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Artificial intelligence is revolutionizing the supply chain.

Sales forecasting, error detection, inventory management, lead time improvement, task automation... Its power is immense. A hybrid role by definition, the AI project manager in supply chain drives technological developments in AI with the aim of improving logistics performance and optimizing transportation. 

Presentation and responsibilities of the AI Supply Chain Project Manager

They are known as AI managers or project managers in supply chain. They build AI and data ecosystems, leverage AI technologies, and support the transformation of the organization's supply chain. They develop strategies for streamlining logistics management processes and improving information systems by selecting stakeholders and tools.

The AI project manager in supply chain conducts audits, makes diagnoses, defines the scope of intervention, and activates logical levers. He or she directs operational management, manages the planning of AI and data projects, and monitors the implementation and deployment of new solutions while respecting costs, deadlines, ethics, and constraints.

To ensure technological transition in the supply chain, he raises employee awareness of the issues at stake and trains them in new processes (whether involving physical or information flows). He coordinates teams on various common topics, always liaising with senior management.

Through the implementation of AI and data, it is modernizing the logistics chain and transforming the supply chain model to improve speed, adaptability, reliability, and efficiency.

Business implications

AI and data in the supply chain are involved in several areas

Data analysis can accelerate the automation of logistics processes (Robotic Process Automation), inventory forecasting and management (e.g., Amazon's warehouse managed by 4,000 robots), fraud detection, production control, delivery process evaluation, foreign language data decryption, and more.

Chatbots and callbots improve customer and supplier services

Augmented reality can now be used to train employees in different warehouse positions or guide them in their searches (thereby reducing errors).

Robotization enables depalletizing, for example, and will eliminate tedious tasks, thereby adding value to professions.

All these advances represent a gain in terms of time and money.

One example in this area is the ENGIE/VEKIA partnership, which involves end-to-end supply chain management: ENGIE carries out 14,000 interventions per day (maintenance, heating/air conditioning repairs, etc.), has 1 million references in its information system, and stocks in 230 agencies.

VEKIA's goal is to use AI to automate warehouse orders, calculate remaining stock levels each time, and make order proposals for each management point.

Ethical implications
The supply chain raises many ethical issues:

Environmental impact and sustainability, sourcing and origin of raw materials, CSR, etc. Since the supply chain uses big data, its handling must respect the rights and freedoms of all (transparency, confidentiality, security, impartiality, human supervision, etc.).

The AI supply chain project manager can consult experts such as artificial intelligence lawyers or ethics officers, who provide valuable support in addressing these complex issues.

Aivancity's programs incorporate all aspects of artificial intelligence and its challenges, whether technical, technological, commercial, ethical, or legal, into their curriculum. It is a comprehensive, hybrid program that enables future engineers to meet the many economic and societal challenges associated with harnessing the potential of data and artificial intelligence. It can be supplemented by doctoral or PhD studies.
Key skills
Supply chain AI manager is a hybrid position that requires both extensive knowledge of supply chain management and significant technological expertise. Proficiency in software, IT tools, and AI/data systems is essential (ERP, TMS, WMS, EDI, machine learning, IoT, NLP/NLU, data science, etc.). Complex data analysis is also one of the key skills required for this role.

The AI project manager in supply chain is familiar with supply chain professions and processes (S&OP, sales & operations planning, sources of performance improvement, resource optimization, flows, and inventory). They are also familiar with AI and data professions and organize interaction between different experts on joint projects.

A skilled communicator (in English and French), he has excellent interpersonal skills. His leadership abilities help him engage teams in his transformation and continuous improvement projects. Analytical skills, accuracy, logic, and methodical thinking are his primary qualities. Technology monitoring is important for the position, and anticipation allows him to always stay one step ahead.

Trends and factors driving change
The AI project manager in supply chain can progress to a position as supply chain director or AI director. They can also offer their services as a consultant.

Transforming the supply chain and its professions, AI and data innovations open up fascinating prospects. The list of challenges to be tackled is at its peak for the AI project manager in supply chain.

*IAgénieur and AIgineer are registered trademarks protected by Aivancity.