AI is coming for logistics 🌀
AI is coming for logistics 🌀
Can AI transforms supply chains? Demand forecasting, warehouse automation, quality control, procurement, customer service, transportation, reducing costs, and boosting efficiency.
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The adoption of artificial intelligence (AI) is transforming industries across the board. Among these industries, supply chains and logistics have embraced AI technologies due to their immense potential for revolutionising operations.
Transforming supply chains with Artificial Intelligence
Statistics
A 2021 report by Gartner, a prominent research and data insights firm, projected a significant trend: 50% of supply chain organisations are expected to invest in AI and analytics applications through the year 2024.
Emergence of AI in supply chains
COVID-19 pandemic fast tracked the adoption of AI. The need for AI in supply chains became particularly apparent in 2020.
This global health crisis created unprecedented challenges for supply chain organisations worldwide.
Economic disruptions, manufacturing halts, and unpredictable consumer behaviour exposed vulnerabilities in traditional supply chain management models.
Supply chain operators found themselves grappling with levels of uncertainty and complexity that their existing methods could not effectively address.
AI's role in demand forecasting
One of the key areas where AI has made a significant impact in supply chains is demand forecasting.
Accurate demand forecasting is essential for maintaining a delicate balance between consumer demand and supply, ensuring that products reach customers on time.
AI excels in demand forecasting by leveraging vast datasets.
It utilises advanced data science models, such as artificial neural networks, to extract insights from sources like past sales records, customer transactions, social media mentions, and economic indicators.
AI-driven demand forecasting minimises stockouts, optimises inventory levels, and reduces excess inventory, which translates to improved inventory management, significant cost savings, and higher customer satisfaction.
AI in warehouse automation
Warehouse operations have also seen substantial improvements through the implementation of AI.
Autonomous mobile robots (AMRs) powered by AI are increasingly being deployed in supply chain warehouses globally.
These robots can perform a range of tasks, including picking, packing, and replenishing, with a high degree of autonomy.
The magic behind AMRs lies in their integration of AI and advanced technologies like machine learning, computer vision, and sensor fusion.
This sophisticated combination allows them to execute intricate tasks effectively.
Moreover, AMRs are adaptable and can adjust to changing warehouse configurations and operational demands.
In environments where AI robots work alongside human workers collaboratively, they complement each other's strengths.
Human workers can focus on tasks that require creativity and problem-solving skills, while robots handle repetitive and mundane tasks.
This dynamic partnership between humans and AI-powered robots not only maximises workforce productivity but also enhances the overall efficiency of warehouse operations in the supply chain and logistics sectors.
AI for quality control
Quality control is another critical aspect of supply chains that AI is revolutionising.
AI-enabled sensors and analytics tools are now capable of monitoring product quality and detecting defects in real time, ensuring that products meet the highest standards before they reach customers.
These sensors can identify imperfections such as scratches, cracks, and dents in products, as well as incorrect markings or missing components.
In addition to this, some predictive maintenance AI models are employed to evaluate product usage patterns and recommend maintenance schedules based on usage trends.
In the transportation sector, AI-enabled sensors can monitor the condition of products during transit.
For example, AI incorporated into Internet-of-Things (IoT) sensors can detect changes in temperature and humidity, ensuring that perishable goods are maintained at the correct conditions throughout the journey.
By integrating AI-enabled sensors throughout supply chain and logistics processes, businesses can guarantee that only high-quality products reach their customers.
This not only leads to enhanced customer satisfaction but also safeguards the reputation of brands.
Streamlining procurement with AI
Procurement processes, often laden with tedious tasks, are ripe for transformation through AI.
For instance, AI can automate invoice processing by assisting companies in validating invoice data.
Beyond this, it can also notify supply managers about pending invoices, ensuring that they are processed in a timely manner.
Such automation results in a significant reduction in time and effort expended on these tasks.
AI's capabilities in procurement extend further to analysing historical data and identifying patterns and trends.
This analytical prowess can be instrumental in spotting potential risks and issues in procurement processes, such as supplier performance problems or compliance violations.
Detecting these issues proactively can avert problematic situations and contribute to process optimisation.
Innovations in this space even include the combination of AI and blockchain technology to create more secure and transparent distributed database procurement systems.
AI applications for a better customer experience
AI has the potential to revolutionise customer service in supply chain and logistics in various ways.
Real-time order tracking is one such capability that benefits customers by providing them with visibility into the status and location of their shipments.
This level of transparency enhances customer confidence and satisfaction.
Natural language processing (NLP)-based AI solutions can automate customer service tasks, reducing the workload on human representatives.
For example, AI can be deployed to answer frequently asked questions (FAQs), freeing up human agents to focus on more complex tasks that require human input or expertise.
These capabilities not only improve response times to customer inquiries but also contribute to overall customer contentment.
AI in transportation management and route optimisation
AI's influence extends to transportation management and route optimisation within the supply chain and logistics domain.
AI solutions analyse data to identify patterns and determine convenient transport routes.
They utilise real-time information such as current traffic conditions and weather forecasts to identify the most efficient routes for deliveries.
This AI-driven approach helps mitigate inconveniences caused by factors like traffic congestion, particularly during peak traffic times, ultimately reducing delivery times.
Industry experts predict that the use of autonomous trucks relying on AI technology is on the horizon.
Several factors contribute to this transformation, including the rapid advancement of autonomous vehicle technology, increased demand for freight transportation, and a shortage of skilled truck drivers.
However, the widespread adoption of autonomous trucks will depend on meeting stringent safety standards.
The future of AI in supply chains and logistics
The future of AI in supply chains and logistics holds immense promise. AI has the potential to revolutionise these sectors by enhancing efficiency and reducing operational costs.
AI is expected to drastically alter the way items are distributed, handled, and transported in the future.
Automation, predictive analytics, and other AI-based technologies are poised to optimise numerous supply chain-related processes.
These developments may lead to improved demand forecasting, real-time shipment tracking, vehicle route optimisation, and enhanced inventory management.
Moreover, AI can significantly lower operating expenses, identify inefficiencies, and improve overall customer responsiveness.
The integration of AI into supply chain and logistics operations promises to boost efficiency, reduce waste, and enable businesses to adapt to the evolving demands of the modern market.
TTD Week That Was 📆
The week SBF went to trial and crypto price on disco tunes.
Saturday: The SBF trial update👩🏻⚖️
Friday: Where are they? 🔎
Thursday: LATAM loves crypto? 🩵
Wednesday: SEC loses again 👀
Tuesday: The big SBF trial👩🏻⚖️
Monday: Ethereum's mood swings 💹
TTD Week in Funding 💰
Blackbird Labs. $24 million. App and loyalty program to connect restaurants and their customers via its crypto-powered app.
Cicada. $9.7 million. a non-custodial credit risk management company.
Phaver. $7 million. he gateway to Web3 social with support for decentralised social graphs
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