Legacy Integration Challenges: Why Workflow Automation Still Matters in an AI World

In an age dominated by AI headlines, logistics and supply chain leaders are still struggling with EDI, XML, and CSV. Here’s why workflow automation is still essential and how it differs from AI.

The Promise of AI vs. the Reality of Supply Chain Tech

Artificial intelligence (AI), especially in the form of agentic systems powered by large language models (LLMs), is generating massive excitement across industries. Autonomous agents promise to reason, adapt, and act on unstructured inputs, transforming workflows and decision-making.

But here’s the reality: most logistics and supply chain systems aren’t ready for AI.

While AI thrives in environments that are flexible, dynamic, and unstructured, the supply chain world still runs on protocols that are decades old, like EDI (Electronic Data Interchange), flat-file CSVs, and verbose XML schemas. These formats don’t “speak AI.” They were built for consistency, reliability, and compliance – not dynamic logic.

Fact Check: According to GS1 and industry research, over 85% of B2B data exchange in supply chains still happens over EDI and similar structured formats.

Splice's workflow platform includes a GenAI agent and above, the agent is used three times in three different ways.

Why Legacy Integration is So Hard

Legacy systems aren't just “old.” They’re rigid. Integrating them with modern platforms often requires:

• Custom-built adapters or middlewares

• Manual file mapping and transformation (CSV to XML, etc.)

• Human-in-the-loop QA for edge cases or failed transactions

• Scraping or RPA (robotic process automation) for systems with no API access

Agentic AI can't easily plug into a system that expects perfectly formatted EDI 856 Advanced Shipping Notices, or FTP-pushed nightly CSVs with specific column headers. These tasks require workflow automation, data normalization, and robust error handling, not generalized reasoning.

Where Workflow Automation Platforms Shine

At Splice, we help businesses automate logistics and supply chain workflows by integrating legacy protocols and modern SaaS tools without the complexity of building from scratch.

Our platform acts like a Zapier for logistics, enabling you to:

• Move data between FTP servers, APIs, and legacy systems

• Transform files from CSV/XML into formats your TMS, ERP, or WMS can understand

• Automate workflows like order processing, shipment tracking, and invoicing

• Add retries, error handling, and human review for failed data flows

This isn’t AI. It’s smarter workflow automation. And it works with the systems you already have.

AI and Workflow Automation Are Complementary – Not Competitors

We’re not anti-AI. In fact, we’re excited about what agentic AI might do for logistics in the future, like proactively resolving shipment exceptions or suggesting routing optimizations.

But until the core systems evolve, workflow automation is the bridge.

• AI needs structured inputs → We help generate them.

• AI doesn’t always know what’s “valid” EDI → We validate and format data correctly.

• AI can’t FTP a file or parse a broken CSV → We can.

As we develop toward more agentic features, our goal is to augment, not replace, your workflows with AI in thoughtful, high-leverage ways.

Final Thoughts: Build the Foundation First

Agentic AI has immense promise. But it’s not a silver bullet, especially for supply chain organizations built on legacy technology stacks. Before you adopt agents, you need automation that understands your current tools, files, and systems.

• Start automating what’s repeatable.

• Then add intelligence when the foundation is solid.