Why AI won't fix Britain's supply chains
Businesses hoping AI will solve their supply chain problems risk wasting their investment unless they first fix weaknesses in their data, skills and management, according to new research published in the Benchmarking: An International Journal.
The notion that artificial intelligence can single-handedly resolve supply chain issues is a tantalizing one, but it's not a magic bullet. The research suggests that companies must first address fundamental weaknesses in their data, skills, and management before AI can be effectively leveraged. This is crucial because AI systems are only as good as the data they're trained on, and if that data is incomplete, inaccurate, or inconsistent, the insights generated will be flawed.
In the context of supply chain management, this is particularly significant. The sector has long struggled with visibility, transparency, and coordination, making it an attractive candidate for AI-powered solutions. However, without a solid foundation in data quality, analytics literacy, and effective management, companies risk investing in AI without reaping tangible benefits. This echoes broader concerns about the responsible adoption of AI, where technological solutions are often outpaced by the need for organizational readiness.
As the logistics and supply chain industry continues to navigate disruptions and uncertainty, it's essential to watch how companies prioritize foundational improvements over quick-fix AI solutions. The next step will be to see whether businesses heed the research's warnings and focus on building a robust data infrastructure, upskilling their workforce, and refining their management practices. Only then can AI be harnessed to drive meaningful efficiencies and innovations in supply chain management.
Originally reported by phys.org. StudentNewsletter adds analysis for science & discovery readers.