Open Data Infrastructure Exit Criteria for AI Platforms

An AI platform exit strategy that only exports files is not an exit strategy.

Exit criteria should test meaning

AI platforms accumulate more than data. They accumulate prompts, context stores, evaluation datasets, policy decisions, lineage, vector indexes, tool contracts, serving traces, and owner workflows. Exporting objects without that meaning leaves the organization technically free and operationally trapped.

Open Data Infrastructure gives leaders a way to define exit criteria before the platform decision becomes irreversible. The question is whether the data and the operating meaning around the data can move.

The exit test needs multiple layers

A useful exit test covers source data, table formats, catalog metadata, semantic contracts, policy rules, lineage, context indexes, evaluation datasets, serving logs, and tool interfaces. It should identify which pieces are open, which are exportable, which are reconstructable, and which are locked inside one platform.

The goal is not to avoid every managed service. The goal is to know which managed service boundaries create irreversible AI dependency.

The ODI pattern changes the buyer conversation

Open Data Infrastructure turns exit from a procurement afterthought into architecture evidence. If metadata, policy, lineage, and evaluations stay portable, the organization can change platforms without relearning what its data means.

For adjacent context, read ODI exit tests for platform mergers, data infrastructure exit strategy, and control planes for AI workloads.

What breaks first

• Data exports work, but policy and lineage exports lose operational detail.
• Vector indexes move, but chunk provenance and freshness do not.
• Evaluation datasets depend on platform-specific traces.
• Tool contracts are documented in application code instead of portable metadata.

Questions to ask

Ask what the platform can export today, what the receiving platform could understand tomorrow, and what evidence would need to be rebuilt manually. Ask whether exit has been tested with a real AI workload, not only a sample file.

Sources to start with

These primary sources anchor the technical claims in this guide.

• Apache Iceberg table specification
• OpenLineage object model documentation
• NIST AI Risk Management Framework
• Model Context Protocol tools specification

Real exit means the next platform can inherit meaning, not just bytes.