Artificial intelligence

Artificial intelligence-driven supply chain innovation (SCI)

Supply chain innovation includes all activities aiming to deal with the environment’s uncertainty through the generation of information processing and technology innovation to provide solutions for supply chain issues and identify new ways to improve processes.

Notably, supply chain innovation relies heavily on advanced technologies and processes alongside radical changes in product, service, or process that improve efficiency and enhance value delivery to the end customer.

Businesses are increasingly making use of AI techniques to overcome information processing constraints inherent to SCI, resulting in innovative paths of designing new products, solving supply chain issues and satisfying customers, and eventually, potentially establishing new ways to deal with uncertainty.

AI techniques are prone to lead innovation processes by fasting forward new solutions for supply chain issues. This acceleration in innovation capacities stands to enable supply chain firms to create new profit streams more fastly and decrease costs in the process, thereby enhancing supply chain efficiency.

Embedding advanced AI techniques into supply chain innovation empowers innovation activities to be human-centric, creative, and effective in leveraging iterations

1-exploiting techniques

Techniques at this level enable to overcome cognitive information processing constraints and deal with a more considerable amount of data while detecting patterns.

Used techniques

-Machine learning and big data

-Robust optimization

-fuzzy logic and programming

-Stochastic programming

-Knowledge, representation Reasoning


-Process much more massive amounts of information and knowledge

-Support supply chain problems detection

-Overcome cognitive information processing constraints

2-Extension techniques

Extension techniques allow generating new ideas in support of human-machine interaction during problem analysis.

Used techniques:

-Network-based algorithms

-Rough set theory

-Tree-based clustering


Generate new ideas within the supply chain innovation process

Support supply chain problems analysis

Strengthen the interaction between human and machine

3-Exploring techniques

These techniques revolutionize exploring problems and solutions and promoting fast prototyping and evaluation of innovative solutions.

Used techniques:

-Agent-based systems

-Model Predictive Control

-Robotic Process Automation

-Computer vision


Explore new ways of identifying problems

Explore new innovative solutions

Prototype and evaluate the effectiveness of the innovation

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