AI in Warehouse Management: Entering The Future of Logistics

In the early third millennium, artificial intelligence is making a robust advent into multiple industries, accelerating and facilitating shop floor routines in real estate, traveling, insurance, banking, construction, manufacturing, and other verticals. Retail and logistics are following this movement, where this disruptive technology is seen in numerous applications.

This article will explore the most typical use cases of AI for warehouse management, considering the vital benefits and key challenges of leveraging the know-how in this domain. Also, we will offer real-world examples and vital tips, and outline future trends concerning artificial intelligence employment in warehouses.

AI in Warehousing: Use Cases Overview

There are several warehouse management areas where artificial intelligence can elevate pipeline operations to a new level.

Demand planning

To avoid overstocking or stockouts, warehouse managers often struggle with forecasting demand for certain items, especially when they have tons of data to process. For AI tools, working with vast data volumes is a cakewalk. They can be highly instrumental in predicting demand scenarios for products in densely populated urban areas with intense purchasing activity, ensuring the company won’t run out of mission-critical supplies (like packaging materials), minimizing waste, and reducing storage costs.

Workflow automation

When simple and repetitive sorting, transporting, and storing jobs are delegated to intelligent robots, employees can focus on more meaningful or complex tasks that require creativity and human oversight.

Real-time operational transparency

Today, RFID (Radio Frequency Identification) technology is widely applied for inventory and personnel tracking. Adding an AI layer to it can boost object identification, behavior prediction, and workflow optimization in real-time. It shortens the reaction time and improves problem-solving.

Workforce planning

As a rule, managers decide on labor allocation, guided by deadlines, daily volume goals, and productivity indices. Artificial intelligence warehouse management solutions can better handle the labor planning routine, continuously maintaining the organization's maximum efficiency.

Risk management

Economic downturns, pandemics, military conflicts, supply chain disruptions, global canal blockages, and other disasters are significant risk factors that have an impact on product circulation. Warehouses can mitigate these risks by employing high-end AI algorithms that model various scenarios and forecast possible market fluctuations in demand and supply.

Employee performance management

Warehouse managers usually set individual performance objectives based on Engineered Labor Standards (ELS). However, capturing ELS data is often time- and resource-consuming. AI can improve the collection routine by considering numerous variables influencing the task-solving time (work area, work type, distance to travel, etc).

Transportation optimization

Very often, workers cover long distances to pick up orders and deliver goods. AI warehouse management software can significantly optimize the traveling cycle and cut down on fuel consumption and delivery time by choosing the shortest shipping routes, analyzing traffic information and weather conditions to bypass traffic jams, and conducting intelligent batching. The latter technique allows employees to batch orders depending on multiple factors like pick location, product attributes, order priority, travel cost, final destination, etc., and thus avoid unnecessary trips, which paves the way to more ecologically-friendly delivery practices.

Space utilization

Many modern warehouses stick to static product placement, which causes subpar space utilization and inefficiencies in item delivery, especially when product demand changes. AI in warehouses can continuously reassess product layouts by taking into account such factors as seasonality, incoming stock, item dimensions, and real-time sales data. Such a dynamic approach enables personnel always to have high-demand goods within easy reach and minimize retrieval time.

Predictive equipment maintenance

Two years ago, in a survey by McKinsey & Company, 62% of senior managers reported excessive maintenance costs. To counter such wastage, 84% of them planned to embrace a predictive approach to equipment maintenance, and AI-fueled solutions can be a good crutch in this task. They can monitor machinery performance, predict its failures, and schedule optimal maintenance sessions, thus creating a resilient and sustainable warehouse environment.

AI-powered solutions will bring numerous advantages to these (and many other) shop floor processes.

Key Benefits of Artificial Intelligence in Warehouse Management

As a trusted software vendor specializing in AI development, the Requestum team sees the following benefits in using artificial intelligence for warehouse management:

• Improved efficiency: The high degree of automation provided by AI tools enables faster employee performance, greater speed of back-office operations, and higher overall efficiency and productivity of the entire organization;

• Round-the-clock availability: AI-fueled systems work on weekends, don't have vacations, and don't call in sick. They work uninterruptedly, tirelessly performing their duties;

• Enhanced accuracy: Whatever task is entrusted to it, artificial intelligence solves the problem with utmost accuracy and without errors, which are often symptomatic of the human workforce;

• Data-driven decision-making: AI mechanisms turn huge quantities of business, personnel, and customer data into valuable insights that enable managers to adopt optimal decisions concerning every aspect of the warehouse management pipeline;

• Cost reduction: More efficient workflows, error-free operations, and minimal human personnel involvement mean reduced costs and, thus, higher revenues for companies;

• Augmented safety: Automation provided by AI-driven robots, timely equipment maintenance, and reduction of manual labor decrease the number of accidents, improving worker safety and risk-free product handling;

• Sustainability: Shipping route optimization, introduced by employing artificial intelligence, contributes greatly to reducing greenhouse gas emissions and promoting sustainable business practices;

• Increased customer satisfaction: The accurate and efficient performance of warehouses that deliver orders on short notice boosts the level of customer satisfaction. Besides, AI algorithms allow organizations to tailor their services according to individual clients' preferences and even whims, creating ultimate customer experiences and fostering brand loyalty.

Although being highly beneficial for all stakeholders, AI in warehouse management faces various challenges.

Potential Hurdles in Adopting AI for Warehouse Management

When deciding on turning artificial intelligence into a driving force behind their enterprise's digital ecosystems, organizations should be aware of potential pitfalls and bottlenecks they may encounter along the way:

• Data quality: AI mechanisms can bring maximum value to task-solving only if they operate high-quality data. That is why companies should ensure the input data they feed into AI-powered solutions is accurate, complete, relevant, consistent, and compatible in format;

• Implementation cost: Like any other innovative technology, artificial intelligence is a big-ticket item. It requires considerable investments in software development, infrastructure setup, and personnel training. For small and medium-sized companies, one-time expenditure on such a scale may become prohibitive, so it is better to spread out the cost over time and use AI as a service (AIaaS) solutions;

• Legacy IT ecosystems: Many warehouses still rely on obsolete software and outdated hardware, which are hardly compatible with novel high-tech products. To address this challenge, they should focus on integrating AI with existing systems to provide seamless operation of the entire digital environment;

• Lack of skills: For emerging technologies, the lack of qualified staff to implement and operate is natural. Companies can overcome this shortage of skills by launching comprehensive training programs for their workforce, which prioritize fostering hands-on competencies;

• Resistance to change: Very often, managers and rank-and-file employees stick to (not so) good old warehouse management practices and frown at any attempts to change the habitual workflow root and branch. In this case, CEOs should take pains to transform organizational culture and create a universal buy-in among all stakeholders, letting them understand the necessity and inevitability of using disruptive know-how;

• Ethical considerations: The massive advent of artificial intelligence raises ethical concerns about its accountability, transparency, and safety. AI solution developers should ensure the security of their products and the privacy of data processed by its algorithms. At the same time, companies' management should mitigate AI-driven potential job displacement by introducing reskilling and upskilling programs for their personnel.

Addressing all these challenges is a prerequisite for successfully implementing AI-based software in warehouse management.

How to Implement AI for Warehouse Management: Essential Tips

Requestum has completed dozens of AI projects, so we know how to tackle AI implementation in warehouse management initiatives. Let’s explore some tips from our team:

Tip 1. Develop a strategy

Without a well-thought-out roadmap, embracing AI for warehouse management is doomed to failure. To develop such a strategy, you should thoroughly analyze your company’s needs and capabilities, set project goals, and establish the deliverables you want to obtain on completing the endeavor.

Tip 2. Select the right type of AI

In fact, artificial intelligence is an umbrella term used to cover various technologies (machine learning, Big Data, natural language processing, computer vision, image recognition, robotics, and more). You should determine which of them fits your project objectives and will bring maximum value to your shop floor operations.

Tip 3. Keep it simple

We recommend novices in the field start their AI journey by implementing pilot solutions honed to solve specific and small tasks. When your personnel take the changes in their stride and learn to handle novel software well, you can move on to more sophisticated products and gradually increase the scale of AI involvement in your workflow optimization.

Tip 4. Assess the results

You should establish KPIs displaying how much your efficiency, productivity, and customer satisfaction have improved after making AI software an essential element of your IT ecosystem. In case the results don't live up to your expectations, you will understand where the shoe pinches and what you need to do to remedy the situation.

All these tips are no secret to major-league brands that utilize artificial intelligence for their warehouse management tasks.

AI in Warehouse Management: Real-World Examples

Now let’s see how blue-chip companies benefited by employing artificial intelligence in their warehouse management assignments.

• Alibaba and Amazon leverage AI to augment their warehouse layouts' efficiency, improve order fulfillment accuracy, and optimize order-picking routines. Besides, they use AI robots in item-handling operations. Equipped with sensors and cameras, they can easily navigate through warehouse aisles and identify the required product swiftly and accurately;

• Werner Electric relies on a smart inventory system, the core of which is AI and digital twin technology. This combo has allowed the company to streamline its inventory-picking routine and improve picks per hour by 30%;

• UPS. Thanks to its AI-powered chatbot, people can obtain rate quotes and track the progress of their parcels, receiving the best-in-class customer experience. Also, UPS has an AI-fueled ORION system in place that helps determine the most efficient delivery routes, sparing drivers millions of extra miles;

• Project44. The AI tools it employs provide end-to-end supply chain visibility and enable clientele to track shipments in real time;

• IBM. Its Watson Supply Chain solution is leveraged for predictive analytics to sift through historical data and forecast market trends, thus minimizing stockouts, enhancing inventory management, and optimizing production planning. Another AI-powered tool used by IBM is Visual Insights software that automates visual inspection of items found in warehouses, thus ensuring product quality and reducing merchandise returns;

• GE Digital employs the Predix platform to predict possible equipment failures and schedule maintenance, minimizing downtime and extending machinery's service life.

Obviously, these business giants keep abreast of the latest high-tech developments and are ready for deeper AI penetration into their pipeline processes in the near future.

AI-driven Warehouse Management: A Glimpse into the Future

What are the dominating trends in this realm today that are likely to shape the contours of warehouse management for years to come?

• Integration of AI and IoT. The Internet of Things in warehousing is all about creating a comprehensive network of devices (RFID, sensors, cameras, etc.) that communicate with each other without human intervention. By bolstering it with AI, companies will obtain powerful Artificial Intelligence of Things (AIoT) products that will reign supreme in providing operational visibility and control in warehouses. This is one of the fastest-growing market niches that is expected to increase more than seven times within six years, approaching a staggering $254 billion by 2030;

• Augmented usage of Big Data. The wealth of enterprise and consumer data analyzed by AI algorithms will improve operational efficiency, inventory management, and supply chain optimization, reducing shipment time and delivery expenses;

• Natural language processing. This technology will become indispensable for improving human-machine interaction and boosting decision-making related to customer service and personnel management across warehouses.

• Autonomous vehicles. Warehouses are on the cusp of harnessing driverless forklifts that can move goods around the facility and employing drones to perform security and surveillance jobs or locate lost items. The latter will also be increasingly leveraged to deliver small-size orders to customers.

As you see, warehouse management is becoming ever more AI-driven. To keep up with the sweeping changes in the industry, you should implement AI-based solutions into your shop floor operations on a large scale.

Summing It Up

Today, artificial intelligence is one of the most dynamic fields that power digital products across multiple industries. Its application for warehouse management initiatives improves enterprises' efficiency and sustainability, enhances the accuracy and safety of their pipeline processes, reduces OPEX, and promotes data-driven decision-making. AI’s use cases in the domain include demand and workforce planning, workflow automation, employee performance management, transportation and space utilization optimization, predictive equipment maintenance, risk management, and more.

Numerous real-world examples of AI usage by major-league companies for warehouse management prove that organizations can maximize the value of AI by addressing typical implementation challenges and hiring qualified IT outsourcers to develop custom AI-powered software that will fit their business goals.

Requestum is a trusted partner in this endeavor. Our experts develop top-notch AI-fueled products that will let you reinvent warehouse management. Contact us to improve your warehouse management and obtain a competitive edge.