The Expert Validation Framework (EVF): Enabling Domain Expert Control in AI Engineering
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866915737648496640 |
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| author | Gren, Lucas Dobslaw, Felix |
| author_facet | Gren, Lucas Dobslaw, Felix |
| contents | Generative AI (GenAI) systems promise to transform knowledge work by automating a range of tasks, yet their deployment in enterprise settings remains hindered by the lack of systematic quality assurance mechanisms. We present an Expert Validation Framework that places domain experts at the center of building software with GenAI components, enabling them to maintain authoritative control over system behavior through structured specification, testing, validation, and continuous monitoring processes. Our framework addresses the critical gap between AI capabilities and organizational trust by establishing a rigorous, expert-driven methodology for ensuring quality across diverse GenAI applications. Through a four-stage implementation process encompassing specification, system creation, validation, and production monitoring, the framework enables organizations to leverage GenAI capabilities while maintaining expert oversight and quality standards. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_12327 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Expert Validation Framework (EVF): Enabling Domain Expert Control in AI Engineering Gren, Lucas Dobslaw, Felix Software Engineering Artificial Intelligence Generative AI (GenAI) systems promise to transform knowledge work by automating a range of tasks, yet their deployment in enterprise settings remains hindered by the lack of systematic quality assurance mechanisms. We present an Expert Validation Framework that places domain experts at the center of building software with GenAI components, enabling them to maintain authoritative control over system behavior through structured specification, testing, validation, and continuous monitoring processes. Our framework addresses the critical gap between AI capabilities and organizational trust by establishing a rigorous, expert-driven methodology for ensuring quality across diverse GenAI applications. Through a four-stage implementation process encompassing specification, system creation, validation, and production monitoring, the framework enables organizations to leverage GenAI capabilities while maintaining expert oversight and quality standards. |
| title | The Expert Validation Framework (EVF): Enabling Domain Expert Control in AI Engineering |
| topic | Software Engineering Artificial Intelligence |
| url | https://arxiv.org/abs/2601.12327 |