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TRUVACE RECORD VERSION
record: TRV-2026-0156
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-13T09:06:42.101647Z
status: published
lens: trace
sector: science
headline: They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism
dek: Declining newspaper revenues prompt local newsrooms to adopt automation to maintain efficiency and keep the community informed. However, current research provides a limited understanding of how local journalists work with digital data and which newsroom processes would benefit most from AI-supported (data) reporting. To bridge this gap, we conducted 21 semi-structured interviews with local journalists in Germany. Our study investigates how local journalists use data and AI (RQ1); the challenges they encounter wh…
gain_title: Local journalists in Germany reported willingness to use AI-supported tools to process data and discover stories to help maintain efficiency.
problem_title: Local journalists in Germany do not fully leverage AI to support data-related reporting work, linked to limited awareness of what AI can do.
trace_subject: AI-supported data reporting for local journalists in Germany to process data and support reporting
gain_reading: Local journalists in Germany reported willingness to use AI-supported tools to process data and discover stories to help maintain efficiency.
gain_evidence: they are willing to use it to process data and discover stories | maintain efficiency and keep the community informed
problem_reading: Local journalists in Germany do not fully leverage AI to support data-related reporting work, linked to limited awareness of what AI can do.
problem_evidence: local journalists do not fully leverage AI's potential to support data-related work | Despite local journalists' limited awareness of AI's capabilities
quick_read: By April 13 2026, researchers reported results from 21 semi-structured interviews with local journalists in Germany examining use of data and AI, challenges in interaction, and perceived opportunities for AI-supported reporting systems.

The work matters because local newsrooms are adopting automation to sustain operations amid revenue decline, yet the study suggests a gap between willingness to use AI and actual use; it remains uncertain which specific reporting workflows would benefit most and how to raise capability awareness without overestimating AI.
limitation: Findings are bounded by a small qualitative sample of 21 local journalists in Germany and by limited existing research on local data practices, which constrains generalizability.
tag: Automated dual reading
key_points: Study based on 21 semi-structured interviews with local journalists in Germany | Investigated how journalists use data and AI, challenges encountered, and perceived opportunities through discursive design | Found limited awareness of AI capabilities and underutilization for data-related work despite openness to adoption
rundown: The authors framed the work against declining newspaper revenues prompting automation adoption, and noted a gap in understanding which newsroom processes would benefit most from AI-supported reporting.

They used discursive design to elicit self-perceived opportunities and imagined future capabilities, aiming to ground recommendations in journalists' socio-technical perspective.
sources:
- peer_reviewed | Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems | https://doi.org/10.1145/3772318.3791130 | 2026-04-13
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