# Requirements Engineering Challenges in Building AI-Based Complex Systems

arXiv: https://arxiv.org/abs/1908.11791 · HTML: https://mlsanity.com/paper/1908.11791/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Aug 2019.

## Built on by (most cited first, 21 of 21)

- [Software Engineering for AI-Based Systems: A Survey](https://mlsanity.com/paper/2105.01984/) (2021)
- [Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study](https://mlsanity.com/paper/2103.09783/) (2021)
- [Management of Machine Learning Lifecycle Artifacts: A Survey](https://mlsanity.com/paper/2210.11831/) (2022)
- [Requirements Engineering for Machine Learning: A Review and Reflection](https://mlsanity.com/paper/2210.00859/) (2022)
- [Requirements Engineering Framework for Human-centered Artificial Intelligence Software Systems](https://mlsanity.com/paper/2303.02920/) (2023)
- [Artificial Intelligence in Industry 4.0: A Review of Integration Challenges for Industrial Systems](https://mlsanity.com/paper/2405.18580/) (2024)
- [How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directions](https://mlsanity.com/paper/2409.07192/) (2024)
- [A Catalog of Fairness-Aware Practices in Machine Learning Engineering](https://mlsanity.com/paper/2408.16683/) (2024)
- [Pairing Conceptual Modeling with Machine Learning](https://mlsanity.com/paper/2106.14251/) (2021)
- [RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers](https://mlsanity.com/paper/2207.08857/) (2022)
- [MLOps Spanning Whole Machine Learning Life Cycle: A Survey](https://mlsanity.com/paper/2304.07296/) (2023)
- [Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models](https://mlsanity.com/paper/2504.16969/) (2025)
- [The Impact of Environment Configurations on the Stability of AI-Enabled Systems](https://mlsanity.com/paper/2408.02825/) (2024)
- [How to Measure Human-AI Prediction Accuracy in Explainable AI Systems](https://mlsanity.com/paper/2409.00069/) (2024)
- [Improving Requirements Classification with SMOTE-Tomek Preprocessing](https://mlsanity.com/paper/2501.06491/) (2025)
- [Data Requirement Goal Modeling for Machine Learning Systems](https://mlsanity.com/paper/2504.07664/) (2025)
- [Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Development](https://mlsanity.com/paper/2510.04380/) (2025)
- [From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systems](https://mlsanity.com/paper/2603.00472/) (2026)
- [Persona-Based Requirements Engineering for Explainable Multi-Agent Educational Systems: A Scenario Simulator for Clinical Reasoning Training](https://mlsanity.com/paper/2604.17186/) (2026)
- [From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systems](https://mlsanity.com/paper/2608.01001/) (2026)
- [Software Engineering for AI-driven Building Operation](https://mlsanity.com/paper/2608.16237/) (2026)

## Abstract (arXiv)

This paper identifies and tackles the challenges of the requirements engineering discipline when applied to development of AI-based complex systems. Due to their complex behaviour, there is an immanent need for a tailored development process for such systems. However, there is still no widely used and specifically tailored process in place to effectively and efficiently deal with requirements suitable for specifying a software solution that uses machine learning. By analysing the related work from software engineering and artificial intelligence fields, potential contributions have been recognized from agent-based software engineering and goal-oriented requirements engineering research, as well as examples from large product development companies. The challenges have been discussed, with proposals given how and when to tackle them. RE4AI taxonomy has also been outlined, to inform the tailoring of development process.