Introduction
The next big disruption in the technology is already here. Artificial Intelligence (AI), is already making its way to the inundation of operational excellence across industries and businesses. This technology is using its advance algorithm to streamline the products, processes and systems that are able to acclimate and acquire.
Just like other industries, the SCM industry is not untouched by AI’s charm. It is playing an increasingly important role in supply chain innovation. In a study conducted by Gartner with CEOs and senior business executives, CEOs said they expect artificial intelligence (AI) to have the most impact on their industry, with the decision through automation in transportation, is likely to rise from 21% to 56% by 2025.
Further, respondents from the highest performing organisations globally, believe that AI is inevitable to their industry. They see AI as the centre of their innovation and logistical success. The integration of AI into logistics optimization is revolutionizing supply chain management, empowering businesses to tackle the intricacies of contemporary distribution networks with remarkable precision and adaptability. AI-powered tools are enabling companies to optimize inventory management, streamline transportation routes, and predict demand fluctuations with unprecedented accuracy, fostering a more efficient and resilient supply chain.
Emergence of AI in SCM
The need for aggressive use of AI in SCM rolls back to the COVID-19 era and since then, there is no looking back. The onset of the epidemic brought unprecedented challenges to organizations worldwide after the global health crisis disrupted economies, idled manufacturing, and led to erratic consumer behaviour. The dilemma further made the manufacturers and supply chain operators across industries to seek more innovative tools and technologies. Consequently, a significant chunk turned to AI solutions due to the advantages of the technology.
One highly effective application of AI within supply chains involves providing intelligent and business relevant recommendations. For instance, it can be deployed to optimize working capital and anticipate potential shortages. The crucial aspect is its ability to engage in predictive actions, enhancing outcomes in both working capital management and the timely delivery performance in manufacturing and dispatching. Unlike existing enterprise systems, which primarily focus on transaction handling and retrospective analysis, AI excels at accurately forecasting future challenges and prescribing specific actions. This capability allows the system to alleviate the decision-making burden from individuals, enabling them to concentrate on more intricate issues requiring direct intervention. The integration of AI-driven recommendations with machine learning for confidence scoring not only clarifies the path to automation but also contributes to high success rates.
Benefits to Enterprise
Many organisations have been exploring AI-driven platforms to enhance their workflow efficiency and beat the challenges involved in managing the movement of consignment from warehouse to end consumers. In fact, as per to a Gartner report, 50% of supply chain organizations are projected to invest in AI and analytics applications through 2024.
AI in SCM is becoming more popular and widely accepted, organisations fair using it for their real-time data utilization capabilities, to:
- Enhance demand forecasting
- Automate warehouse
- Maintain quality control
- Streamline procurement processes
- Collaborate between multiple stakeholders
- Forecast demand accurately
- Optimize production and delivery schedules
The Future is Here
The adoption of AI in supply chain and logistics has the capability to significantly influence the distribution mechanism, automate and optimize a number of supply chain-related processes, using their predictive analytics and other AI-based technologies. Further, AI can bring down the operating expenses, identify gaps across various steps, and enhance overall customer experience. Manufacturers are now striving to automate a substantial portion of their predictive and prescriptive tasks, aiming to streamline 60% to 70% of these processes. By leveraging advanced analytics, machine learning, and tailored workflows, supply chain executives can seize a competitive edge and navigate the dynamic supply chain landscape effectively. AI’s integration into supply chain and logistics operations promises to improve efficiency, reduce wastage, and better respond to the changing needs of the market demands as it continues to evolve, without impacting the human network to a large extent. It has the potential to transform the technology used to solve supply chain issues by making it more conversational. In future, It is likely to enable professionals to make more informed decisions based on the information available, thereby transforming the role of supply chain professionals to work smarter.
