AI Is Creating a New Interoperability Challenge for Mid-Size Businesses

Elizabeth
Jun 19
2 min read

Interoperability and harmonization have been priorities for governments, regulators, and standards organizations for decades. The principle is simple: systems create more value when they can work together.

Global trade depends on common standards. Financial institutions rely on shared payment networks. Supply chains operate because participants can exchange information across organizations, platforms, and borders.

Artificial intelligence is bringing this challenge into focus again.

AI Adoption Is Accelerating

According to the 2025 McKinsey Global Survey on AI, 78% of organizations report using AI in at least one business function, up from 55% in 2023.

Many mid-size businesses have adopted AI through individual tools for customer service, marketing, analytics, software development, and operations. The result is often a collection of capable systems that operate independently.

The question is no longer whether businesses are using AI. It is whether their AI systems can effectively interact with the data, platforms, and processes that already exist across the organization.

Why Interoperability Matters

AI systems depend on access to reliable information. When data is fragmented across departments or platforms, the effectiveness of AI can be limited.

This is one reason why standards bodies and technology providers are increasingly discussing common frameworks for data exchange, governance, and system integration.

The objective is not uniformity. It is compatibility.

Businesses that structure their data, processes, and technology around open and interoperable approaches may find it easier to integrate future AI capabilities without rebuilding their foundations.