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The hidden corners of the supply chain are becoming prime ground for Industrial AI to deliver real-world business value.
The facility yard is often the forgotten part of the supply chain. For decades, it has been a black box: a physical buffer zone managed by spreadsheets, walkie-talkies, and tribal knowledge. This operational blind spot, however, is precisely where some of the most significant and practical gains from Industrial AI are being realized today.
I was pleased to join Tyler Nickel and Kerry Wigginton from FourKites for their recent webinar, "Yards Reimagined: Why Supply Chain Leaders are Investing in AI-Powered Yard Management," to discuss this very transformation. We explored how new AI capabilities are moving beyond the hype to solve long-standing challenges in yard and scheduling operations, unlocking massive efficiencies and cost savings.
From a "Forgotten" Space to a Hub of Intelligence
For years, the yard has remained resistant to technological advancement. As I noted during our discussion, it often lacks the robust sensor data we see in factories or warehouses. However, the proliferation of other data sources, like camera feeds and real-time transportation visibility data, has created the perfect environment for AI to thrive.
Kerry Wigginton of FourKites pointed out that pressures like labor shortages and increasing on-time-in-full (OTIF) fines are forcing companies to finally focus on this area. The consequences of an unmanaged yard are significant: lost trailers, detention fees, and poor inventory velocity.
Putting the Industrial AI Toolbox to Work
A key theme of our conversation was understanding that "AI" is not a monolithic concept. As I frequently emphasize in my research at ARC Advisory Group, the industrial sector was an early adopter of many AI and machine learning techniques long before the recent buzz around Generative AI. In the webinar, I highlighted my "Industrial AI Toolset" framework, which includes established technologies like computer vision and emerging ones like AI agents.
Kerry provided excellent, real-world examples of how these tools are being applied today:
Computer Vision for Gate Automation: One company reduced its average driver check-in time from 15 minutes to just two minutes by using AI to help drive gate automation. This not only improves velocity but also eliminates the cost of manned gates.
Automated Yard Inventory: Using cameras to constantly monitor the location and status of trailers eliminates manual yard checks, saving on labor and fuel.
Agent-Based Workflows: AI agents are being deployed to intelligently automate tasks. For instance, an agent can proactively contact a carrier for an updated ETA if a GPS signal is not working, read the email response, and update the appropriate systems.
The Rise of AI Agents and the Path to Interoperability
These use cases are a perfect illustration of the trend I covered in my recent blog, “AI Agents Take Center Stage”, where I rounded up the many AI Supply Chain Agents announced in 2025, including those from FourKites. We are moving from passive analytics to proactive, automated decision-making orchestrated by intelligent agents.
Looking ahead, it’s collaboration that will unlock the full potential of these agents. During the webinar, I stressed the importance of interoperability and the emerging standards that will enable it. As I detail in my blog series, “The Rise of A2A: Completing the Industrial AI Protocol Stack”, protocols like the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication are foundational. They are creating a future where specialized agents from FourKites, SAP, and others can communicate and coordinate complex, multi-enterprise workflows.
This isn't a far-off vision; the groundwork is being laid now. As I mentioned in the discussion, the recent wave of open-source, multi-vendor support for the A2A protocol is a testament to the industry's commitment to avoiding siloed AI systems.
Key Takeaways
For supply chain leaders evaluating these technologies, our discussion offered several key insights:
The Yard is Ripe for AI: The yard is an underserved area with massive potential for efficiency gains and cost savings. It represents a tangible starting point for applying AI to physical operations.
It’s More than Just GenAI: The full "Industrial AI Toolbox,"—especially computer vision and AI agents—delivers immediate, practical value in the yard.
AI Agents are Delivering ROI Now: Specific use cases like automated gate check-in, inventory management, and detention reduction are providing measurable returns.
Interoperability is the Future: The evolution of standards like MCP and A2A is critical for scaling the use of AI agents across the enterprise. Forward-looking organizations must plan for a future of multi-agent collaboration.
To get a deeper understanding of these use cases and the strategic path for implementing AI in your facilities, I encourage you to watch the full webinar on demand.
Engage with ARC Advisory Group
For ARC Advisory Group recommendations for Navigating the AI Wars, Closing the Digital Divide by Embracing Industrial AI, assembling your Industrial-Grade Data Fabric, the Modern Industrial AI Technology Stack, and governing and guiding major decisions about enterprise, cloud, industrial edge, and AI software, please contact Colin Masson at [email protected] or set up a meeting with me, or my fellow Analysts at ARC Advisory Group.