Predictions 2024: How AI will Get us Closer to Completely Autonomous Supply Chains

A quick look at the six AI-powered trends:?

10X Productivity: AI-powered co-pilots will be more capable of identifying issues, recommend accurate solutions and even escalate issues if needed, helping achieve 10X productivity.

10X Predictability: Leveraging AI and all the data that resides across the different parts of a supply chain, business will be able to predict outcomes 10 times more accurately.

Leveraging Public Digital Infrastructure: Making the most of the technology infrastructure being provided by the Government to drive efficiencies and process optimization.

A New UI: AI-powered chat with co-pilots will completely alter how enterprise software is used across sales to operations execution.

Focus on Planning: To reduce the firefighting on logistics execution, a lot more focus will move towards AI based planning techniques across line haul, last mile, manpower and more.

Unified Fulfillment will be the Future of CX: A unified fulfillment experience that integrates warehousing, inventory and transportation will redefine supply chain management.

Let’s talk a bit more about each of these trends.

AI, AI and some more AI, that is how I would describe the future of supply chain management. From improving productivity and predictability by 10X, automating issue identification and resolution, fostering generative AI powered conversations to reducing costs and boosting CX, AI will become the very core of autonomous supply chains and unified fulfillment experiences. Here are six amazing supply chain trends that will rapidly emerge in 2024 and beyond.

#1. 10X Productivity?

AI-powered agents and co-pilots will be more capable of identifying issues, recommending accurate solutions, and even escalating issues if needed, empowering businesses to achieve 10X productivity. To improve incident management, we are creating intelligent and automated workflows. However, the future of this phenomenon will ultimately involve the creation of AI agents. Logistics leaders will be able to set KPIs for such agents, and it will be possible to clearly outline things like where these agents will receive data from, what critical areas they will monitor, the actions they should take, and finally, how they create and deliver reports based on their analysis.

Support agents who used AI could?handle?13.8% more customer inquiries per hour—Nielsen Norman Group

#2. 10X Predictability?

Supply chain leaders are transitioning from reactive to proactive decision-making. This shift can be readily achieved by utilizing AI to analyze and act upon data from various supply chain functions. For example, consider a driver en route for a delivery. The system analyzes all the real-time data of the journey, such as speed, traffic conditions, and stops along the way. It then determines that a particular pickup scheduled for 6 pm will not be completed on time. As a result, the system dynamically reallocates the order to a rider who is in a much better position to meet that pickup time. This approach will enable businesses to predict 10-times more accurately.

#3. Greater Usage of Public Digital Infrastructure?

Governments across the globe are focusing on strengthening the supply chain’s digital infrastructure. Businesses will rapidly see themselves leveraging this technology infrastructure to drive logistics efficiencies and process optimization. For instance, integrating location data received digitally from customers with national address databases will drastically enhance location accuracy resulting in greater delivery success and optimized costs.?

#4. A Completely New UI

It would not be incorrect to state that Generative AI and LLMs (Large Language Models) will transform enterprise software just like cloud computing and analytics did. Integrating AI co-pilots with applications across finance, supply chain, and customer service sectors will enable businesses to interact with systems through chat interfaces. This integration will provide access to highly accurate responses, derived from real-time signals such as location data, inventory data, carbon emissions tracking data, ETAs, rider data, customer feedback, and so on.

45 % of businesses are currently employing AI-powered demand forecasting, and 43 % aim to do so over the next two years—Gartner

#5.Focus on Logistics Planning

Logistics planning is time-intensive and dynamic. Therefore, employing techniques such as dynamic network planning, dynamic hub operations planning, dynamic line haul planning, and dynamic workforce planning, among others, saves significant time and costs by thousands of dollars. For instance, through dynamic hub operations, businesses can automatically generate mid-mile trips, tailor trips according to stops and consignment destinations, and monitor all line-haul movements on a single dashboard.

#6.Unified Fulfillment will be the Future of CX?

To enable truly end-to-end logistics transformation for businesses across manufacturing, retail, and logistics service providers (LSPs), while ensuring a completely integrated fulfillment experience, a unified warehouse, inventory and transportation management system will be the future. It’ll drive cost efficiency by eliminating the need to invest in integration resources and data management. Businesses will have access to a single source of truth to gain real-time knowledge on warehousing, transportation and order fulfillment. Dispatch times can be drastically reduced by eliminating double sortations. It’ll also improve responses to transportation risks and management of docks and staging areas.

These are exciting times for the global supply chain industry. With AI becoming mainstream, businesses have a massive opportunity to break traditional practices and become more competitive, profitable, resilient, and customer-centric.