Artificial Intelligence & Machine Learning In The FMCG Sector

As the construction of artificial intelligence data-gathering algorithms and machines that can learn from stimulus to produce ever-increasingly more-efficient results increases, the impact of these technologies within the Fast-Moving Consumer Goods sector, in particular the food industry, must be evaluated. Big data algorithms can be implemented to more efficiently analyse stock levels, purchases and revenue from particular goods and robotics can be applied within packaging settings to increase the output of farming sheds and other manufacturing plants. Some of these technologies are already being applied within the food packaging industry, notably mass production of labels and packaging goods. It’s expected that continued innovation in this sector could result in $2.2 Trillion of additional revenue to the Australian economy.

Product Placement

In the food distribution industry, artificial intelligence computing with visual inputs is able to calculate the most effective positioning for food products based on remaining stock, profit share and frequency of purchase. These algorithms are able to learn over time too, meaning that product placement artificial intelligence can evolve to provide data regarding how much stock to keep in warehousing, what product price should be set by management and where to place new products based on market data. A previously complex task will undoubtedly be made much easier by technology that is rapidly being adopted across the Australian food services industry.


Within the food and food packaging manufacturing, artificial intelligence can be applied to robotics technology to facilitate widespread growth in operations resulting from highly-efficient packaging, logistics and freight systems. Operational inefficiencies have historically resulted in bottlenecks in supply chain management which can hinder the distribution of products on a national scale. Advanced algorithms can now analyse wastage levels, security threats and safety standards and provide insight into how to innovate within an organisation to reduce downtime, slow procedures and previously ineffective practices.


Advertising algorithms make the dissemination of information by computing robotics as simple as pressing a button. Placing information in front of relevant consumer segments using desktop PCs, laptops and mobile phones has never been easier with targeting algorithms invented by organisations like Google, Facebook and YouTube. User profiles can be input to a system and then face advertising from companies selling products they believe will be useful to or meet a need of this particular demographic.

Challenges of Adopting AI & ML In The FMCG Sector

Inconsistencies within food products can manifest difficulties in applying robotics technology to food processing plants. Similarly, the cost of investment in robotics technology or artificial intelligence software is significant, and at the moment only big businesses can afford the investment in technology that is designed to significantly improve the output and increase the efficiency of companies operating within the Fast-Moving Consumer Goods sector. Similarly, disperse operations centres make the application of company-wide technology difficult. Some level of convergence is needed before every business is able to operate on a cross-location basis with artificial intelligence and machine learning technology.