Introduction
With the eruption of e-commerce, the logistics scenario experienced a great revolution in the 2000s. As a consequence of the e-commerce fever, the necessity for efficient operations and enhanced processes gained more importance as customers’ expectations and outlook towards goods and services are dynamic by nature, and businesses like to successfully steer through periodic highs and lows.
This is where Artificial Intelligence (AI) surfaces as a major player, delivering ground-breaking solutions to the challenges and concerns confronted by the global logistics industry.
Now, what is AI in Logistics?
The logistics industry which is a critical constituent of the globalized economy is infected with several challenges and concerns in the present competitive international market scenario. The typical challenges can range from handling multifaceted systems, increasing transportation budgets, and fluctuating consumer expectations, to restructuring operations. Moreover, the industry is struggling to cater to the demands and requirements for enhanced customer service, dealing with enormous volumes of data, capping transportation expenditures, and comprehending and integrating compliance laws and standards.
But AI is a technology that is swiftly transforming the logistics industry and making it more appropriate for contemporary times. It denotes the application of algorithms and machine learning to automate and boost different logistics procedures. It is already being implemented to automate repetitive chores and offer in-depth understandings of the present and future that were formerly impossible to attain.
AI is mostly compatible with logistics owing to the industry’s far-reaching networks. By considering and analysing already gathered data, AI can envisage future production and transport capacities, and this results in more effectual resource mobilization and utilization. Accordingly, tasks are being given to self-learning digital systems at an ever-growing speed without any hesitation.
Present Challenges and Concerns in AI Adoption
Budget of Application & Upkeep
AI implementation comes at a price. Implementing AI technology frequently needs significant investment in hardware, software, security systems, and overall infrastructure, which can be expensive.
Now, above things are not the only things you invest in. Furthermore, constant maintenance, modernization, and training may be necessary to ensure the smooth functioning of AI systems for delivering precise results. This increases the general expenditure. For SME companies or those with inadequate resources, these overheads can be unaffordable and usually stop them from completely applying AI technology. At times, this inability affects ROI negatively.
Deficiency of Resources
Most establishments are completely devoted and invested in AI but a maximum number of them don’t have the essential in-house experts to execute their strategy and achieve their AI aim. Since it is a comparatively new technological phenomenon, problems are many.
Now, you need to educate and train people about AI so that they are interested in it. Evidently, education and training is the fundamental hurdles to entry of experts in this field as well as organizations. The cost of employing and training employees to make them accomplished in AI technology further pushes up the total budget of application and maintenance. This can slow down the organization’s advancement in technology to a great extent.
Apprehensions Pertaining to Privacy & Security
One of the principal challenges is the potential of AI to be utilized to encroach upon privacy and compromise security.
Since, AI systems depend on and manage sensitive client data, chronological cyber security gaps have made businesses hesitant and also lacking in self-assurance when it comes to implementing and also upgrading technology solutions. In this case, it’s vital to reflect if AI is suitable to embed because some procedures may offer themselves to other methods of automation.
Usages of AI in the Global Logistics Industry
Enhances Relationship with Consumers
AI has proved to be beneficial in enhancing relationships with consumers. You can automate the search process, and purchaser’s expectation management, and speed up response time to customers by implementing AI.
Virtual assistants aid visitors to a website to steer their search through diverse product prospects without getting confused and lost. Again, Chatbots can be applied to all dealings at B2B marketplaces to ascertain the most popular procurement requests and then handle purchasers’ expectations accordingly. Also, with the help of AI businesses can cut down on customer response time and also reduce the prerequisite for customer care personnel. For example, presently, customers use voice-based solutions to keep track of their shipments and the entire experience is very tailor-made. DHL is in partnership with Amazon. So, DHL clients can request the Alexa app to connect with Amazon Echo. The customers can obtain status updates of their consignments by probing Alexa and immediate information about the movement of their deliveries. If any issues occur, Echo users can straightaway connect with DHL for support from its client support team.
Better Inventory Management
Now, what is inventory management? Inventory management is the method of handling and tracking the goods and merchandise that a business holds in stock. It includes tracking and managing inventory levels and ordering and replenishing products accordingly, and making sure that the inventory is supervised competently.
AI-powered inventory management software can support especially e-commerce businesses in making improved inventory choices by automating various labor-intensive procedures. Conventionally, these manual processes were timewasting, predisposed to human mistakes, and lacked the ability to deliver actual insights into inventory levels and customer demand patterns. But, now implementation of AI helps in analysing huge volumes of data and offers real-time insights into inventory levels, demand and supply needs. This also involves evaluating data from point-of-sale systems, past sales statistics, and supplier data.
The use of AI in inventory management has numerous benefits for logistics firms like – decreases unintended downtime of machinery and software, detection of patterns and problems before occurrence, and enhances equipment lifecycle by detecting maintenance needs early, this, in turn, lessens the necessity for expensive substitutes and increases the general efficacy and usefulness of logistics operations.
Supports Demand Forecasting
AI has considerably enriched demand forecasting in logistics. But what is demand forecasting? Demand forecasting systems are extremely useful for e-commerce businesses. It helps to derive more precise sales predictions and boost their inventory levels according to predictions, which, in turn, results in enhanced supply chain efficacy and improved client gratification levels.
Now, predictive analytics and demand forecasting models, power-driven by AI, have empowered improved production planning. Again, machine learning algorithms are being used to augment routes and shipment loads, resulting in more effective logistics processes. Moreover, AI can automatically regulate inventory levels depending on actual data, thereby cutting down the possibility of overstocking or understocking.
Smart Warehousing
Warehouse operations have been revolutionized with the incorporation of AI. Implementation of robotics is the most happening thing in streamlining warehouse operations. Presently, inventory tracking has been automated using AI cameras and sensors, thereby, decreasing human mistakes and enhancing efficacy. Again, self-driving robots are being used for locating, gathering, and sorting, packing, and shipping items. This definitely expedites the entire procedure and decreases the necessity for engaging is physical labour. Finally, Computer vision, a subcategory of AI, is being applied for stress-free inbound assessments and quality control.
For example, according to some reports Amazon has deployed 200.00 robots in their fulfillment centers to work together with humans.
Smart Roads
Smart traffic solutions include roads that integrate sensors, solar panels, AI, and big data to boost visibility, communicate with independent vehicles, and observe carefully into road situations. It significantly benefits the industry by guaranteeing the safe shipping of goods.
Optimization of Transportation & Delivery
AI is improving transportation and delivery in numerous ways. Like, AI route optimization is being implemented for fuel and delivery efficacy, thereby, decreasing expenditures and environmental effects.
Again, vehicles are a big headache for the logistics industry. Their frequent breakdown, fuel wastage and cost, and other things are a matter of financial stress. So, machine learning is being utilized for predictive looking after and repairs of vehicles, cutting down on time loss and increasing the lifecycle of the vehicles. Also, natural language processing, another subsection of AI, is being exploited to automate booking, mapping out, and tracking, refining customer service and overall efficiency.
Conclusion
AI integration is necessary for the logistics industry to take certain necessary steps like – beginning small, but scaling up, taking stock of data readiness, up-skill your professionals with new skills regularly, fixing strict targets, and creating partnerships with AI vendors and specialists. The integration of AI in logistics is bringing enormous worth through various improvements across operational capacities.
