AI Driving Top Trends In Supply Chain Technology For 2024: Gartner

Advancements in technology will provide supply chain technology leaders and chief supply chain officers with opportunities to support new business models, augment and automate decision-making and foster ecosystem collaboration, according to research and consulting firm Gartner.

With these emerging opportunities, Gartner has identified eight supply chain technology trends for 2024 that will help supply chain leaders in pursuit of these objectives. Artificial intelligence variants continue to be both a driver of trends, such as in robotics, and a trend itself, represented by composite AI, this year.

According to Gartner, the top trends in supply chain technology for 2024 are:

Cyber Extortion  

Cyber criminals are successful at executing ransomware attacks to extort funds from supply chain organisations. It is likely that they will utilise AI to generate advanced attack tools, making their attacks even more effective. Supply chain technology leaders should collaborate with IT leadership to confirm that ransomware attack scenarios are included in the corporate risk management processes and develop a detailed ransomware incident response playbook.

Supply Chain Data Governance

The emergence of tools for advanced analytics and AI techniques is scaling the capabilities for cross-functional visibility, scenario modelling and decision automation. As those technologies are increasingly adopted, the importance of maintaining a high level of data quality and strict governance process is becoming critical for businesses.

End-To-End Sustainable Supply Chains

Sustainability-related legislation is growing and driving a shift from voluntary to regulatory compliance. As a result, sustainability data accuracy needs to be enhanced from indicators to being investment grade to meet stakeholder requirements, while driving internal decision making.

AI-Enabled Vision Systems

AI-enabled vision systems are novel hyper-automation solutions that combine industrial 3D cameras, computer vision software and advanced AI pattern recognition technologies. These solutions can autonomously capture, interpret and make inferences based on the unstructured images the vision systems see in real time.

Augmented Connected Workforce

Augmented connected workforce initiatives reduce the time required after onboarding for an employee to become fully productive. ACWF is a strategy to optimise the value derived from human workers by integrating the use of intelligent technology, workforce analytics and skills augmentation. It treats these capabilities as a unified, cohesive strategy to accelerate and scale talent.

Composite AI

Composite AI is the combined application of multiple AI techniques to improve efficiency and accuracy of learning for driving supply chain performance improvements. Depending on the context of a specific use case, different AI techniques—or a combination of techniques—should be utilised rather than relying on a one-size-fits-all approach.

Next-Generation Humanoid Working Robots

Next-generation humanoid robots combine sensory awareness with mobile manipulation and dynamic locomotion to perform productive work earlier done by humans. Humanoid robots will typically imitate the human body with a head with sensors and cameras for sensing its environment; a body that houses the power and mechanicals; arms and hands/grippers for grasping, manipulating and carrying items; and legs for dynamic locomotion.

Machine Customers

Machine customers are nonhuman economic actors that autonomously obtain goods or services in exchange for payment. Examples include IoT-connected devices or assets that place orders independently of a human command, intelligent replenishment algorithms that maintain availability of consumables and intelligent assistants that suggest deals to consumers.