The proposed AI-based consultancy platform could significantly affect Cartn’s current business model across all four stages of value creation identified in the pre-seen: defining value, creating value, delivering value and capturing residual value.
Currently, Cartn defines value for consultancy clients through the expertise of its engineers and technicians who recommend suitable packaging solutions. The AI platform would broaden this value proposition by providing clients with faster and potentially more cost-effective recommendations.Clients would benefit from
- faster turnaround times,automated packaging recommendations,sustainability optimisation,cost optimisation insights.This aligns with increasing customer demand for efficiency and sustainability in food packaging. The platform may also strengthen Cartn’s reputation as an innovative market leader, particularly as competitors such as Valboxx do not currently provide consultancy services.
However, there is also a risk that clients may perceive automated recommendations as less reliable than advice from experienced engineers, especially where food safety, aseptic packaging or regulatory compliance are involved. Packaging decisions are complex and errors could damage customer trust and Cartn’s reputation.
Therefore, AI should initially complement rather than replace human consultancy expertise.
 
The AI platform could improve operational efficiency within Cartn’s consultancy division.Currently, consultancy work depends heavily on highly skilled engineers. Automation of routine tasks would reduce dependence on scarce specialist staff,improve productivity,allow engineers to focus on complex projects.increase consultancy capacity without proportional increases in labour costs.The system would also utilise Cartn’s historical consultancy data and engineering expertise, allowing the company to leverage its accumulated knowledge more effectively.In addition, the AI platform may improve sustainability outcomes by recommending optimal material combinations that reduce waste and environmental impact. This supports Cartn’s sustainability strategy and may improve its competitive positioning as consumers and regulators become increasingly focused on recyclable and sustainable packaging.However, the creation of value depends on Cartn overcoming capability gaps in AI, data science and digital platform development. The company’s expertise is primarily in engineering and manufacturing rather than software development. Significant investment in recruitment, training and external partnerships may therefore be necessary.There is also a risk of cybersecurity breaches because the platform will contain sensitive client data and proprietary engineering information.
 
The AI platform could significantly improve the speed and scalability of service delivery.Unlike traditional consultancy services, which depend on the availability of engineers, digital services could be delivered continuously to clients across multiple countries simultaneously. This would strengthen Cartn’s ability to support global customers efficiently.The platform may also improve consistency in consultancy recommendations because recommendations would be based on standardised algorithms and historical data.
In addition, subscription-based access could provide customers with ongoing support rather than one-off consultancy engagements. This may improve customer relationships and retention.However, there are operational risks. AI-generated recommendations may not fully account for unusual product characteristics or local regulatory requirements. Human oversight will therefore remain important, particularly for complex packaging projects involving aseptic packaging, frozen foods or sustainability compliance.
 
The AI platform could create new recurring revenue streams through subscription-based consultancy services. This would diversify Cartn’s income beyond manufacturing and traditional consultancy fees.The platform may also strengthen synergies between consultancy and manufacturing operations. Consultancy clients receiving AI-generated recommendations compatible with Cartn products may subsequently purchase more cartons and tubs from Cartn.Furthermore, automation may improve consultancy profit margins by reducing labour costs per engagement.However, the project may require substantial upfront investment in software development,AI systems,cybersecurity,recruitment,staff training,data management infrastructure.There is therefore uncertainty regarding whether the long-term financial returns will justify the investment.
 
Overall, the AI-based consultancy platform could strengthen Cartn’s business model by improving efficiency, scalability, sustainability performance and customer value while creating new recurring revenue opportunities.However, the proposal also introduces significant risks relating to capability gaps, cybersecurity, implementation costs and service reliability. Cartn should therefore adopt a phased implementation approach in which AI supports engineers rather than fully replacing human consultancy expertise.