# AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agents

arXiv: https://arxiv.org/abs/2502.17443 · HTML: https://mlsanity.com/paper/2502.17443/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- Builds on 2 of its 16 references that are in the map.
- First posted on arXiv 22 Jan 2025.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Builds on (most cited first, 2 of 2)

- [Gorilla: Large Language Model Connected with Massive APIs](https://mlsanity.com/paper/2305.15334/) (2023)
- [TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs](https://mlsanity.com/paper/2303.16434/) (2023)

## Built on by (most cited first, 11 of 11)

- [AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges](https://mlsanity.com/paper/2505.10468/) (2025)
- [Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions](https://mlsanity.com/paper/2510.25445/) (2025)
- [Agentic Web: Weaving the Next Web with AI Agents](https://mlsanity.com/paper/2507.21206/) (2025)
- [Intelligent AI Delegation](https://mlsanity.com/paper/2602.11865/) (2026)
- [Self-Organizing Agent Network for LLM-based Workflow Automation](https://mlsanity.com/paper/2508.13732/) (2025)
- [Architecting Trust in Artificial Epistemic Agents](https://mlsanity.com/paper/2603.02960/) (2026)
- [Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog](https://mlsanity.com/paper/2507.14063/) (2025)
- [An Agentic AI for a New Paradigm in Business Process Development](https://mlsanity.com/paper/2507.21823/) (2025)
- [Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs](https://mlsanity.com/paper/2605.21027/) (2026)
- [Leveraging Large Language Model for Intelligent Log Processing and Autonomous Debugging in Cloud AI Platforms](https://mlsanity.com/paper/2506.17900/) (2025)
- [From Performance to Purpose: A Sociotechnical Taxonomy for Evaluating Large Language Model Utility](https://mlsanity.com/paper/2602.20513/) (2026)

## Abstract (arXiv)

The rapid advancement of Generative AI has catalyzed the emergence of autonomous AI agents, presenting unprecedented challenges for enterprise computing infrastructures. Current enterprise API architectures are predominantly designed for human-driven, predefined interaction patterns, rendering them ill-equipped to support intelligent agents' dynamic, goal-oriented behaviors. This research systematically examines the architectural adaptations for enterprise APIs to support AI agentic workflows effectively. Through a comprehensive analysis of existing API design paradigms, agent interaction models, and emerging technological constraints, the paper develops a strategic framework for API transformation. The study employs a mixed-method approach, combining theoretical modeling, comparative analysis, and exploratory design principles to address critical challenges in standardization, performance, and intelligent interaction. The proposed research contributes a conceptual model for next-generation enterprise APIs that can seamlessly integrate with autonomous AI agent ecosystems, offering significant implications for future enterprise computing architectures.