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Science·The Trace·Automated dual reading·Published 2026-07-13

AI-supported data reporting for local journalists in Germany to process data and support reporting

Source article: They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism

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…

TRV-2026-0156Peer-reviewedPermanent record — cite & verify
Trace impact reading

Contested: both sides are scored from claims and sources, not community votes.

P 70The P score combines the specificity and measured human impact of the grounded problem claim with the strength of this Trace’s cited sources.G 70The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.
They Think AI Can Do More Than It Actually Can: Practices, Challenges, & Opportunities of AI-Supported Reporting In Local Journalism

"Army scientists energize battery research" by U.S. Army CCDC, CC BY-SA 2.0.

The 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.

Main 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
Gain

Local journalists in Germany reported willingness to use AI-supported tools to process data and discover stories to help maintain efficiency.

Problem

Local journalists in Germany do not fully leverage AI to support data-related reporting work, linked to limited awareness of what AI can do.

The 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.

What this doesn’t fix

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.

Sources

Reader signal

How should this claim be treated?

The debate