Artificial intelligence (AI) is a technology that enables machines, software, and systems to emulate some types of human intelligence and behavior. AI is powered by systems that use “smart agents” and complex algorithms to understand information, perform tasks, and adapt to changing inputs and environments.
Typically, AI uses human reasoning as a model for decision making, with the goal of providing better insights, products, services, or efficiencies. There are many subfields of Artificial Intelligence including machine learning, natural language processing, planning, problem-solving, and robotics.
Artificial Intelligence Development in the supply chain has several applications, including information mining, data analysis, supply and demand planning, autonomous vehicles, and warehouse management.
Impact Of AI in Supply Chain Management:
AI-enhanced customer experience:
AI changes the relationships between logistics providers and customers by customizing them. An example of personalized customer behavior is DHL Parcel’s cooperation with Amazon. The courier company offered a voice service to track packages and get shipping information using Amazon’s Echo powered by Alexa.
A customer can check with Alexa to find out the current whereabouts of their shipment by asking “Alexa, where is my package?” or “Ask DHL where my package is”. If there is a problem with shipping, Echo users may also request assistance from DHL and be redirected to the company’s customer service department.
Recommended: How AI is Revolutionizing Supply Chain and Logistics?
AI provides insights to improve supply chain management productivity:
AI can provide unmatched analysis of supply chain management performance, which, in turn, helps determine new factors that affect that performance.
According to the aforementioned report from DHL and IBM, artificial intelligence combines the powerful capabilities of three sophisticated technologies (supervised learning, unsupervised learning, and reinforced learning) to identify important factors and issues that affect supply chain performance.
For example, supervised learning can detect identity fraud and make informed predictions, while reinforced learning can facilitate real-time decisions by providing relevant data.
IBM’s Watson is one example of artificial intelligence used to drive knowledge and productivity in supply chain management, One Network’s Neo is another.
AI for global supply chain management planning:
Supply chain planning and optimization, including demand forecasting, are among the key areas where AI is already beginning to be implemented. Experts say that global supply chains have become so complex and affected by so many variables that AI can be essential in helping to identify and predict problems and possible solutions.
Consequently, companies are already applying artificial intelligence-based machine learning to automatically analyze large amounts of supply chain management data, identify trends, and generate predictive analytics, the ability to predict problems and outcomes. Lippincott says that benefits in managing the global supply chain include reductions in forecasting errors. “Software technologies are beginning to apply artificial intelligence abilities that can easily find errors and make corrections while processing data streams in real-time,” he says. “With industries founding a large amount of data that can be used to train algorithms to figure out where things went wrong, we are at the tip of the iceberg of how much companies will leverage these capabilities.”
Benefits of AI in the Supply Chain Management:
1. Improved security: Automated AI-based tools can ensure smarter planning and efficient warehouse management, which can improve the safety of workers and materials. AI can also analyze workplace safety data and inform manufacturers of potential risks. You can record storage parameters and update operations along with necessary feedback loops and proactive maintenance. This helps manufacturers react quickly and decisively to keep warehouses safe and compliant with safety standards.
2. Accurate inventory management: Accurate inventory management can ensure the correct flow of items in and out of a warehouse. Usually, there are many variables related to inventory such as order processing, picking and packing and this can be time-consuming with a high tendency for errors. Additionally, accurate inventory management can help prevent overstocking, inadequate stocks, and unexpected stockouts.
3. Reduce manual human labor: “Supply chain management spends countless time collecting data from different systems and using BI tools or spreadsheets to design strategies. It is an increasingly difficult task,” says Morvan. “There’s just too much data, too many applications, and too many variables to take into account. Cognitive automation takes over the heavy lifting that humans traditionally do. It offers deep analysis down to the SKU level, not practical with a manual approach.”
AI use cases in Supply Chain Management:
Workforce planning: Workforce planning is a must for any modern industry. It involves processes like hiring, retention, employee development, reassignment, performance management, and a few others. Machine learning and artificial intelligence (AI) solutions can significantly simplify these and make your workforce planning strategy more efficient. This is important, as employees who like your organization and the way you work are more productive. And with such a team, your business will be more successful.
Supplier Relationship Management: Selecting a reliable supplier and maintaining a proper relationship with them can be a great challenge. If you make the wrong decision, your business can suffer, and the same can happen if you make a mistake in managing your cooperation. In the worst case, your business may even fail. But you do apply machine learning to your data sets based on your supplier relationship management actions (for example, audits and credit rating). You will get fairly reliable predictions for every interaction with your existing or potential vendor. This tip will help you avoid many mistakes and build a mutually beneficial collaboration.
Cost To Develop AI in Supply Chain Management:
While a few years ago only companies like Google, Microsoft and Facebook could afford to develop ML-based software, now a large number of companies can too. Thanks to the emergence of various tools, libraries and frameworks for creating ML-based software, the technology is becoming more and more available to businesses.
Prices are calculated for each case individually, but often:
Prototype development starts from $ 2,500
MVP starts from $ 8,000 and generally costs up to $ 15,000
The complete solution can cost from $ 20,000 to $ 1,000,000
However, it all depends on the scope and complexity of the project, customer and system requirements, as well as other factors, mentioned above.
Final thoughts of AI in supply chain management:
The current scenario has exposed vulnerabilities in nearly every company’s supply chain, with 94% of Fortune 1000 companies experiencing supply chain disruptions and the consequent degradation of their growth outlook. This has been a risk event that virtually no supply chain risk management contingency plan has taken into account. According to some, this may well be the black swan event that triggers a comprehensive, large-scale transformation of conventional supply chain models. The capabilities and technologies needed to drive effective supply chain transformation are readily available. Technologies such as ML and AI in supply chain management have the potential to deliver intelligent, data-driven supply chains that, in addition to enabling real-time end-to-end visibility, cognitive capabilities and decision-making autonomous, can also help companies manage atypical situations. risks that alter the world.
USM Business Systems is one of the Best Artificial Intelligence Development Company, human resource management systems, application development, data quality solutions, workforce service to create interactive experiences for all major platforms.
Blog Written By
KoteshwarReddy
I am a Technology Asst. at USM SYSTEMS, I develop software technologies (AI, ML, Mobile App and HRM)
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In the intervening years, this field has evolved and blossomed to cover a variety of activities.It is also growing at a phenomenal pace and in spite of having impacted so many aspects of our daily -lives,we are scarcely aware of its influence.According to Nils Nilsson, a pioneer in the field said, “Artificial intelligence is that activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment.”Based on this perspective and since intelligence encompasses many areas and is multi-dimensional, the differences between AI and a human brain is based on intuitive learning, processing speed, scale, generality and the degree of autonomy.At one point, a calculator was considered as an AI tool, but advances in this field have transformed every aspect of life completely.Some instances of AI are speech recognition software, cruise control in automobiles, the auto-pilot feature in airplanes, smartphones and even thermostats.The impact of artificial intelligence is undeniable and expected to improve continuously and in increments.Lets take a look at the impact of AI in day to day life.
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