在世界范围内，人工智能正在使供应链更快，更可靠，利润更高。 (Around the world, AI is making supply chains faster, more reliable and more profitable.)

Artificial intelligence is one of the most promising technologies available to businesses today. A McKinsey study of more than 2,000 participants found that 58% of respondents use AI in at least one process. This impressive adoption rate isn’t baseless, either, as AI can improve areas like supply chain management in several ways.

人工智能是当今企业可用的最有前途的技术之一。 麦肯锡对2,000多名参与者的一项研究发现， 58％的受访者至少在一个过程中使用了AI 。 令人印象深刻的采用率也不是没有根据的，因为AI可以通过多种方式改善供应链管理等领域。

Logistics is a fast-moving and essential industry, one that many other sectors rely on to function. As such, it stands to benefit from thorough and timely data analytics. AI makes this possible.

物流业是一个快速发展且必不可少的行业，许多其他行业都依赖该行业来运作。 因此，它将受益于全面，及时的数据分析。 AI使这成为可能。

Some AI technologies have already seen widespread adoption in logistics, while some are just now emerging. Here are 10 ways AI is and can improve the supply chain.

一些人工智能技术已经在物流中得到广泛采用，而有些则刚刚出现。 这是AI可以改善供应链的10种方式。

1.更快的数据分析 (1. Faster Data Analysis)

Data analytics are essential to the modern supply chain. Logistics companies need to analyze vast amounts of information to find inefficiencies and potential ways to improve. This process doesn’t require AI, but it does it much faster.

数据分析对于现代供应链至关重要。 物流公司需要分析大量信息以发现效率低下和潜在的改进方法。 此过程不需要AI，但可以更快地完成。

Combing through information manually to make insightful connections can take a lot of time. In a business as time-sensitive as logistics, that can be a problem. Since AI systems can analyze multiple data sets at once, they can give supply chains results in a fraction of the time.

手动检查信息以建立有见地的联系可能需要很多时间。 在像物流这样对时间敏感的企业中，这可能是个问题。 由于AI系统可以一次分析多个数据集，因此它们可以在短时间内提供供应链结果。

2.预测需求 (2. Forecasting Demand)

Managing inventory is often not as straightforward as you might think. If a warehouse incorrectly estimates future demand, it could end up with too little or too much of a product. Either case could represent a substantial monetary loss, but AI provides a solution.

管理库存通常并不像您想象的那样简单。 如果仓库错误地估计了未来需求，那么最终可能会导致产品太少或太多。 两种情况都可能造成巨大的金钱损失，但AI提供了解决方案。

Through predictive analytics, AI systems can use past trends and market signals to forecast demand. Warehouse managers can use them to see what they need to store more or less of. They could then avoid surplus and deficit, maintaining a consistently prepared operation.

通过预测分析，人工智能系统可以使用过去的趋势和市场信号来预测需求。 仓库经理可以使用它们来查看存储或多或少需要存储的内容。 这样，他们就可以避免盈余和赤字，保持一贯的准备工作。

Amazon uses AI at nearly every level of its supply chain, but especially in the warehouse. Its AI predictions about customer demands are part of how it manages to stay on top of the e-commerce industry. It helps it fill orders faster than most, if not all, of its competitors.

亚马逊几乎在其供应链的每个层次上都使用AI ，尤其是在仓库中。 其关于客户需求的AI预测是其如何保持领先于电子商务行业的一部分。 它帮助它比大多数(如果不是全部)竞争对手更快地完成订单。

3.过程自动化 (3. Process Automation)

Amazon uses AI at nearly every level of its supply chain, but especially in the warehouse. Its AI predictions about customer demands are part of how it manages to stay on top of the e-commerce industry. It helps it fill orders faster than most, if not all, of its competitors.

亚马逊几乎在其供应链的每个层次上都使用AI ，尤其是在仓库中。 其关于客户需求的AI预测是其如何保持领先于电子商务行业的一部分。 它帮助它比大多数(如果不是全部)竞争对手更快地完成订单。

Generally speaking, AI systems are often better at data-heavy, monotonous work than humans. Assigning such tasks to AI doesn’t just save time, but it also saves money. When AI take care of these administrative jobs, it frees human employees to work on other projects at the same time.

一般而言，人工智能系统通常比人类更擅长数据繁重的单调工作。 将此类任务分配给AI不仅可以节省时间，还可以节省金钱。 当AI负责这些管理工作时，它将使人类员工解放出来同时从事其他项目。

Tasks like filing paperwork manually can cost businesses 6,500 hours a year, a substantial time loss. Imagine everything a company could accomplish with more than 6,000 additional hours to work. This productivity advantage is too beneficial for logistics businesses to ignore.

诸如手动提交文书工作之类的任务每年可能使企业花费6,500个小时 ，这是大量的时间损失。 想象一下，公司可以多花6,000多个小时才能完成的所有工作。 这种生产力优势对于物流企业来说实在是太有利了，不容忽视。

4.更可靠的发货更新 (4. More Reliable Shipment Updates)

Many companies use technologies like RFID tags to track products through the supply chain. Sometimes, though, items ship without these tags or events cause them to be unreadable. By using AI, businesses can still offer shipment updates to customers.

许多公司使用RFID标签等技术来跟踪整个供应链中的产品。 但是，有时候，发货时没有这些标签或事件会使它们变得不可读。 通过使用AI，企业仍然可以向客户提供货件更新。

When tracking technology fails, AI can calculate delivery so companies can still provide an estimate. These programs can analyze things like average shipment times and weather patterns to offer accurate results. Supply chains can then understand their progress and maintain customer satisfaction.

当跟踪技术失败时，AI可以计算交付量，因此公司仍可以提供估算值。 这些程序可以分析平均发货时间和天气模式等信息，以提供准确的结果。 供应链然后可以了解其进度并保持客户满意度。

5.自动化仓库管理 (5. Automated Warehouse Management)

Countless other factors affect how efficiently the supply chain runs, but a poorly managed warehouse hinders success from the beginning. Despite this urgency, only 20–30% of warehouses are running as effectively as they can. Using AI to manage operations can help.

无数其他因素影响着供应链的运行效率，但是仓库管理不善从一开始就阻碍了成功。 尽管有这样的紧迫性，但只有20％到30％的仓库正在尽可能有效地运行。 使用AI管理操作会有所帮助。

Automated warehouse management systems (WMSs) can find inefficiencies through data analytics. Since AI is often better at making insightful connections between data points, this can eliminate human errors in management. Small changes across the board can lead to a substantial increase in efficiency.

自动化仓库管理系统(WMS)可以通过数据分析发现效率低下的问题。 由于AI通常更擅长在数据点之间建立有见地的联系，因此可以消除管理中的人为错误。 全面的细微变化可以大大提高效率。

6.优化路线规划 (6. Optimized Route Planning)

Supply chains need to make the most of their shipping to deliver products on time. Often, this means planning the fastest, safest way to get from point A to point B. In yet another application of predictive analytics, AI is ideal for this job, too.

供应链需要充分利用其运输来按时交付产品。 通常，这意味着计划从A点到B点的最快，最安全的方法。在预测分析的另一种应用中，AI也是这项工作的理想选择。

AI systems can look at traffic patterns and weather to determine what the best course of action is. Since factors like this are dynamic, the optimal route may change from day to day. As a result, supply chains need tools like AI that can analyze data and plan routes quickly.

人工智能系统可以查看交通模式和天气，确定最佳行动方案。 由于此类因素是动态的，因此最佳路线可能每天都在变化。 结果，供应链需要诸如AI之类的工具，这些工具可以快速分析数据并规划路线。

UPS has used a system called ORION to optimize its routes since 2012. Since then, this AI has saved the company 100 million miles and 10 million gallons of fuel per year.

自2012年以来，UPS已使用名为ORION的系统优化其路线。此后，该AI每年为公司节省了1亿英里和1000万加仑的燃油。

7.监控产品质量 (7. Monitoring Product Quality)

UPS has used a system called ORION to optimize its routes since 2012. Since then, this AI has saved the company 100 million miles and 10 million gallons of fuel per year.

自2012年以来，UPS已使用名为ORION的系统优化其路线。此后，该AI每年为公司节省了1亿英里和1000万加仑的燃油。

Supply chain management isn’t just about ensuring products arrive on time. Logistics companies also need to ensure that goods arrive undamaged and unspoiled, which can be challenging with some items. AI can determine the lifespan and risk factors for sensitive products, helping businesses ensure their quality.

供应链管理不仅仅是确保产品按时到达。 物流公司还需要确保货物完好无损地送达，这对于某些物品而言可能具有挑战性。 人工智能可以确定敏感产品的寿命和风险因素，从而帮助企业确保其质量。

If there are any unforeseen delays, AI systems can determine if they need to readjust routes to protect some products. If a shipment contains food or plants, they may need to change their path to deliver those first. Without AI, companies may not know to make these changes on the fly.

如果有任何不可预见的延迟，人工智能系统可以确定是否需要重新调整路线以保护某些产品。 如果货物中包含食物或植物，则他们可能需要更改其路径以首先运送那些食物或植物。 如果没有人工智能，公司可能不知道即时进行这些更改。

8.明智的供应商选择 (8. Informed Supplier Selection)

Selecting the right product supplier can be a gamble for some supply chain managers. If they can’t deliver consistent quality or are prone to scandal and ethical issues, it could harm logistics companies’ public image. With the help of AI, though, they can get a better understanding of each business’s history and potential risks.

对于某些供应链经理来说，选择合适的产品供应商可能是一场赌博。 如果他们不能提供一致的质量或容易发生丑闻和道德问题，则可能损害物流公司的公众形象。 但是，借助AI，他们可以更好地了解每个企业的历史和潜在风险。

AI systems can determine if going into business with a company would be a financial or PR risk. Supply chains can then make informed decisions about supplier selection.

人工智能系统可以确定与公司开展业务是否存在财务或公关风险。 然后，供应链可以做出有关供应商选择的明智决定。

9.改进的客户支持 (9. Improved Customer Support)

One of AI’s most common applications is in chatbots, most often in customer support roles. Roughly 40% of American consumers have engaged with a chatbot in the past year. They enable supply chains can provide customer support around the clock.

AI最常见的应用程序之一是聊天机器人，通常是客户支持角色。 在过去的一年中，大约40％的美国消费者使用了聊天机器人。 它们使供应链可以全天候为客户提供支持。

By handling customer engagement with AI, logistics companies free their human employees to focus on other tasks. Not only does customer support improve, but so does overall efficiency. These AI make information more readily available to customers, too.

通过处理与AI的客户互动，物流公司可以解放其员工，使其专注于其他任务。 客户支持不仅得到改善，而且整体效率也得到改善。 这些AI也使信息更易于客户使用。

DHL allows customers to check their order status with Alexa, giving them quick, reliable answers. On top of being a fast, hands-free gateway to information, smart speakers are already present in many homes. People used to using these technologies will appreciate being able to learn about their orders through them.

DHL允许客户使用Alexa检查其订单状态 ，从而为他们提供快速，可靠的答案。 除了作为快速，免提的信息网关外，智能扬声器已经在许多家庭中出现。 习惯使用这些技术的人们将很高兴能够通过这些技术了解他们的订单。

10.自主运输 (10. Autonomous Shipping)

These AI make information more readily available to customers, too.

这些AI也使信息更易于客户使用。

DHL allows customers to check their order status with Alexa, giving them quick, reliable answers. On top of being a fast, hands-free gateway to information, smart speakers are already present in many homes. People used to using these technologies will appreciate being able to learn about their orders through them.

DHL允许客户使用Alexa检查其订单状态 ，从而为他们提供快速，可靠的答案。 除了作为快速，免提的信息网关外，智能扬声器已经在许多家庭中出现。 习惯于使用这些技术的人们将很高兴能够通过这些技术了解他们的订单。

As AI technology improves, it will eventually enable fully autonomous shipping. AI is the key to self-driving vehicles, and driverless delivery would improve shipping times. Self-driving trucks don’t need to stop to rest, so they can drive longer stretches in less time.

随着AI技术的改进，它将最终实现完全自主的运输。 人工智能是自动驾驶汽车的关键，无人驾驶交付将缩短运输时间。 自动驾驶卡车不需要停下来休息，因此可以在更短的时间内驾驶更长的路段。

This technology isn’t available yet, but researchers are getting closer. It will improve with further AI adoption, leading to faster development and implementation.

这项技术尚不可用，但研究人员正在接近。 随着AI的进一步采用，它将得到改善，从而加快了开发和实施的速度。

Fully autonomous shipping may not be a reality right now, but several companies are working on it. In 2017, Rolls-Royce partnered with Google to develop self-driving cargo ships. While the technology isn’t available yet, it will improve with further AI adoption, leading to faster development and implementation.

目前，完全自动化的运输可能不是现实，但有多家公司正在为此进行努力。 2017年， 劳斯莱斯与Google合作开发了自动驾驶货船。 尽管该技术尚不可用，但随着AI的进一步采用，它将得到改善，从而加快了开发和实施的速度。

数据驱动的物流链 (The Data-Driven Logistics Chain)

Data-centric supply chain management is essential to improving the logistics industry. AI comes hand-in-hand with that, as it allows companies to use data to its full potential. As AI sees wider adoption in this sector, the industry will continue to improve.

以数据为中心的供应链管理对于改善物流业至关重要。 人工智能与此并驾齐驱，因为它允许公司充分利用数据。 随着人工智能在该领域的广泛采用，该行业将继续发展。

The supply chain is the backbone of many industries. When logistics companies adopt AI, it creates a ripple effect of benefits and improves the sector’s function.

供应链是许多行业的骨干。 物流公司采用AI时，会产生收益的连锁React，并改善该部门的功能。