Connected intelligence across all parts of a supply chain can drive significant bottom-line impact and great customer service. However, despite extensive data and analytics investments, their business impact remains limited due to difficulties of access and lack of adoption.
Large Language Models (LLMs) can close the critical last mile of adoption and impact, democratizing data and insights in an organization. By adding a conversational layer to the organization’s data and analytics systems, the technology makes it easy for users to “ask” for data and access it in seconds. It allows users to converse with the data, drill down for more clarity, or a new angle, or new information. When integrated with an advanced analytics platform, it helps users quickly pull out causal factors, predictive insights, and recommendations for mitigative actions and realignments. By closing the gap between individuals and their enterprise data systems, LLMs can have multiple levels of impact in an organization – profitability, sustainability, innovation, and customer loyalty.
This session will address the fundamentals of implementing Large Language Models in Supply Chain systems –
- Reality and Applicability of Generative AI in Supply Chains
- The Role of Data Quality and Availability
- Model Training and Accuracy
- Importance of Domain Expertise and Interpretability
- Privacy & Security
- Bias & Ethical Considerations
Leverage the gains of Generative AI at scale through well-planned Supply Chain integrations.
