{
  "id": 7335,
  "url": "https://arxiv.org/abs/2603.11842v1",
  "title": "The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research Agendas",
  "summary": "As organizations grapple with the rapid adoption of Generative AI (GenAI), this study synthesizes the state of knowledge through a systematic literature review of secondary studies and research agendas. Analyzing 28 papers published since 2023, we find that while GenAI offers transformative potential for productivity and innovation, its adoption is constrained by multiple interrelated challenges, including technical unreliability (hallucinations, performance drift), societal-ethical risks (bias,",
  "authors": "Aleksander Jarzębowicz, Adam Przybyłek, Jacinto Estima, Yen Ying Ng, Jakub Swacha, Beata Zielosko et al.",
  "category": "research",
  "topics": "bias-fairness,jobs-economy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-12T12:06:25.000Z",
  "fetched_at": "2026-07-14T16:33:08.014Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7335",
  "original_url": "https://arxiv.org/abs/2603.11842v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}