AI Supply Chain Stats

Every industry’s success is impacted by how well its supply chain functions.

AI has various use cases that can help the supply chain industry, streamline processes, reduce supply chain costs, and generally optimize the industry.

Organizations already using AI are 2X faster than their peers, hence AI adoption seems to be important to not fall behind.

Let’s look at how AI is changing how supply chains function, starting with some key stats!

The AI Supply Chain Market Is Expected to Reach $58.55 Billion by 2031

It is expected to grow at a very high CAGR of 40.4% from 2024 to 2031. (Meticulous Research, 2024)

In 2024, the Hardware Segment Is Expected to Account for 44.4% of the AI in Supply Chain Market

The AI in the Supply Chain Market is segmented into 3 sections which are: hardware, software, and services. (Meticulous Research, 2024)

The Software Segment Is Expected to Record the Highest CAGR of 43.2% During the Forecast Period

This is due to the various benefits that supply chain software provides, it can enhance supply chain visibility and aid centralized operations. (Meticulous Research, 2024)

Even in Developing Areas of Sustainability Tracking and Measurement, AI Adoption Is as High as 62%

Standardizing processes and optimizing last-mile delivery are also areas where AI is being adopted. (EY, 2024)

40% of Supply Chain Organizations Are Investing in GenAI

Although Gen AI tools are limited in capabilities by their input data, in this case the data gotten from supply chain partners. (EY, 2024)

87.4% of Leaders Said Being Data-Driven Was the Top Attribute of a Resilient Supply Chain

Data-driven here encompassed visibility, transparency, and traceability as well. (Supply Chain Digital, 2024)

A Mining Company Used AI-Driven Solutions Reducing Production Downtime by Up to 30%

Sandvik Mining and Rock Technology used Artificial Intelligence to predict maintenance needs, which caused the reduction. (IBM, 2020)

82% of Industry Professionals Say Tech Advancements Will Have a Significant Impact in the Next 5 Years

The specific areas are quality assurance, predictive analytics, and operational efficiency, supporting improved decision-making and transparency.

Here are more insights from the report by Inspectorio, that can help companies develop key growth strategies:

Only 24% of Companies Have Integrated AI Into Operations

76% of respondents indicated that AI is not yet integrated into their supply chains.

41% Think That Technology Will Have a Very High Impact on Supply Chains in 5 Years

Around 80% think that tech will have at least a high impact.

20% Reported That Efficiency and Automation Was Their Key Objective for AI Integration

This was tied with data analysis and decision-making at 20% as well.

AI, Automation & Technological Integration Were Seen as the Top Big Opportunities for Innovation

Sustainability and Eco-Innovation came next, followed by Supply Chain Logistics.

Top Supply Chain Organizations Are Using AI to Optimize Processes 2x Faster Than Their Competitors

The survey also revealed that the best supply chain organizations prioritize productivity in their business model instead of efficiency or cost savings. (Gartner, 2024)

AI for Forecasting Can Cut Errors by 30-50% in Supply Chains

According to a survey by McKinsey Digital, AI can mitigate the losses caused by correcting errors in the supply chain.

Lost sales due to sold-out products can be reduced by up to 65%, and 20 -50% inventory reductions are also achievable.

AI Platforms, When Used to Optimize Picking Routes Within Warehouses, Boost Workforce Productivity by About 30%

Optimized picking routes save workers time and ensure smooth supply chain operations and warehouse management.

69% of Executives Opted for AI, Advanced Analytics, and Digital Twins For Their Future Endeavors

65% said advanced planning systems would help them, 56% said ERPs or digital cloud would, and finally, 54% went for intelligent automation. (Supply Chain Digital, 2024)

Demand forecasting is also a key area that supply chain executives can look towards.

Demand Forecasting Leads AI/ML Adoption in High-Performing Supply Chains

According to Gartner, here are the statistics of the percentage of high-performing sectors in terms of using AI:

• Demand forecasting: 40%

• Order management and fulfillment: 33%

• Supply planning: 31%

• Logistics and distribution: 27%

• Sales and operations planning/integrated business planning: 24%

66% of Executives Ranked Operations Process Optimization as One of the Top Areas to Use Generative AI

Here are some other areas that were also flagged as important, according to a KPMG report:

• 47% cited planning/scheduling

• 44% mentioned quality control and inspection

• 43% mentioned inventory management

Supply Chain Organizations With Mature AI Strategies Align With Warren Buffett’s Investment Philosophy

The strategy involved figures what’s most important for the supply chain right now, and then established clear metrics for measuring success. (Zero, 2024)

A further quote from one of the supply chain leaders from this report emphasizes the importance of adopting AI quickly:

“The global supply chains of tomorrow will be AI-empowered and fully digitized from end-to-end — a complete convergence of supply chain and IT that will fundamentally change the nature of supply chain work,” says Kevin O’Marah, co-founder and chief research officer with Zero100.

Challenges of Implementing AI in Logistics

There are quite a few challenges of implementing AI/machine learning in logistics, such as the increased potential of hackers using LLMs to cause disruptions in the supply chain.

Lack of industry specific use-cases of AI was also another limitation that a lot of supply chain professionals mentioned.

AI in other areas like customer service are lacking the ‘human touch’ that customers feel uneasy without.

Let’s look at the stats to see supply chain risks and limitations:

Criminals Have Been Known to Use LLMs such as ChatGPT and WormGPT to Hack Customer Information

As consumers and companies both are at risk of falling for such scams, so is the logistics sector at risk of AI cybercrime. (Statista, 2024)

Novel methods to reduce these supply chain risks will be an important area of research for supply chain risk management.

Lack of Industry-Specific AI Solutions Was Cited by 47% As the Primary Barrier For Not Integrating AI

This points to a gap in the market for industry-specific AI solutions. (Inspectorio, 2024)

There are other areas like customer service, where AI integration is sometimes not favored by customers themselves, as in this Statista survey:

43% of Respondents Said They Weren’t Satisfied When AI Answered Their Queries

Only 25% said that they were happy with the service. (Statista, 2024)

At 22%, Restrictive IT Policies Were Cited As the Second Largest Barrier to AI Adoption

This was out of the 76% of respondents who hadn’t adopted AI into their supply chain program. (Inspectorio, 2024)

40% of Respondents Listed Risk Management and Supply Chain Resilience as Their Primary Concern

Around 37% mentioned regulatory and compliance pressures, and 32% cited budget constraints. (Inspectorio, 2024)

82.8% of Professionals Claimed They Were Either ‘Ready’ or ‘Somewhat Ready’ for the Future

5.7% even said they are ‘leading the way’ towards a better future for the supply chain industry. (Supply Chain Digital, 2024)

Let’s look at some concluding thoughts on the future of AI in the industry.

Final Thoughts: Is AI Here to Stay in the Logistics Industry?

Regarding the future of ai in supply chain, here is what Luis Gonzalez, Becle global supply chain director, informs CGT:

• Every single company needs to react quickly and adapt to the ever-changing world

• Every day there is an increase in the complexity of supply chain procedures

• For companies to survive they will have to automate more processes and have humans supervise the machines