How Logistics Teams Can Transform the Supply Chain with AI and Machine Learning

Artificial intelligence (AI) and machine learning (ML), for logistics management, promises to free up employees from tedious, repetitive tasks that aren’t leveraging their unique skills—to reclaim time for teams to focus on strategic matters. After all, AI and AL are proven tools that can reduce human error, increase efficiency, and scale operations across industries.

In logistics specifically, automated processes—from procurement and manufacturing to inventory management and warehousing—are transforming the supply chain to provide greater visibility, better forecasting, and more opportunities for savings.

But while the future of logistics is on the cusp of transformation, supply chain leaders are up against tight budgets, overworked and understaffed teams, and unprecedented bottlenecks. As a result, logistics teams will need to find a way to innovate while tackling these day-to-day challenges.

A closer look at AI and machine learning

Gartner’s technology research company predicts that by 2023, intelligent algorithms and AI techniques will be an embedded or augmented component across 25% of all supply chain technology solutions.

For logistics teams, AI and machine learning are increasingly ubiquitous—with the potential to create a more resilient, data-centric, and transparent supply chain that doesn’t rely so heavily on manual processes. That means better data and more visibility into operations increase, and greater accountability and efficiencies are realized. As a result, fewer disruptions and decreased costs are reality versus a vision for the future.

Complete a thorough needs assessment

But, the technology must align with the business strategy. While advanced technologies like artificial intelligence and machine learning have great potential to transform the supply chain, that doesn’t necessarily mean it’s a good idea to adopt them right now.

Logistics teams can take concrete steps to determine whether the technology aligns with the business strategy. Making a thorough assessment of any needs for automation and prioritizing automation initiatives are essential when evaluating new technologies. It’s crucial to resolve these to make the best determinations about alignment with key business drivers.

Current solutions to today’s problems

Many logistics teams don’t have the money, resources, and staff to implement costly, advanced technologies right now. It doesn’t mean that it will never happen—but some options can chart a course for a future that includes AI and machine learning. Still, a culture of innovation must be encouraged. Equally important—determine if there are any roadblocks to innovation. Innovation cannot be stalled.

A partner like CTSI-Global understands that today’s problems urgently need innovation. However, tried-and-tested supply chain technology can still significantly impact your operations—both now and for years to come. It can include tools that improve efficiency and visibility like a transportation management system (TMS) and those that will consistently put money back into the bottom line, like freight audit and payment solutions.

Address today’s problems with tried-and-true logistics technology. Contact us today to get started.