Sizing the Potential Value of Artificial Intelligence in Logistics

As digitization hits the ground running at global logistics companies, artificial intelligence (AI) is trailing the footsteps to disrupt the industry. To stay competitive and agile, global logistics giants including DHL are capitalizing on AI’s machine learning technologies for automating critical business processes efficiently. As a well-positioned provider of AI development services, Oodles AI explores the practical applications of artificial intelligence in logistics.

Role of Artificial Intelligence in Logistics

With AI becoming more accessible, logistics leaders are exploring AI’s potential for back operations and customer-facing activities to reduce costs and improve productivity. Today, logistics companies are eyeing AI capabilities for automating routine tasks, extracting data and insights, and interacting with customers significantly.

Acknowledging AI’s capabilities in the collaborated report, “Artificial Intelligence in Logistics”, IBM’s Global Industry Leader for Rail, Freight and Logistics Keith W. Dierkx and DHL’s Senior Vice President for Strategy, Marketing, and Innovation Matthias Heutger write-

“Looking ahead, we believe AI has the opportunity to significantly augment current activities in logistics from end to end. AI will fundamentally extend human expertise in terms of reach, quality, and velocity by eliminating mundane and routine work, allowing logistics workforces around the world to focus on more meaningful and impactful work.”

Interestingly, the network-based nature of the logistics industry offers a natural framework for deploying and scaling AI. It has pushed the journey of artificial intelligence in logistics beyond routine tasks such as sorting letters or parcels. Algorithmic advancements have led logistics companies to adopt machine learning development services across warehouses, customer desks, and inventory management.

A Business Insider’s report suggests that early AI adopters in transportation and logistics already enjoy profit margins greater than 5%.

The transformation is possible thanks to AI’s data processing capabilities and to the supply chains generating rich datasets every day. It triggers AI technologies to provide real-time visibility and analysis by training ML models with supply chain data. AI-driven logistics optimization enables companies to solve complex cost and delivery constraints by utilizing in-depth insights and analytics.

A visualization of AI’s key developments in logistics is demonstrated in Mckinsey’s report, Smartening up with Artificial Intelligence (AI)–

Apparently, AI’s benefits for logistics encapsulates reduced inventory risk, route optimization, savings in last-mile costs, and more as we find in the applications ahead.

Artificial Intelligence in Logistics | Applications and Opportunities

1) Robotic Process Automation

For AI to flourish in logistics, it should pivot around human-machine collaborations for major back-office operations including repetitive data entry. Here, the combination of Robotic Process Automation (RPA) and AI can automate and streamline routine business tasks to cut corners significantly.

RPA at logistics companies has already begun to replace clerical labor using software tools that can be easily integrated into business IT systems. Moving ahead, RPA can automate repetitive logistics tasks such as-

a) Collecting and processing data files

b) Shipment scheduling and tracking

c) Order processing and sending confirmation emails

d) Capturing, researching, and closing out loads, and more.

IBM’s report demonstrates how humans and robots can together fine-tune routine tasks to increase profit margins across the realms of logistics.

Also read- Transforming eCommerce Businesses with Robotic Process Automation

2) Natural Language Processing

Some of the core logistics functions are often outsourced through third-party vendors entailing prodigious amounts of invoices and receipts. Manual efforts to process million of invoices annually turn burdensome and cost-consuming for both businesses and employees.

AI technologies such as natural language processing (NLP) are efficient at extracting information such as payee information, dates, addresses, billing amounts, etc. Moreso, the combination of AI’s computer vision and NLP technologies deploys machine learning models to act as advanced OCR (Optical Character Recognition) systems to-

a) Extract information from structured and unstructured files into tabular formats.

b) Make searchable archives of data

c) Automate translation into multiple languages, and

d) Store accurate records on the cloud to reduce heavy server loads

A sneak peek into AI-powered OCR systems powered by machine learning.

Also read- Improving Data Analysis with AI-powered OCR Applications

3) Conversational agents

Another key area in logistics that is on the brink of automation is customer service. With AI-infused conversational bots gaining significant traction, it is time that supply chains also move beyond traditional voice-based picking.

From routine customer interactions to warehouse interactions between operations and IT systems, AI is powering innovative conversational solutions across logistics. Advancements in NLP algorithms are widening the scope of conversational AI for logistics in the following ways-

a) Input, store, and retrieve product information

b) Trigger automated picking system at warehouses with voice inputs

c) Guide drivers with voice-based inputs from route optimization systems

Also read- Conversational AI Trends 2020: Roadmap and Strategy

Realizing the Future of AI in Logistics with Oodles

As the logistics’ tech radar expands, Oodles AI is opening new opportunities for logistics companies to foster growth with emerging technologies. Our AI team is constantly exploring innovative methods for embedding artificial intelligence in logistics to reduce cost and time constraints and improve ROI. With extensive experience in deploying AI technologies, our team extends the following solutions for the logistics companies-

a) Robotic Process Automation for streamlining repetitive back-office operations

b) Conversational AI for standardizing and improving customer and in-house interactions

c) AI-powered OCR systems for extracting critical information from scanned documents

d) Predictive analytics for analyzing online data and conversations, and more.

Learn more about our AI offerings for logistics by connecting with our AI experts.