Generative AI: Opportunities and Risks for Supply Chain Organizations

Generative AI is a digital and operational force to be reckoned with. Since its release at the beginning of this year, ChatGPT has amassed more than 100 million users around the world. Thanks to its predictive (or generative) capabilities, its creative and strategic use cases across sectors are virtually unlimited.

Within freight and logistics, as well as the greater supply chain, generative AI can augment existing processes, automate and speed up operations and predict and optimize supply chain structures and networks. But, for all the benefits it offers supply chain organizations, generative AI does have its fair share of significant risks as well - risks that could cost freight and supply chain enterprises greatly if they're not managed properly.

Let's examine generative AI's role within freight and logistics and supply chain planning and management.

How can generative AI benefit the freight and logistics industry?

Although its adoption across the freight industry hasn't been as swift compared to other sectors, generative AI holds immense potential for improving supply chain stability and improving the operational efficiency of freight forwarders, carriers, and customs brokers across the supply chain.

For freight and logistics companies, generative AI is particularly useful within supply chain visibility, risk management, route optimization, and fleet management.

Within supply chain visibility, generative AI can easily structure and enhance unstructured datasets, using this structured data to better track shipment status and movement across supply chains. It can also prevent efficiency bottlenecks within internal freight operations resulting from data errors, omissions, and duplications, correcting them based on historical data and predictive analytics.

Generative AI can assist with risk management by building digital twins of existing supply chains within a purely virtual sphere. Organizations can use digital twins to run different scenarios and predictive modeling, assessing the potential outcomes without making any adjustments to existing supply chains. Gen AI models can also be used to identify potential geopolitical and climate or weather-related risks, allowing businesses to make changes before these risks impact their bottom line.

Generative AI can optimize existing routes and improve route planning and management by analyzing historical traffic data, weather conditions, and live updates. Using these datasets, it can recommend ideal shipping and fulfillment routes that take speed, fuel consumption, delivery agreements, and other metrics into account. It can support fleet management by using predictive analytics for maintenance and support and providing recommendations for fixing and upkeep.

The risks of generative AI to supply chain security and agility

However, as impressive and expansive as the benefits are to freight organizations, generative AI does pose risks too. Because generative AI tools like ChatGPT and Bing have been trained on vast datasets from the internet, written text, and other sources, the quality of their responses is only as good as the quality of their training data. In instances where gen AI has no data to parse to base its response on, it will often create a fallacious, inaccurate response even with made-up citations and resources to support it.

This is known as a "hallucination" and, when considering the delicate nature of supply chain stability, the risk of errors and miscalculations manifesting in hallucinations could cost freight and supply chain organizations greatly.

Disinformation is another threat that stems from generative AI. Disinformation, including fake, inaccurate, and unverified data can threaten a freight forwarder's, carrier's, and customs broker's data quality and integrity they use for their operations. Inaccurate, fake, and unverified data can compromise an organization's strategic agility and operational planning and influence other shipping partners further along the supply chain.

How can freight organizations leverage gen AI in a safe, effective manner?

Freight and supply chain organizations are faced with a conundrum: use generative AI with the inherent risk of disinformation and hallucinations, or don't use it and miss out on its powerful capabilities. How can freight and logistics businesses harness the power of gen AI and its capabilities without taking on its risks?

There is a solution that makes this possible for supply chain organizations. Stargo is an AI-powered data management and centralization platform that speaks "freight". Aside from robust data cleansing, structuring, and enriching capabilities, Stargo's proprietary generative AI capabilities give freight organizations the predictive agility and accuracy they need - without the risk.

Stargo: safe, reliable generative AI at your fingertips

Stargo's built-in generative AI is trained on clean, reliable freight datasets. Our large language model (LLM) is trained using over 1 million free text samples from over 35,000 real-world emails, ensuring our model produces accurate, reliable, and verified data.

Unlike other gen AI tools like ChatGPT that use general, unspecified datasets from the internet and text, our gen AI platform's self-supervised learning uses only vetted, verified data monitored by our team of specialists. The result? Only accuracy and best-in-quality AI capabilities. Through Stargo, you can harness the unlimited power of generative AI safely and effectively, for reinforced data integrity and greater operational efficiency.

Book a demo and see what Stargo can do for your productivity and profitability.