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The future of Supply Chain Logistics to be driven by AI and ML
Today, AI has become more accessible than ever. It is progressively used to improve business operations and outcomes in transportation and logistics management and also across diverse fields like finance, healthcare, retail, and many others. An Oxford Economics and NTT DATA survey of 1,000 business leaders conducted in early 2020 has revealed that 96% of companies were at least researching AI solutions, and around 70% had either fully implemented or at least piloted the technology.
Nearly half of the survey respondents said that the failure to implement AI would cause them to lose their customers, with over 44% reporting their company’s bottom line would suffer without it.
In general, AI enables companies to parse huge quantities of data and make well-informed and vital business decisions fast. The transportation management industry is specifically using AI and its companion technology, ML, to gain greater process efficiency and performance visibility. It drives impactful changes bolstering the bottom line.
Tools reduce costs and increase revenue
A McKinsey research has revealed that 61% of executives have reported decreased costs, and 53% have reported increased revenues due to introducing AI into their supply chains. Lower inventory-carrying costs, reductions, and lower transportation and labor costs are some of the most significant areas for savings captured by high-volume shippers for supply chains. AI has boosted supply chain management revenue in sales, forecasting, spend analytics, and logistics network optimization.
The ML portion of this emerging technology helps organizations enhance their routing and plan for weather-driven disruptions. For instance, through pattern recognition, ML helps transportation management professionals understand how weather patterns in the past affected the time it took to carry loads, then considers current data sets to make predictive recommendations.
Pandemic accelerates the adoption of AI and ML
The COVID-19 pandemic has put a tremendous amount of pressure on many industries, but at the same time, it has come with a silver lining. This pandemic has provided an opportunity to change!
As organizations are increasingly transforming to work smartly to fulfill customers’ expectations, there is an increased appetite to retire inefficient legacy tools and invest in new processes and tech tools to work more efficiently.
Applying AI and ML to pandemic-posed challenges can make a crucial difference between accelerating or slowing growth for transportation management professionals. When applied correctly, these technologies improve logistics visibility, offer data-driven planning insights, and successfully increase process automation. However, organizations should perform due diligence when considering the application of AI and ML to their operations.
Data quality should come first
The essence of an effective AI program is proper data hygiene and management. But, compiling, organizing, and accessing this data is a significant barrier for many. As per a survey conducted by O’Reilly, 70% of respondents reported that poorly labeled and unlabelled data are a significant challenge
The transportation industry has recently begun making up ground to embrace AI in the next five years. Gartner has also predicted that by the end of 2024, 75% of organizations will move from piloting to operationalizing AI and driving a five times increase in streaming data and analytics infrastructures.
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