5 Impediments to Successful Artificial Intelligence Implementation in Supply Chains

Artificial intelligence (AI) is set to be pivotal to supply chains going forward, however, there are several obstacles supply chain managers will have to navigate if they’re successfully going to utilize it.

The state of artificial intelligence in supply chains is still something that is very much unfolding. Both AI and supply chains are multifaceted and thus have elements where they work well together and elements where they don’t. For example, a subset of AI like machine learning has become a prominent feature in forecasting. However, AI being used for self-driving trucks is still years away. Regardless, AI is undoubtedly deeply intertwined with supply chains. It has to be carefully integrated into them in order to work well.

This week’s article by Morai Logistics explores 5 barriers that supply chains face when attempting to make us of artificial intelligence.

Lack of Data

AI only works optimally if it has access to large amounts of accurate data. If there isn’t enough data or the data is of a low quality, the results it produces will suffer. Take machine learning for instance, in order to make predictions or employ its algorithms, a computing system needs enough clean data to pull from for its predictions to be accurate. Simply put, not having a large pool of consolidated up to date data for an AI is like having a sports car without any fuel.

Segmented Artificial Intelligence

Supply chain managers know that one part of their job is to keep an eye on the big picture. Supply chains may be broken up into many individual processes and procedures, but they come together to make the chain. As such, it’s critical that AI implementation be holistic. Much in the same way AI needs access to data that is clean and plentiful, it also has to have access to data that is uninterrupted. If an AI only has data split into disparate segments of a supply chain to work with, then it will produce commensurately uneven results.

Lack of AI Knowledge in the Workforce

Artificial intelligence is conceptually new. It’s also confusing for many. When introduced into a supply chain, supply chain managers may find that many along their chain having trouble adapting to its functions. This is entirely understandable given the often complex and changing nature of AI. With that being the case, supply chain leaders should be providing training for their workforce. Or, conversely, they can hire new personnel to make up for this knowledge gap.

Poor Understanding of AI Processes

Understanding how to use AI and what it’s there for is different from understanding what it’s specifically doing to produce its results. This leads to the “black box” problem—that being the results themselves being mysterious. If there isn’t a transparent AI operation in place, it will likely produce inexplicable results. These results then have to be accepted on faith.

As an article in Forbes highlighted earlier this year,

Black box solutions are controversial. With a black box solution, planners cannot see into the machine and understand how the forecasting engine is generating the forecast. They must trust the output. AI solutions are more likely to be black box than traditional solutions.

Measuring Success

The metrics used to gage success within a supply chain that adopts AI will change. AI transforms many functions in a supply chain. As a result, the indicators of success need to be adapted to these new supply chain realities. Moreover, the nature of AI and what it can do is in a state of continual development. Meaning measuring how successful it is can require continual adjustments of success markers with each development.

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Experts say that supply chain management is one of the top industries that will benefit from the adoption of artificial intelligence (AI) this year.

In February, Morai Logistics discussed the positive impact Artificial Intelligence is forecasted to have on our industry. From robotics and machine learning to delivery optimization to maintenance consistency, the possibilities are endless.

According to Statista, in 2025 the global AI market is expected to generate approximately 89, 847.26 billion U.S dollars. This technology has gained considerable global interest for the heightened efficiency, productivity and innovation it provides many industries. The AI market is also forecasted to contribute ‘$15.7 trillion to the global economy’ by 2030.

There is no denying the positive impact Artificial Intelligence will have on industries that help propel our world forward. Supply chain management is considered one of the top three industries to benefit from the advancements of AI technology. From the manufacturing floor, to inventory and logistics, AI is a catalyst for efficiency, agility and accuracy.

In part two of Artificial Intellignece, Morai Logistics discusses the current impact of AI in the supply chain industry in 2019. It also outlines the valued benefits of integrating AI technology into supply chain management.

Artificial Intelligence at a Glance

To understand the global impact of AI, Microsoft commissioned a survey that included 400 senior executives working within eight various markets. Their findings indicated that 94% of executives ‘describe AI as important to solving their organizations strategic challenges’. Digital maturity has been a slow and progressive movement across a variety of industries. However, more than 27% of executives stated they have already incorporated AI into their organizations.

From a supply chain standpoint, a recent study by global research leader, McKinsey, found adoption to be significantly high. Their global survey indicated that 76% of supply chain respondents found ‘moderate to significant value from deploying AI’. Their research indicated that supply chain management is one of the top three industries to benefit from this technology. Thus, confirming that this technology has made its way into the industry, with positive feedback from top level professionals.

Benefits of AI in Supply Chains

Before we outline the extended benefits of AI in supply chains, it’s important to first recognize the challenges with implementation. If the process of integration of technologies was simple, many industries would be at the higher end of the spectrum of digital maturity. Forbes indicates that the most significant challenge is acquiring the right talent pool. However, they also followed with optimism that many organizations place importance on ‘building in-house AI capabilities’. Therefore, as supply chains evolves, employees are also encouraged to develop their skills.

In February, Morai Logistics looked at robotics and machine learning, delivery optimization and maintenance consistency. According to Microsoft,

There is tremendous opportunity for AI to augment human abilities across industries while capitalizing on unique human capacities for creativity and agility – human characteristics that are difficult for computers to mimic.

This supports the fundamental reality that AI heightens employee performance, as AI technologies enable them to focus on their core skills. Furthermore, research has also found positive results from the integration of predictive capabilities. The reality is that AI continues to evolve and learn which also enables supply chains to learn and adapt to change. This is especially helpful when developing processes that enable ‘demand forecasting and capacity planning’.

Big Data is also an incredible tool that helps technologies such as AI advance. Research indicates that 81% of shippers and 86% of third-party logistics (3PLs) providers believe in using Big Data. In fact, they believe that ‘using Big Data effectively will become “a core competency of their supply chain organizations.

AI will cause considerable change and provide opportunities to the supply chain and logistics industry in the upcoming years. As organizations continue to diversify their labour force and integrate and develop various tools using AI, supply chains will see positive growth.

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This year, artificial intelligence (AI) remains one of the top advancements in supply chains and an integral solution toward improving efficiency.

Artificial intelligence generated major buzz as a revolutionary technology for supply chains in 2018. Early last year, Morai Logistics discussed how AI improved transparency with customers, in addition to optimizing transport management systems. In fact, the success of the market in 2018 generated ‘USD 730.6 billion’.

The latest forecast on Artificial Intelligence in supply chain indicates that by 2025 this figure is ‘expected to reach ‘USD 10,110.2 million’. This increase is based on a compound annual growth rate (CAGR) of 45.55%.

These findings indicate a significant global investment into AI technology, in addition to a lucrative future from integrating AI into supply chains. In addition, research on AI adoption found that,

By 2023, at least 50% of large global companies will be using AI, advanced analytics and IoT in supply chain operations.

Gartner, a leading global research and advisory firm, believes that over the next four years, the presence of AI in warehouses will also increase. In fact, by 2023 collaborative robotics will supplement ‘over 30% of operational warehouse workers’.

The goal of integrating AI into supply chains is to support high demand with greater visibility and efficiency. Experts also link the integration of AI enhanced technologies, such as the Internet of Things (IoT), with ‘revenue increase or cost savings’. Let’s take a deeper look at the top ways this technology will impact the industry this year.

Robotics & Machine Learning

Robotics will play a significant role in improving warehouse performance. There has been skepticism in the past that advanced robotics will replace human labour, however, this is not the case. On the contrary, robots and workers will work in a collaborative working environment.

Research indicates that these ‘intelligent and aware’ machines are best suited for ‘complex motor control’. Furthermore, to enable workers to focus on their strengths and core responsibilities, robotics can independently help move goods around.

Maintenance Consistency

The connection between AI and efficiency is also shown through the use of data automation. Experts on the integration of AI into supply chains believe that by implementing this technology into equipment, a company will save. According to SupplyChain247,

Artificial intelligence collects information from sensors on equipment, which combines with maintenance records.

This efficient, streamlined process will ensure transparency on maintenance and improved productivity is achieved. For instance, extended research found that integrating AI could improve ‘productivity by 20% and cut maintenance costs by 10%’.

Delivery Optimization

The advanced learning of AI also provides the added benefit of improving efficiencies throughout the shipment life cycle. This includes Omni-channel modes of transport such as tracks, rail, ocean and air. In the fall of 2018, Forbes spoke to the integration of ORION, an ‘AI-powered GPS tool’ that UPS had adopted. This technology removed barriers caused by traffic and back-tracking, by collecting and transmitting data by customers, drivers and vehicles. The insight generated from this data would be utilized to pin point ‘the most optimal routes’. This is a great example of how AI can contribute to improving efficiencies while also improving cost-savings across the organization.

Based on the above findings, Artificial Intelligence (AI) will equip supply chains with the support and optimized solutions they require to improve efficiencies. From warehouse and robotics, to improving maintenance consistency and delivery optimization, AI will continue to drive the market forward.