoption:

• The percentage of companies in the assessment phase grew from 36% in 2023 to 47% in 2024, highlighting a growing interest in exploring AI’s potential.
• 42% of companies reported actively using AI in 2024, indicating progress in the practical integration of AI technologies.

Generative AI in retail and consumer packaged goods (CPG)

By leveraging neural networks, generative AI identifies patterns and structures in existing data to produce personalised recommendations, marketing content, predictive analytics, and more, Generative AI is revolutionising the retail and CPG industries by enabling businesses to create new and original content, enhance customer experiences, and optimise operations. 

Adoption and strategic importance of generative AI: 

• 82% of respondents reported they are either using or assessing generative AI in their operations.
• 11% of companies are in a "wait-and-see" phase, observing developments before adoption.
• Nearly 50% of respondents believe generative AI is a strategic technology.

Key use cases of generative AI: 

1. Marketing and content generation: The most popular application of generative AI, with 60% of companies using it to create text, images, videos, and other multimodal assets for marketing and advertising campaigns.
2. Predictive analytics: A staple in retail, predictive analytics remains a critical use case for generative AI, utilised by 44% of companies to forecast customer preferences and market trends more effectively.
3. Personalised marketing and advertising: 42% of respondents use generative AI to tailor marketing messages and advertisements.
4. Customer analysis and segmentation: 41% of companies rely on generative AI to analyse customer data and segment audiences.
5. Digital shopping assistants and copilots: Deployed by 40% of companies, these AI-driven tools provide personalised shopping recommendations and support.

Investment in generative AI:

• 93% of respondents plan to increase spending on generative AI in the next fiscal year.
• 51% expect their budgets to grow by more than 10%, with 31% projecting increases of over 20%.
• Only 2% of respondents indicated a potential decrease in investment.

Concerns about generative AI: Despite its advantages, the adoption of generative AI presents several challenges for retailers and CPG companies:

1. Data privacy and security: 60% of respondents identified data privacy as a top concern, given the extensive customer data collected across multiple touchpoints. 49% cited data security as a significant issue, emphasising the need to protect sensitive information and prevent misuse.
2. Regulatory and legal issues: 49% of respondents expressed concerns about legal complexities, including copyright issues related to generative AI-created content.
3. Implementation costs: The cost of implementing generative AI was a concern for 57% of respondents in 2024, a sharp increase from 25% in 2023. 
4. Job displacement: Fewer respondents (16%) identified job displacement as a concern in 2024, down from 21% in 2023. 

AI in the supply chain

The supply chain has long been a challenging area for retail and consumer packaged goods (CPG) companies. Over the past five years, these challenges have intensified due to global disruptions such as the pandemic, shifting customer preferences, and the growing demand for omnichannel shopping experiences. This has placed increased pressure on companies to adapt their supply chain operations to ensure efficiency, meet customer expectations, and manage costs.

Artificial intelligence (AI) is playing an increasingly important role in addressing these issues by improving operational efficiency, reducing costs, and enabling better decision-making through data analysis.

Key insights on AI in the supply chain

Improving supply chain operations with AI: AI is being widely adopted by companies to address the complexities of modern supply chains. Key areas of improvement include:

• Operational efficiency: AI is used to optimise processes such as inventory demand prediction and shipping logistics, ensuring that products are available when needed while reducing waste.
• Cost management: Companies are leveraging AI to analyse inefficiencies within their supply chains and identify cost-saving opportunities.
• Meeting customer expectations: With the acceleration of digital commerce, customers now expect seamless experiences, including fast delivery and product availability. AI helps companies address these expectations by improving forecasting and logistics.

Investment in AI for supply chain operations: The primary focus of these investments is on demand forecasting and prediction, which was cited by 82% of respondents as the most critical area for AI application. Other areas of investment include:

• Warehouse employee copilots: AI-powered digital advisors to assist employees, cited by 35% of respondents.
• Periodic reporting automation: Automating regular reporting processes, cited by 33%.
• Robotics and physical AI: Investments in pick-and-place robotics (29%), smart forklifts and automated mobile robots (24%), and sensor-based intelligence at loading docks (24%).

Top supply chain issues addressed by AI: AI is helping companies address several key challenges within their supply chains:

1. Operational efficiency and throughput: 58% of respondents identified this as the top issue addressed by AI. By predicting inventory demand and shipping times, AI ensures that resources are used effectively and popular products remain available.
2. Cost management: 45% of companies reported that AI helps reduce supply chain costs by identifying inefficiencies and optimising operations. A quarter of respondents said costs were reduced by more than 10%.
3. Meeting customer expectations: 42% of respondents highlighted AI’s role in addressing heightened customer expectations, particularly in terms of faster delivery times and reduced stockouts, which are critical in today’s competitive retail environment.

Key use cases for AI in supply chain operations: AI is being deployed across various aspects of supply chain management, with specific use cases showing significant adoption:

• Demand forecasting and prediction: AI is enabling companies to anticipate customer demand with greater accuracy, ensuring better inventory management.
• Robotics and physical AI: Technologies like pick-and-place robotics, smart forklifts, and automated mobile robots are helping companies improve logistics and reduce manual effort.
• Simulation and digital twins: AI-powered digital twins are being used to create simulations of warehouses and other assets, allowing companies to test configurations and optimise operations without disrupting real-world activities.

Impact of AI on supply chain operations: The integration of AI into supply chain operations has led to measurable improvements:

1. Cost reduction and task automation: 61% of respondents cited reductions in operational costs and automation of repetitive tasks as key benefits of AI. By automating processes like data entry and scheduling, AI allows employees to focus on higher-value tasks.
2. Enhanced decision-making: 58% of companies reported that AI improved their ability to make informed decisions by analysing large volumes of supply chain data.
3. Improved customer service: 55% of respondents said AI had enhanced customer service by ensuring better personalisation and faster response times.
4. Inventory and supply chain optimisation: 48% highlighted improvements in inventory and supply chain management, including reduced stockouts and optimised product flows.
5. Improved forecasting: 32% of respondents noted that AI had strengthened their forecasting capabilities, helping them predict customer demand and market trends.

Challenges in AI adoption for supply chain management: Despite the benefits, companies face several challenges in implementing AI for supply chain operations:

1. Explainable AI tools: 33% of respondents identified the need for more transparent and user-friendly AI tools as a significant challenge. This reflects the demand for solutions that are easier to interpret and deploy.
2. AI talent: 31% of respondents cited difficulties in recruiting and retaining skilled professionals to develop and manage AI solutions.
3. Budget constraints: Budget limitations remain a challenge for many companies, particularly as they scale AI projects beyond initial trials.

Overall trends for AI in retail and CPG

Artificial intelligence (AI) is transforming the retail and consumer packaged goods (CPG) sectors, influencing nearly every aspect of business operations. From enhancing decision-making to optimising productivity and creating operational efficiencies, AI has become integral to how these industries function. This section explores the trends, challenges, and opportunities associated with AI in retail for 2025.

Key trends for 2025

Broadening AI investment across retail operations: Retailers are increasingly recognising the return on investment (ROI) that AI offers across various operational areas. The focus of AI investment spans:

• AI is being applied to enhance ecommerce, mobile platforms, and social media operations.
• Companies are using AI for marketing, human resources, and financial management.
• AI is improving forecasting, distribution, and warehouse management.
• AI applications in brick-and-mortar locations include inventory management and adaptive advertising.

Key use cases for AI in retail: AI applications are widespread across retail and CPG operations, with many companies implementing six or more use cases. The most notable examples include:

• Physical stores: AI is being used for inventory management, providing analytics and insights, and implementing adaptive advertising to reach target customers.
• Back-office operations: Customer analytics and predictive analytics are the top use cases for AI, enabling better decision-making.
• Digital retail: Content creation for marketing and advertising, as well as hyper-personalised product recommendations, are primary applications of AI in digital retail.

The impact and ROI of AI: AI has delivered tangible benefits across retail and CPG operations, with significant impacts in key areas:

1. 43% of respondents noted that AI has enhanced their ability to understand customers, optimise supply chains, and manage inventory.
2. 42% of respondents highlighted improved workforce efficiency, a notable increase from 14% in 2023. Generative AI, for instance, has been used to create marketing content and streamline tasks, freeing employees to focus on more strategic work.
3. Marketing and advertising content generation delivered the greatest ROI, cited by 23% of respondents. Customer analysis and segmentation followed at 19%, while hyper-personalised recommendations and predictive analytics each contributed significantly, cited by 18% and 17% of respondents, respectively.

As the retail and consumer packaged goods (CPG) industries increasingly adopt AI, the results of the latest survey highlight a significant change in how businesses operate in today’s complex environment. Top companies are using advanced technologies — like AI agents and physical AI — to improve efficiency, boost revenue, and establish themselves as leaders in innovation, helping to reshape the future of retail and CPG.