To maintain quality, 6AM City's AI newsletters don't generate content from scratch. Instead, they use "extractive generative" AI to summarize information from existing, verified sources. This minimizes the risk of AI "hallucinations" and factual errors, which are common when AI is asked to expand upon a topic or create net-new content.

The company Anti-Fraud pioneers a "Snitching as a Service" model where it only earns revenue when its AI-powered investigations lead to government recovery from corporate fraud. This whistleblower-driven approach perfectly aligns incentives and provides a sustainable financial path for investigative journalism, an industry that has struggled with traditional advertising and subscription models.

AI is not solely a tool for the powerful; it can also level the playing field. Grassroots political campaigns and labor organizers can use AI to access capabilities—like personalized mass communication and safety reporting apps—that were previously only affordable for well-funded, established entities.

Journalist Casey Newton uses AI tools not to write his columns, but to fact-check them after they're written. He finds that feeding his completed text into an LLM is a surprisingly effective way to catch factual errors, a significant improvement in model capability over the past year.

AI tools like Claude Code are evolving beyond simple SQL debuggers to augment the entire data analysis workflow. This includes monitoring trends, exploring data with external context from tools like Slack, and assisting in crafting compelling narratives from the data, mimicking how a human analyst works.

The risk of unverified information from generative AI is compelling news organizations to establish formal ethics policies. These new rules often forbid publishing AI-created content unless the story is about AI itself, mandate disclosure of its use, and reinforce rigorous human oversight and fact-checking.

In studying sperm whale vocalizations, an AI system trained on human languages did more than just process data. It actively "tipped off" researchers to look for specific spectral properties resembling human vowels. This highlights AI's evolving role in scientific discovery from a pure analytical tool to a source of hypothesis generation.

Traditional automated dashboards are often ignored. AI-driven reporting is superior because it doesn't just present data; it actively analyzes it. The AI summarizes trends, generates relevant follow-up questions, and even attempts to answer them, ensuring that insights are never missed, even when stakeholders are busy.

Instead of using AI to score consumers, Experian applies it to governance. AI systems monitor financial models for 'drift'—when outcomes deviate from predictions—and alert human overseers to the specific variables causing the issue, ensuring fairness and regulatory compliance.