How Sahan Journal Uses AI to Boost Efficiency While Protecting Editorial Integrity

How Sahan Journal Uses AI to Streamline Operations

Artificial intelligence is now a part of many news organizations' workflows. The key question is how to use it effectively. Using AI to write full stories without thorough human checks risks spreading inaccuracies. A safer approach is employing AI for headlines, summaries, and social posts, always reviewed by editors. But the most practical use lies in automating internal tasks that consume time but don’t require editorial judgment.

Sahan Journal, a six-year-old nonprofit digital outlet covering immigrants and communities of color in Minnesota, is applying AI this way. Supported by a $220,000 grant from the American Journalism Project and OpenAI, they’ve integrated AI to handle tasks like processing financial data on charter schools, creating Instagram story summaries, and adding audio to articles.

The biggest gains have come on the revenue side. AI helps the Journal refine its media kit and analyze audience interests, such as gauging how much their readers care about public transportation. This improves targeting and potentially boosts funding.

Still, Sahan remains cautious about using AI for editorial content. Cynthia Tu, the Journal’s data journalist and AI specialist, notes that even internal AI applications can be unreliable, sometimes generating false data despite clear instructions not to access external sources. This raises concerns about building systems on platforms like OpenAI’s, which face financial sustainability challenges.

Quality Matters More Than Ever

Concerns about AI-powered search engines, like Google's new AI search, suggest potential threats to news traffic. However, the impact varies. High-quality journalism brands like The New York Times and The Wall Street Journal have been less affected than outlets relying on clickbait.

For local news organizations, focusing on distinct, community-centered content offers insulation from such disruptions. Building trust and relevance with local audiences reduces reliance on search traffic and strengthens long-term engagement.

Using AI to Screen Pitches Efficiently

Caleb Okereke, a Ph.D. student and editor at Minority Africa, faces a common challenge: a surge in story pitches without a proportional increase in editorial staff. To manage the volume, his team developed Iraka, a customized AI tool that performs an initial screening of submissions.

Iraka assists editors by providing a first-pass review, but every pitch still receives human reading. No editorial decisions rely solely on AI. This cautious integration helps maintain fairness and depth while improving workflow efficiency.

Such AI tools can ease operational burdens for small editorial teams by filtering and organizing incoming content, freeing staff to focus on quality control and reporting.

Practical Takeaways for Operations Professionals

• Use AI to automate routine internal tasks: Data processing, summarizing, and audience analysis can be handled efficiently with AI, improving productivity.
• Maintain human oversight: AI-generated editorial content requires careful review to avoid errors or misinformation.
• Focus on quality content: Building a loyal, engaged audience through distinctive journalism remains the best defense against traffic losses from AI-driven search changes.
• Integrate AI tools gradually: Employ AI to assist, not replace, your team. Start with non-critical tasks and expand as confidence grows.

Operations leaders can learn from organizations like Sahan Journal and Minority Africa to adopt AI pragmatically, balancing efficiency gains with quality control.

For those interested in exploring AI tools and training for operational roles, resources like Complete AI Training offer relevant courses and certifications.