Is it helpful or can it go?
The Aachen Institute for Operations, Research and Management INFORM has investigated the extent to which generative AI is already being implemented in logistics – and why it sometimes fails.
16 Jan 2025Share
Generative AI – a subfield of artificial intelligence (AI) that is capable of generating new content from existing data – has so far only been used to a limited extent in the logistics sector: according to a recent study by Aachen-based optimization specialist INFORM, only 16 percent of the 130 specialists and managers surveyed use generative AI in their logistics processes. Nevertheless, 39 percent of those surveyed are convinced that generative AI will change logistics in the long term, while 34 percent consider it to be an important innovation topic.
There is a great deal of interest in generative AI
The study, conducted by INFORM in the summer of 2020, surveyed a total of 130 employees and managers from the logistics and supply chain management sectors of companies in a range of different industries. An initial assessment of the participants shows that there is a great deal of interest in generative AI. Almost half of the respondents (48 percent) say that the technology piques their interest, despite possible risks. 23 percent of the participants are curious but do not want to make a final assessment yet and are waiting for further developments. 18 percent, on the other hand, are enthusiastic about the possibilities of generative AI and see considerable potential in it.
Implementation status varies
Although there is a high level of interest in generative AI, only 16 percent of the companies surveyed already use it in their logistics processes. The main ways in which companies use generative AI are in data analysis (57 percent), followed by process automation (43 percent) and as personal assistants for employees (33 percent). The state of implementation varies: 43 percent of participants are currently in the implementation phase, in which the first projects have been implemented and processes adapted. 24 percent are still in the exploratory phase with no concrete plans, while 19 percent are already in the optimization phase, refining and scaling their AI applications. The main drivers for adoption for most companies are increasing the efficiency of systems, processes and operations (86 percent), reducing operating costs (71 percent) and increasing revenue and profitability (29 percent).
Where there is a lack of action in some cases
Among the companies surveyed that do not yet use generative AI, there are different views on the need for action. While 35 percent are currently examining the possibilities and planning implementation in the medium term, almost as many (31 percent) currently see little need and only limited application possibilities for their company. 22 percent even state that no resources or priorities are currently available for implementation. This could possibly be due to the many obstacles that still stand in the way of companies: in particular, integration into existing systems and insufficient data quality pose major challenges for 38 percent of respondents, followed by data protection and security concerns (35 percent) and a lack of time for extensive implementation projects (33 percent).
Data quality as a success factor for AI integration
Finally, the participants were asked to identify and prioritize the three most important factors for the successful introduction, continuous use and widespread adoption of AI within their organization. Even though the participants' assessments vary greatly in some cases, the majority of respondents consider high-quality, reliable data to be the decisive element in first place. The following places are occupied by acceptance by managers, who are considered the second most important criterion, and acceptance by employees, who are considered the third most important criterion.
Potential of generative AI for logistics
“It is perfectly understandable that new technologies and the changes they bring about should initially evoke respect and even caution,” says Ulf König, Head of Business Development at INFORM and spokesperson for the study, in his assessment of the results. ”The fact that it is not yet widely used does not necessarily mean that generative AI is just a passing fad. Rather, it could indicate that more time is needed to fully integrate and scale the technology. There are already many interesting use cases, especially in the area of intelligent process optimization. It is therefore worthwhile to exploit the potential of generative AI for logistics and to position oneself a bit more flexibly for the future.”
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