Major logistics providers have long relied on analytics and research
teams to make sense of the data they generate from their operations.
AI’s ability to streamline so many supply chain and logistics functions
is already delivering a competitive advantage for early adopters by
cutting shipping times and costs. A cross-industry study on AI adoption
conducted in early 2017 by McKinsey found that early adopters with a
proactive AI strategy in the transportation and logistics sector enjoyed
profit margins greater than 5%. Meanwhile, respondents in the sector
that had not adopted AI were in the red.
However, these crucial benefits have yet to drive widespread adoption.
Only 21% of the transportation and logistics firms in McKinsey’s survey
had moved beyond the initial testing phase to deploy AI solutions at
scale or in a core part of their business. The challenges to AI adoption
in the field of supply chain and logistics are numerous and require
major capital investments and organizational changes to overcome.
In a new report, BI Intelligence explores the vast impact that AI
techniques like machine learning will have on the supply chain and
We detail the myriad applications for these computational techniques in
the industry, and the adoption of those different applications. We also
share some examples of companies that have demonstrated success with AI
in their supply chain and logistics operations. Lastly, we break down
the many factors that are holding organizations back from implementing
AI projects and gaining the full benefits of this disruptive technology.
The current interest in and early adoption of AI systems is being driven
by several key factors, including increased demands from shippers,
recent technological breakthroughs, and significant investments in data
visibility by the industry's largest players.
AI can deliver enormous benefits to supply chain and logistics
operations, including cost reductions through reduced redundancies and
risk mitigation, improved forecasting, faster deliveries through more
optimized routes, improved customer service, and more.
Legacy players face many substantial obstacles to deploying and reaping
the benefits of AI systems, though, including data accessibility and
AI adoption in the logistics industry is strongly skewed toward the
biggest players, because overcoming these major challenges requires
costly investments in updating IT systems and breaking down data silos,
as well as hiring expensive teams of data scientists.
Although AI implementations are unlikely to result in large-scale
workforce reductions in the near term, companies still need to develop
strategies to address how workers' roles will change as AI systems
automate specific functions.
This exclusive report also:
Details the factors driving adoption of AI systems in the supply chain and logistics field
Examines the benefits that AI can deliver in reducing costs and shipping times for supply chain and logistics operations
Explains the many challenges companies face in implementing AI in their
supply chain and logistics operations to reap the benefits of this
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