The Seamless Integration: How AI Is Quietly Reshaping the FMCG World
The time is now for CPG companies to truly digitize their entire supply chain... Especially AI-led automation that can then take its efficiencies and productivity to a whole new level.
Artificial intelligence (AI) continues to have a transformative impact on the commercial world, from marketing and logistics to finance and healthcare. The fast-moving consumer goods (FMCG) sector has also been greatly affected.
Also known as consumer packaged goods (CPG), FMCG describes a wide array of products that are sold quickly at a relatively low cost. This sector is incredibly diverse, comprising everything from packaged foods and beverages to toiletries, cosmetics, dry goods, and over-the-counter drugs.
The FMCG industry has always been dynamic and highly competitive. Due to the quick nature of product turnover and the relatively low cost of individual sales, operating margins and timelines are very tight. The industry has been quick to adopt new technologies, with various tools used to refine operations and leverage commercial advantages.
Based on the 'AI and the FMCG Business: Great Partnership to Deliver the Goods' report from Infosys, 57% of FMCG companies are already engaged with AI technology, with 32% planning to adopt AI in the next 12 months and just 4% having no plans to get involved.
In this article, we'll explore numerous ways that AI has been woven into the FMCG industry. We'll forecast emerging AI trends, look at case studies, and analyse the implications of this exciting technology.
AI and the Natural Evolution of FMCG
AI has vast potential across the FMCG sector. This technology has diverse applications and broad benefits, from innovative shopping experiences to improved product design and better decision-making. Two fast-moving areas are sales forecasting and demand planning, which can help FMCG companies make better predictions around inventory management. Emerging AI technologies are also involved with shaping consumer experiences, managing supply chain logistics, and improving customer service.
With increased adoption and further refinement, AI has the potential to improve workflows and maximise operating efficiencies on multiple levels. To be successful, however, this technology needs to integrate successfully with existing tools and technologies. It needs to analyse data effectively, make accurate predictions, and enhance the user experience without being obtrusive. If these challenges are met, the FMCG sector can benefit from AI in many ways.
FMCG companies have already benefitted from more accurate demand forecasting, improved marketing personalisation, enhanced quality control, and better supply chain optimisation. A range of tools is needed to maximise these benefits, with companies needing to make intelligent decisions about how and when to adopt different technologies. This is incredibly important, with employees and customers not always willing to embrace inefficient or immature applications. Success comes when AI is integrated with existing tools and adopted without aggression.
According to Infosys, "The time is now for CPG companies to truly digitize their entire supply chain... Especially AI-led automation that can then take its efficiencies and productivity to a whole new level. This will allow intelligent systems to take over more of the known, well-defined aspect of the value chain, and decision makers can focus on finding new opportunities to create new kinds of products, experiences, and value that do not yet exist."
Behind-the-Scenes: AI at Work in FMCG
AI is already widely used in the FMCG sector, and it's not going away any time soon. The potential applications of this technology are almost as diverse as the possible rewards, from back-room processes and logistics to front-facing marketing campaigns and customer support. The following applications are among the most promising:
Inventory management and smart restocking
As mentioned above, smart inventory management is fundamental to the FMCG sector. When implemented properly, AI helps to optimise inventory levels through efficient resource management and demand forecasting. It can also help to improve distribution networks, enhance productivity, and reduce operational costs. AI can be used to tighten operating margins and leverage business resources more effectively.
For example, Nestle has been using AI-powered demand forecasting to develop its Nespresso brand — analysing historical sales data, promotional activity, and even weather patterns.
Personalised consumer experiences through data analysis
Personalisation is an emerging trend in AI. Tailored marketing campaigns can be enabled through data analysis and delivered without explicit AI branding. In recent years, many of these tools have become more refined and better integrated. AI can be used throughout the customer journey — analysing, funnelling, and transmitting information effectively across diverse platforms, channels, and touchpoints.
Improvements in supply chain logistics
Large e-commerce companies use AI-powered tools to optimise supply chains, adjust inventory levels, and refine shipping routes. AI helps with all aspects of inventory management and delivery. Automating inventory and logistics management helps to reduce waste and improve delivery times, and it also helps to boost service accuracy, track employee performance, and enhance quality control.
For example, Procter & Gamble has been using AI-powered quality control to identify defects in its products — analysing images to identify defects that are not visible to the human eye.
Product recommendations and customer service
Customer support is one of the frontier fields of AI technology. Chatbots and virtual assistants have been used for years, and the FMCG sector has embraced many of these trends. When natural language processing (NLP) and other AI technologies are integrated with existing systems, they can provide subtle product recommendations and superior customer service enhancements.
The Consumer Experience: Seamless and Enhanced
Many of the biggest advances in AI are related to the customer experience. Along with improving workflows through demand forecasting and inventory management, this is the most influential area of AI technology for the FMCG sector. The natural integration of AI continues to influence the consumer experience, and the future of AI will be defined by how well these changes are received.
AI has changed the consumer experience in many ways. It has helped companies to understand consumer behaviour, given them tools to improve product design, and helped them to maximise cost efficiencies in marketing and advertising. All of this value starts with data, with global networks and AI software giving companies unprecedented access to accurate real-time information.
Predictive analytics utilises historical data to forecast future buying patterns and enable personalisation. It helps companies make accurate business decisions and optimise prices based on the needs of the market. When this technology is immature or implemented incorrectly, it risks upsetting customers. When well-designed and properly integrated, it results in happy customers and repeat business. Customer feedback is central to this process, with AI able to analyse reviews, explore alternatives, and adjust roadmaps based on what's important to the end user.
Along with understanding consumer behaviour, AI can also improve product design. FMCG companies generally produce small functional items, with competition tough and products not always unique. In this environment, machine learning and other AI technologies can help to optimise product design. If companies find a way to create more sustainable and customised products, they're more likely to stand out from the competition and stay ahead of the curve.
Challenges and Cautious Steps
Despite the potential benefits of this technology, AI is not without challenges. Numerous pitfalls are associated with AI automation and integration, and the adoption phase is not all smooth sailing. Major challenges exist in data privacy, data accuracy, data redundancy, and consumer acceptance. Cautious steps are needed from the outset, with AI platforms and applications best adopted in stages to avoid conflict with current systems, protocols, and markets.
Information privacy is a huge concern for end users, and data accuracy is another critical issue that affects successful implementation. Companies interested in AI need to understand the limitations of this technology, especially when it comes to content creation and personalisation. While AI can create useful and engaging content for marketing and information purposes, it lacks true creativity and has no novelty value.
When it comes to consumer-facing AI content, there's a delicate balance between personalisation and intrusiveness. End users are not always ready to embrace AI-generated content. Within the FMCG industry, where products are generally small and impersonal, consumers may prefer simple messaging campaigns that respect their privacy. Whatever the future holds, there is a growing need for transparency and compliance, with industry guidelines and government regulations needed to address ethical considerations and protect users.
A number of FMCG companies have already adopted AI technologies, some of them very successfully. This technology can be used in many different ways, from forward-facing marketing campaigns to deep back-office logistics and delivery tactics. According to the 'AI in Consumer Goods' report from GlobalData, two of the leading adopters of AI are Coca-Cola and Unilever:
Coca-Cola is a global giant and market leader in customer-focused AI adoption. It mostly uses AI technology for product innovation and market research. For example, it created self-service drinks machines, collected data, and used that information to develop the most popular variant — Cherry Sprite. It also tracks social media with AI and develops targeted ads based on demographic trends.
Unilever is a consumer goods company from England, with its products including food and condiments, bottled water, baby food, soft drink, ice cream, and instant coffee. Unilever has developed a competitive market position, partly through the smart adoption of business-facing AI. For example, diverse AI systems are used to source raw materials, manage harvest times, and handle product manufacturing and packaging.
AI continues to have a huge influence on global markets and consumer behaviour. While there are significant challenges to address, the inconspicuous integration of AI is proving to be an effective strategy in the FMCG sector. When AI technology is adopted in stages and feedback is used to adjust implementation details, companies can take advantage of numerous customer- and business-facing tools. At Skipped, we help businesses in the FMCG sector to take advantage of new opportunities.
As a company in the FMCG industry, you're uniquely positioned to innovate and integrate with AI technology. Many of the biggest names in your field have already developed mature AI systems, with new applications and tools unlocked all the time. If you want to incorporate AI without disrupting the natural consumer experience, the team at Skipped is here to help. The seamless adoption and integration of AI technology will inform the very future of the FMCG sector, and no one can afford to miss out.