The human side of AI in packaging 

Man and AI robot waiting for a job interview: AI vs human competition. Credit: Stokkete at Shutterstock

Artificial intelligence is a key theme at the forefront of packaging industry leaders’ minds.  

It can be difficult to cut through the noise surrounding AI and its various technological branches, but a burning issue surrounding the technology in general is its potential effects on humans and whether it will become a friend or foe to consumers and employees.  

GlobalData packaging service director Dominic Cakebread proposes that there is no need for AI and humans to be pitted against one another, as a symbiosis will provide the ultimate advantages for the packaging industry.

Dominic Cakebread: Whilst Artificial Intelligence has been increasingly used in recent years in manufacturing and packaging lines for quality control inspection, line control and packaging waste sorting as well as distribution and logistics optimisation, on-line and in-store marketing, payment and after sale activities, the recent and very rapid recent developments in Generative AI – take the technology into whole new areas where it can be used for wider creative purposes. 

These uses include but are not limited to bespoke packaging innovation and design to meet increasingly diverse consumer demands.  

By using large language datasets across multiple regions, countries, consumer and product areas, generative AI can be used to develop more customized and specific packaging shapes designs tailored to specific consumers and customers, based on hard information and data.  

Though expanding fast, developments are at an early stage of development and packaging companies are still in practice exploring the possibilities that Generative AI offers in the package design sphere.  

Although, it seems conceivable it may move some of the functions of packaging design from bespoke design house to brand managers within the brands. 

Dominic Cakebread: Non-generative AI has seen steady growth in use amongst packaging companies for a number of years in terms of its application in packaging material product and packing systems.  

One of its main uses to date has been inspection control machinery where it has helped control to identify and reject failing products and packaging in high-speed packaging lines and hence reduce downtime, improve overall machinery efficiency, and line speeds.  

Whilst to some extent these developments may be seen as a threat to human-based QC checks, in practice these developments have simply improved the scope and accuracy of these tests and have complimented, rather than replaced existing personnel, reducing their workload and freeing time for them to work in other areas.   

This trend is likely to continue and accelerate and move further down the chain into areas such as integrated logistics and distribution, marketing, online and in-store sales and after sales support as the technology becomes increasingly powerful. 

Generative AI-will more directly affect the creative side of packaging design with more preliminary work undertaken by the brand owner themselves in terms of scoping the design and less by the design agency.   

This will mean that the designers with the brand owners will need to become more involved with (and develop the skills for) the use of Generative AI for their products in a  commercial environment – including their own brand positioning, product and pack design, consumer preference monitoring, online store positioning and in-store presence.  

Again, this is expected to change the roles of the individual and companies (brand owner, packaging design agencies and packaging suppliers) involved with a shift in emphasis in terms of roles and functions but ultimately it is not expected to obviate the roles entirely. 

Generative AI is more likely to become another technical tool with which internal and external designers will work to speed up and reduce the costs of the process, rather than a replacement of that role entirely. As all companies adopt the technology, this should enable more packs to be designed more quickly at lower cost. 

Dominic Cakebread: For Generative AI it is really too early in development to assess this – most packaging companies are still exploring the issues and options and considering how the technology is expected to impact their operations and business, in what areas it can be deployed to best commercial advantage within their own business and what are the threats it poses – either from a competitive position or to existing jobs and employees.   

The ubiquitous  nature of AI means it could potentially be deployed across many business functions and activities and throughout the supply chain from packaging producers to brand owners, retailers, consumers and even in recycling and post-consumer waste.   

By the same token however, the ubiquitous nature of the technology means that it can be adopted by competitors and new innovative start-ups alike. The competitive threats are likely to come from many angles, many perhaps unexpected, causing significant commercial disruption.  

In a Darwinian sense, this means that it will be the packaging companies that are quickest to evolve and adapt to the technologies, that are likely to survive strongest – and this perhaps explains why so many companies are looking at the technology in a broad context to first better understand how and in what ways it is likely to  affect their businesses.  

As ever in packaging, it is using the technology to better understand the consumer behaviour, the core market trends and  their customers’ changing needs, that is likely to be most important to retaining a competitive edge for packaging materials suppliers and converters. 

Dominic Cakebread: First make sure you have a full and (as importantly) on-going understanding of the AI-technologies involved as this is a rapidly changing technology.

Second, review all your core business processes and operations and consider where and how the technologies can potentially be deployed, the advantages it could offer and also possible issues (e.g., copyright infringement). All look at what your key competitors are doing for reference.

Third, allocate budget and prioritise and schedule implementation (including tests and trials of suitable technology and measure the impact). 

Fourth, choose those AI technologies and areas that work best and are most effective to develop at a larger scale. 

Throughout this process do not neglect to consider the implications for existing roles and personnel – what is the impact on existing roles and function, how can they be adapted to embrace the new technology, what retraining, skills, or staff are required. 

Dominic Cakebread: Generative AI is developing extremely fast at the moment. Its ubiquitous nature means it is likely to affect all consumer and non-consumer industries and the packaging supply to them.   

Overall, it is likely to lead to widespread automatisation and robotics throughout the value “circle” (i.e., including returning and recycling), improving efficiency and reducing costs, changing (but not necessarily replacing) roles throughout organisations who must once again adapt to survive and thrive.