One-Quarter of Logistics Firms Projected to Use AI for KPIs by 2028
Gartner predicts that generative AI could be the next frontier for key performance indicators (KPIs) in logistics.
The research firm projects that by 2028, 25 percent of all logistics-focused KPI reporting will rely on generative AI.
More from Sourcing Journal
Carly West, senior director analyst, Gartner Supply Chain, said the research team arrived at that figure by analyzing data on existing usage and aspirations and inferring where leaders may be headed.
“This was based on our research and conversations with both end users and technology vendors. Generative AI is obviously getting a lot of attention right now, [and] AI in general is being prioritized by many leaders,” West told Sourcing Journal. “One of the most obvious use cases for logistics was in KPI reporting. Logistics leaders sit on a ton of data, but aren’t always able to compile, query and report on it easily.”
According to Gartner data, 14 percent of supply chain organizations have already implemented or are working to implement generative AI. An additional 50 percent of leaders indicated they plan to implement the technology within the next year.
KPIs aid logistics providers in tracking targets, efficiency and performance. Having that data can allow leaders to make more informed decisions, but in organizations that track a sprawling variety of metrics, it can prove difficult to parse through the data trove. Gartner suggested that generative AI could help highlight the most important indicators for a business.
West said generative AI-powered systems stand to improve the ease of querying information—especially in terms that make sense to the user.
“For most logistics leaders, this isn’t easily done today without building reporting or leveraging their own data analysts or building something in a visualization tool. [Generative AI] will speed up the KPI reporting process,” she explained.
But in order to see the best outcomes from technology, enterprises need to ensure the data they enter into the systems is the best quality it can be, West warned.
“Data quality is absolutely critical. We’ve heard it a million times before: garbage in, garbage out. Your reporting will only be as good as your data. If you’re measuring [or] reporting on performance and the data being used to measure isn’t accurate, then you break trust and can drive unintended actions with poor outcomes,” she said.
To mitigate data-based issues, West said, supply chain and logistics organizations should consider embedding data governance structures and working on data management and quality strategies.
KPIs may not be the only function of the supply chain altered by emerging technologies. Gartner also predicts that by 2028, there will be more smart robots than frontline workers in manufacturing, retail and logistics.
But the reason may not be aligned with at-large fears over job loss. Gartner said the reason for that prediction is due to labor shortages.
In line with that trend, retention in warehouses and manufacturing facilities has become crucial. Gartner said by 2028, it anticipates 40 percent of all large warehouse operations will deploy tools to engage their employees. That could help motivate the workforce and may, in turn, drive higher retention rates.
As supply chain players continue to evaluate the best use cases for AI in their organizations, they may need to consider whether to build their own models and tools or buy systems operated by a third-party provider.
For many small-to-medium companies, the former could be a major challenge. West said most ordinary companies may want to consider working with providers to streamline the AI implementation process.
“Highly mature organizations might have the technology, the data and the talent to develop and customize gen AI solutions. However, lower-maturity organizations might lack one or more of these requirements and should consider embedded offerings of technology or service providers they work with,” she noted.
