Artificial intelligence (AI for short) now offers a wide range of possible applications and opens up numerous new opportunities for logistics companies. Nevertheless, it is far from having arrived in the industry.

Current Status of AI in logistics

In a study by EHI Retail Institute GmbH, experts from various logistics disciplines see the most important areas of application for ML in demand forecasting and sales planning, transport optimization (e.g., through autonomous transport systems), and production optimization .
sales planning, transport optimization (e.g. through autonomous transport systems) and production optimization. AI and ML offer the possibility to data streams in one model and thus discover facts and dependencies. (1)

This results in more accurate predictions that form the basis for planning. The McKinsey Global Institute
estimates that, in most use cases, the application of AI in logistics
and SCM will lead to an increase in resource efficiency. With less manpower required, dependencies implicitly present in the data are identified and better decisions can be made. (2)

Greatest opportunities for AI in logistics

Data and algorithms enable forecasts under the influence of a wide range of parameters. But what can AI bring to logistics in concrete terms? According to the survey, logistics companies see the most potential in the following areas: (3)

• Demand forecasting and sales planning (62%).
• Production optimization (51%)
• Transport optimization (50%)

References

(1)  https://www.mckinsey.com/business-functions/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021

(2) https://www.ehi.org/produkt/whitepaper-ki-im-supply-chain-management-des-handels/

(3) https://www.mckinsey.com/business-functions/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021