API governance in the age of AI: Designing for human and machine consumers

As artificial intelligence becomes increasingly integrated into software development, API governance is evolving to address its dual role as both a developer tool and a consumer. Experts in the field, including leaders from Tyk and Level 250, agree that while AI can accelerate prototyping, AI-generated APIs are not yet ready for production due to issues like hallucination and unreliable outputs. To mitigate these challenges, clear guidelines and standards should be embedded in AI prompts, and human reviewers and deterministic tools should validate outputs. Moreover, AI's role as a consumer presents its own set of challenges, with Model Context Protocols (MCPs) offering a way to bridge the gap by simplifying complex APIs for AI agents. Effective API governance in this context involves prioritizing clarity, consistency, and structured documentation to improve API design, ensuring that both human and machine consumers can interact seamlessly with APIs. This approach, supported by tools like Tyk AI Studio, aims to enhance productivity and create APIs that are efficient and reliable for both developers and AI-driven systems.