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Discovering untapped AI potential in the logistics industry

AI’s potential in logistics extends far beyond warehouse robots and self-driving trucks.
The past few years have been a perfect storm for the logistics industry, with pandemic disruptions, labor shortages, and interest rate swings all wreaking havoc on supply chains.
Fortunately, industry insiders see AI turning the tide. While technologies like warehouse robots and self-driving trucks tend to grab headlines, AI’s potential extends far beyond these high-profile applications.
Learn some lesser-known ways logistics companies can leverage AI to propel themselves toward a more efficient future.

How AI is used in logistics: Four underrated use cases

1. AI-powered predictive analytics unlock unprecedented forecast accuracy

The pandemic exposed the limitations of traditional demand forecasting. Manufacturers grappled with a whiplash effect — one moment, they were struggling with shortages of cars and furniture, and the next, they were drowning in excess inventory.
Pinpointing future demand has historically been a frustrating guessing game for producers. But with AI, the holy grail of precise demand forecasts is within reach.
Traditional models that rely mainly on past sales data become meaningless in unprecedented times like the pandemic. Instead, AI-powered predictive analytics take a wider array of variables into account.
These algorithms incorporate real-time market trends, external events, and social media sentiment. Armed with this data, logistics companies can avoid stockouts and overstocking.
The benefits don’t end there. AI can also leverage historical maintenance data to anticipate equipment failures, preventing costly downtime and ensuring seamless operations.

2. The rise of the intelligent supply chain

Modern supply chains are a well-orchestrated dance between global manufacturers, distributors, and logistics companies.
They’re incredibly efficient but also fragile. As we saw during the pandemic, delays at a port, labor shortages at a warehouse, or unexpected spikes in demand can quickly throw the entire system out of sync.
This doesn’t mean we need to sacrifice efficiency for resilience. AI is powering a new generation of supply chain intelligence that can more easily adapt to unexpected shocks.
Read our related case study for Dicom Logistics.

A network that responds, not reacts

Intelligent supply chains are vast networks of interconnected data points. Warehouses, carriers, distributors — even customer data — all feed into this ecosystem. AI can analyze this data stream and proactively identify potential issues before they lead to a chaotic domino effect.
Let’s imagine a scenario where a shipment is held up at customs. Traditionally, this would trigger a flurry of phone calls and emails, scrambling to inform stakeholders and adjust delivery schedules.
In the intelligent supply chain, however, the system reacts proactively. AI can:
  • Automatically trigger alerts: The moment a delay is flagged, relevant parties across the supply chain receive instant notifications. This allows them to explore alternative sourcing options or adjust production schedules proactively.
  • Optimize inventory levels: Forecasting algorithms can analyze the expected delay and adjust inventory levels at the destination point. This prevents stockouts and ensures customers still receive their orders on time.
  • Enhance the customer experience: We’ve all experienced the disappointment of a package that doesn’t arrive on time. Real-time shipment tracking and potential delay notifications keep customers informed so they can adjust their expectations accordingly.
The intelligent supply chain is not just about efficiency. It’s about building resilience in a world of constant change. Leveraging AI to proactively identify and address potential issues can help companies ensure a smoother flow of goods and a better customer experience.

3. Augmenting human decision-making with AI recommendations

The rise of automation and AI in logistics has sparked anxieties among workers fearing job displacement. Like any new technology, AI will replace some jobs. But generally, AI is most effective when it augments human expertise, rather than replacing it.
Consider the tedious tasks of data consolidation, cleaning, and labeling. Anyone who’s worked an analyst-level job has suffered through this drudgery and would prefer to avoid it entirely.
AI excels at repetitive tasks like these, but it lacks the human touch. It can’t make nuanced decisions based on an understanding of the bigger picture.
The real magic happens when you combine the two. Now freed up from data processing tasks, analysts can spend more time on value-adding work. This might involve investigating the root causes of flagged delays, using data insights to negotiate with suppliers, or contributing to strategic planning.
The future of logistics lies in humans and AI working together. AI excels at data analysis and pattern recognition, while humans bring their experience, intuition, and problem-solving skills to the table. By combining these strengths, you can achieve truly remarkable results.

4. Redefining trucking route optimization with AI-powered algorithms

Trucking route optimization traditionally relied on static maps and historical data, which were easily thwarted by traffic jams or unexpected storms. This led to winding journeys, wasted fuel, and frustrated customers.
AI-powered algorithmic route optimization is rewriting the script. These models incorporate historical and real-time data to create the most efficient routes possible and suggest detours when necessary.
Along with taking real-time traffic and weather conditions into account, route optimization algorithms can factor in driver availability and skill sets when creating routes. This ensures that drivers with specialized skills, like a commercial vehicle endorsement (CDL), are assigned to appropriate deliveries.
Moreover, optimizing routes for specific vehicle capacities prevents overloading and ensures efficient fuel consumption. This translates to cost savings for businesses and a smaller environmental footprint.

The future of AI in logistics

These applications merely scratch the surface of how AI is used in logistics. Whether it’s AI-powered chatbots that handle customer inquiries or smart packaging solutions that optimize container space, the possibilities are endless.
Logistics operators that harness these capabilities will have a significant leg up going forward. But AI tends to be outside their expertise — they know the ins and outs of supply chain management, not necessarily how to train a large language model.
That’s why it’s imperative to enlist the right partner to guide you through this technological transition. Our team of senior engineers at Lumenalta has decades of experience helping companies take advantage of cutting-edge technologies. AI implementation can be complicated, that’s why we work closely with our clients to ensure their solutions are built to drive value and adhere to industry regulations and best practices.
Read next: Is your business AI-ready?

Learn more about leveraging AI in logistics.