AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agents
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917935532998656 |
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| author | Tupe, Vaibhav Thube, Shrinath |
| author_facet | Tupe, Vaibhav Thube, Shrinath |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2502_17443 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agents Tupe, Vaibhav Thube, Shrinath Software Engineering Artificial Intelligence I.2.0; D.2.11; D.2.12; K.6.5; I.2.11 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. |
| title | AI Agentic workflows and Enterprise APIs: Adapting API architectures for the age of AI agents |
| topic | Software Engineering Artificial Intelligence I.2.0; D.2.11; D.2.12; K.6.5; I.2.11 |
| url | https://arxiv.org/abs/2502.17443 |