The AI-based consultancy initiative represents a major strategic shift for Cartn from traditional engineering-led consultancy services towards a technology-enabled, data-driven business model. This will affect multiple stakeholder groups in different ways, both positively and negatively.

1. Employees (Consultancy Engineers, Designers, Support Staff)

This is likely the most significantly affected stakeholder group.

Positive impacts:

- Employees may be redeployed to higher-value activities such as:
  - Complex engineering design
  - AI system supervision
  - Sustainability optimisation
- Reduced workload for routine consultancy tasks due to automation
- Opportunity to develop digital and analytical skills

Negative impacts:

- Closure of consultancy offices may result in:
  - Job losses or redundancy risk
  - Reduced job security
- Fear of replacement by AI systems
- Resistance to change and lower morale

Overall impact:

High disruption but potential long-term upskilling opportunities if managed effectively.

2. Customers (Food & Beverage Manufacturers)

Customers are central stakeholders in Cartn’s business model.

Positive impacts:

- Faster consultancy turnaround times
- 24/7 access to AI-driven recommendations
- Improved cost optimisation and sustainability analysis
- More consistent and data-driven packaging solutions

Negative impacts:

- Reduced human interaction with experienced consultants
- Potential lack of trust in AI-generated recommendations for complex packaging needs
- Concerns over data security and confidentiality of product specifications

Overall impact:

Likely positive if AI is accurate and reliable, but trust and transparency will be critical.

3. Shareholders / Investors

Positive impacts:

- Increased efficiency and reduced consultancy operating costs
- New recurring revenue streams (subscription-based AI services)
- Stronger long-term growth potential through digital transformation
- Improved competitiveness versus rivals such as Valboxx

Negative impacts:

- High initial investment and R&D expenditure
- Uncertainty over return on investment
- Risk of implementation failure or cost overruns

Overall impact:

Potentially high long-term value creation, but with increased short-term volatility and risk.

4. Suppliers and Technology Partners

Positive impacts:

- Increased demand for:
  - Cloud services
  - AI software
  - Data infrastructure
- Opportunities for strategic partnerships

Negative impacts:

- Dependence on fewer but more critical technology providers
- Risk of supplier lock-in

Overall impact:

Increased strategic importance but also higher dependency risk.

5. Government and Regulators

Positive impacts:

- Improved sustainability outcomes through:
  - Optimised packaging design
  - Reduced waste materials
- Better environmental reporting capability

Negative impacts:

- Increased scrutiny over:
  - AI decision-making in food-related packaging
  - Data protection and cybersecurity compliance
- Potential regulatory concerns regarding automation replacing skilled labour

Overall impact:

Mixed, but likely positive if sustainability improvements are demonstrated.

6. Local Communities (where offices are closed)

Negative impacts:

- Job losses due to closure of consultancy offices
- Reduced local economic activity
- Potential reputational damage in affected regions

Positive impacts:

- Potential long-term investment in digital infrastructure and new roles in technology hubs

Overall impact:

Likely negative in the short term.

Conclusion

The AI initiative creates a clear shift in stakeholder value distribution:

- Customers and shareholders benefit from efficiency and innovation
- Employees and local communities face disruption and uncertainty

Successful implementation will depend on effective change management, communication and reskilling strategies to balance these impacts.