When integrating AI into your supply chain, watch out for these risks: 1. Data Issues: Poor-quality data can lead to bad decisions. 2. Cybersecurity: Sensitive data may be targeted by cyberattacks. 3. Over-Reliance: Lack of human oversight can cause disruptions. 4. Costs: High implementation expenses may strain budgets. 5. Resistance: Employees or vendors might resist the change. 6. Compliance: AI could introduce biases or privacy violations. 7. Compatibility: Existing systems may not integrate easily. 8. Vendor Dependency: Relying on external AI providers can pose risks. 9. Unrealistic Expectations: Overpromising AI capabilities can disappoint. 10. Disruption: Transitioning to AI can temporarily disrupt operations.

Ai systems are risky when it comes to cybersecurity risks. This meannif there is high value data involved the risk is greater and bigger of a security breach, data leakage, Strong offensive regulations to be implemented such as testing system weaknesses on a fixed and random basis, Since AI models will only rely and thrive on heavy data feeding making it sensitive if data is outdated and poorly collected,regulated. This will be projected immediately to poor decision makijg and wrongful ones. So having neat,highend data is crucial to the success of the model. If i missed something let me know