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Technical debt in supply chains arises from outdated systems and inefficient processes, leading to increased costs and risks. Generative AI offers a solution by automating workflows and enhancing data integration, which can significantly improve supply chain efficiency. The reliance on legacy systems and manual processes exacerbates these issues, making it crucial for companies to adopt modern technologies.
Generative AI, particularly through large language models (LLMs), can optimize decision-making and predictive analytics in supply chains. By automating tasks and providing real-time insights, it empowers managers to make informed decisions, ultimately reducing operational costs. However, careful implementation and data governance are essential to avoid deepening technical debt.
• Generative AI can automate workflows and enhance supply chain efficiency.
• Legacy systems contribute significantly to technical debt in supply chains.
In supply chains, technical debt results from outdated systems and inefficient processes.
It plays a pivotal role in enhancing data integration and decision-making in supply chains.
LLMs facilitate better communication and data interpretation among supply chain stakeholders.
Tredence's expertise in supply chain and manufacturing is highlighted in the context of addressing technical debt.
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