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TRUVACE RECORD VERSION
record: TRV-2026-0868
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-24T14:14:24.649906Z
status: published
lens: trace
sector: entertainment
headline: Agentic AI in Newsrooms: Towards a multi-dimensional framework for evaluating trust, editorial accountability, and workflow quality
dek: As artificial intelligence (AI) systems evolve from assistive to agentic capable of autonomous planning, decision-making, and content generation existing evaluation frameworks struggle to capture their broader organizational and ethical implications. Most assessments of newsroom AI focus narrowly on technical accuracy or efficiency, overlooking how such systems reshape trust, governance, and human collaboration. This study conducts a systematic literature review of 46 peer-reviewed and institutional sources (201…
gain_title: Proposes a Four-Dimensional Evaluation Framework for agentic AI in journalism covering technical quality, human-organizational alignment, ethical-governance responsibility, and trust-value impact to balance innovation with accountability.
problem_title: Current newsroom AI assessments focus narrowly on technical accuracy or efficiency and struggle to capture broader organizational and ethical implications for trust, governance, and human collaboration.
trace_subject: evaluation of agentic AI performance in journalism newsrooms
gain_reading: Proposes a Four-Dimensional Evaluation Framework for agentic AI in journalism covering technical quality, human-organizational alignment, ethical-governance responsibility, and trust-value impact to balance innovation with accountability.
gain_evidence: offering a multi-dimensional structure for evaluating agentic AI systems that balances innovation with accountability and public value | The framework reconceptualizes AI success as a socio-technical equilibrium where technological capacity, ethical integrity, and collaborative trust co-evolve
problem_reading: Current newsroom AI assessments focus narrowly on technical accuracy or efficiency and struggle to capture broader organizational and ethical implications for trust, governance, and human collaboration.
problem_evidence: Most assessments of newsroom AI focus narrowly on technical accuracy or efficiency, overlooking how such systems reshape trust, governance, and human collaboration | existing evaluation frameworks struggle to capture their broader organizational and ethical implications
quick_read: As of November 2025, this peer-reviewed review examines agentic AI in newsrooms that can autonomously plan, decide, and generate content. Analyzing 46 sources from 2015-2025, it finds current evaluations emphasize technical accuracy and efficiency while neglecting trust, governance, and collaboration.

The authors propose a Four-Dimensional framework to assess technical quality, human-organizational alignment, ethical-governance responsibility, and trust-value impact. Its contribution is conceptual, offering a structure for Responsible AI in journalism, with empirical validation in real newsrooms still to be demonstrated.
limitation: 
tag: Dual reading
key_points: Systematic review of 46 peer-reviewed and institutional sources from 2015-2025 | Draws from Information Systems Success Theory, Socio-Technical Systems Theory, Accountability Theory, and Trust Theory | Defines 4D dimensions: Technical Quality, Human-Organizational Alignment, Ethical-Governance Responsibility, Trust-Value Impact
rundown: The paper identifies a gap as AI moves from assistive to agentic, noting existing frameworks miss organizational and ethical dimensions in journalism.

It synthesizes four theoretical lenses to build the 4D model and positions AI success as co-evolution of technological capacity, ethical integrity, and collaborative trust.
sources:
- peer_reviewed | World Journal of Advanced Research and Reviews | https://doi.org/10.30574/wjarr.2025.28.2.3766 | 2025-11-14
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