Recently, supply chains have become significantly challenging to manage, increasing physical flows reflecting the rising product portfolio complexity. Market volatility caused the pandemic has increased the demand for flexibility and agility. With increasing attention on the environmental effect of supply chains, organizations and shareholders are being more focused on supply chain resilience.

Supply chain solutions based on Artificial Intelligence (AI) are expected to be a powerful tool to assist companies in tackling hardships. Artificial Intelligence’s potential to analyze massive data, understand relationships, offer operation visibility, and support better decision-making has made this technology a game-changer across different industry verticals.

The Transition Face of Supply Chain Management

AI-based tools are being leveraged throughout the supply chain industry. The purpose is to maximize efficiency, minimize the effect of global labour shortage, and identify safer methods to transport goods.

Logistics companies use IoT devices to obtain and analyze shipment items and track the mechanical health and expensive vehicles and tool location. In several companies, supply chain management has focused on dynamic optimization of the organization’s global value rather than simply enhancing their local functional performance.

Few benefits from AI in supply chains are less tangible than others; for instance, identifying the effect of predictive analytics based on supply chain data can yield benefits. However, few organizations are reporting a direct link between revenue shifts and the addition of AI in supply chains.

According to McKinsey & Company, the research found that 61% of employees who included AI in their supply chain management report minimized costs and more than 50% revenue increase. An IBM article “AI is reshaping the supply chain” featuring Arnaud Morvan, the senior managing director of Aera Technology, found 4 pros of applying AI to supply chain challenges:

• Minimized manual labour operation
• End-to-end transparency with real-time data
• Informed decision-making augmented by ML, AI-driven predictions, and suggestions based on analyzing different potential situations.
• Actionable analytic insights based on pattern identification
• AI Optimizing Routing Efficacy and Logistics Delivery 

In today’s world, anything can be ordered online and delivered anywhere with the help of data. Organizations that don’t have a robust method of tackling delivery logistics are prone to higher risks. Customers expect swift, accurate shipping.  Customers are ready to turn somewhere else when a firm cannot offer services or products as desired.

AI-driven route optimization networks and AI GPS tools create the most effective routes from all the potential scenarios. A task flawed with traditional methods, which have been inadequate for analyzing different possible ways.

Demand Forecasting

Machine Learning is leveraged to determine patterns and influential supply chain data factors with algorithms and constraint-based modeling. This allows warehouse managers to make better decisions about inventory management.  AI leverages AI to power its Inventory Optimization network, which offers warehouse managers data on components, finished goods, and parts in real-time.

Cost-saving and Revenue Enhance Methods

Transporting goods around the globe is becoming more expensive. According to, a Bloomberg report, the expense of transporting items by logistics increased by 12% in 2020. Artificial Intelligence in supply chain innovations is transforming the way for a better future, where we can expect to see AI-powered autonomous vehicles. The data these networks are mining and analyzing will continue to enhance the cost and efficacy of an increasingly complex worldwide supply chain.

In a nutshell, Artificial Intelligence, Machine Learning, Big Data, Deep Learning, Computer Vision, NLP are such revolutionary technologies that can automate the industries in the manifold.