Susan Catron had seen enough AI failures to know the risks. As managing editor of The Current, a coastal Georgia nonprofit covering communities abandoned by consolidated newspapers, she watched general-purpose AI tools produce convincing nonsense. Her newsroom couldn’t afford that kind of mistake.
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The Current faced the classic small-newsroom bind: 10 people responsible for investigative reporting plus all the digital publishing mechanics: SEO headlines, social media posts, newsletter formatting. Every hour spent sweating metadata was an hour not spent on accountability journalism. But adopting untested AI could destroy the trust The Current had built since its launch in 2020.
Nota offered a middle path: journalism-specific AI trained on newsroom data, not internet content. The platform doesn’t write articles; it reformats journalist-created content for different channels. Setup takes under an hour. Catron could test one feature, evaluate results, then expand cautiously.
This quick reference covers how they did it and what they learned.
The gist
The Current’s cautious, incremental rollout turned AI skepticism into measurable efficiency gains:
- Setup required less than one hour; ongoing maintenance takes 15-30 minutes weekly
- Platform now handles most SEO tasks, saving hours of reporter bandwidth
- Social media suggestions used for approximately 50 percent of posts
How they did it
The Current‘s implementation strategy prioritized testing before commitment:
- Started with headlines only: Catron piloted headline optimization alone, evaluating three AI-generated suggestions against her editorial judgment to build trust in the system without risking full workflow integration.
- Uploaded representative content: Team provided 10-15 articles establishing The Current’s tone and style, training Nota on their voice preferences and AP style conventions.
- Expanded to SEO automation: After several weeks of headline testing validated quality, added tag generation, slug optimization and meta description tools to reclaim time spent on publishing mechanics.
- Added social media formatting: Implemented platform-specific caption generation for approximately half of social posts, expanding digital capacity without hiring additional staff.
- Established review protocols: Built editorial approval checkpoints ensuring human oversight for every AI-generated suggestion before publication, maintaining quality control and audience trust.
Key numbers
- Setup time: Less than 1 hour for initial integration with WordPress CMS
- Weekly maintenance: 15-30 minutes reviewing and approving automated suggestions
- Social media adoption: Approximately 50 percent of posts now use Nota-generated captions
- Cost: $99/month for newsrooms under 7 FTE and $250K annual revenue
- Network scale: Institute for Nonprofit News uses Nota to distribute 26,000+ monthly stories across 500+ member newsrooms
What to watch for
Implementation challenges and limitations The Current encountered:
- Quality depends on input: Well-reported, well-written articles yield better AI outputs; the system amplifies existing quality rather than compensating for weak source material.
- Requires consistent use: CEO Josh Brandau notes value requires scale and consistency—sporadic adoption limits efficiency gains and prevents the system from learning newsroom preferences effectively.
- Limited documented metrics: Beyond qualitative time savings, The Current hasn’t tracked specific productivity metrics, making precise ROI calculations difficult for budget justification.
Small newsrooms considering similar implementations can explore Nota’s grant-backed pricing and CMS integration options at heynota.com. The platform works best for outlets seeking publishing task automation rather than content generation tools.
