The world of supply chain technology is at a critical moment. For the past five years, the industry has been focused on moving to the cloud and leveraging machine learning to optimize everything from warehouse operations to rate shopping. But the next wave of innovation isn't just a continuation of this trend — it's a fundamental shift toward AI-native workflows and autonomous agents that will redefine how outbound shipping works.
Last week, we hosted a LinkedIn Live to discuss this evolution and explore what the future holds for supply chain technology.
The COVID-19 pandemic accelerated a major transformation in supply chain technology. We moved from a pre-cloud era to one where cloud-based models became the norm, bringing three key benefits:
Let’s take rate shopping as an example. The use of ML allows shippers to go beyond simple rate checks and factor in variables like time-in-transit confidence (vs. static transit times), allowing them to make smarter, data-driven decisions. This ML-optimized workflow allows for both greater delivery accuracy and the increased use of ground methods.
After a period of healthy skepticism fueled by past over-hyped technologies, AI has reached an undeniable inflection point. The technology is no longer just a buzzword; it's a fundamental shift in how work gets done. If anything, we are currently "under-hyping" its potential.
This isn't just about using AI as a tool; it’s about becoming AI-native. Shipium is undergoing this transformation, fundamentally changing our internal and customer-facing workflows to be built on AI principles.
The first step in this AI-native future is the creation of small, impactful tools that provide significant productivity gains. For example, something we’re exploring is a feature that explains "What happened with my shipment?" Instead of a user submitting a support ticket and waiting hours or days for someone to investigate why a specific shipping method was chosen, an AI-powered tool can provide an instant explanation. This reduces friction and allows operations teams to focus on more strategic work.
The ultimate vision is a world where logistics are managed by autonomous agents. During my time at Amazon, I often wished for a "little red button" that could handle necessary changes on a daily basis — for example, automatically reroute orders from a fulfillment center experiencing issues.
An AI-powered agent could make this a reality. Instead of relying on a human to monitor multiple data sources and manually trigger a reroute, an agent could:
This shift from human-driven, reactive responses to always-on, proactive agents will allow companies to manage the chaos of supply chain networks with unprecedented control and efficiency.
Large Language Models (LLMs) are the building blocks of this new world. They power everything from simple chatbots that explain why a shipment was routed a certain way to the complex, multi-modal data processing required for autonomous agents.
The core idea is that AI allows us to move beyond the "transactional" mindset of the past. For instance, rate shopping is no longer a one-time event; it's a part of an interconnected process of decision-making. AI can glue together existing optimization techniques, allowing for flexible rules and custom workflows that help shippers make the right decisions throughout the fulfillment process.
We think that by 2028, a Chief Supply Chain Officer won't just have a team of analysts; they'll have a fleet of autonomous agents helping them run the business..
The transition to AI-native workflows will not just be an incremental improvement; it’ll represent a complete transformation of how supply chain technology is built and used.
As a result, supply chain leaders and operators will have the ability to focus most of their time and energy on strategic problems and initiatives, rather than manually putting out fires.
If you’re interested in learning more about this topic, you can watch the webinar here.