AI Research and Source Discovery

The Research Revolution

Research is where journalists spend the most time — and where AI delivers the biggest gains. A reporter researching a local developer’s ties to city hall might need to review years of council minutes, campaign finance records, property transactions, and previous news coverage. That’s days of work.

With AI, you can feed those documents into a tool and get a structured summary with key connections highlighted in an hour. You still read the critical documents yourself. But AI tells you which documents are critical.

Document Summarization

The bread and butter of AI-assisted research: turning massive documents into actionable briefings.

I'm a journalist researching [topic]. I have this [document type — court filing, government report, corporate annual report, etc.].

Please provide:
1. A 3-paragraph executive summary focusing on newsworthy elements
2. Key names, organizations, and their roles
3. Notable numbers (dollar amounts, dates, statistics)
4. Potential story angles based on what's unusual or significant
5. Questions this document raises but doesn't answer

Be specific. Cite page numbers or section references for key claims.

This prompt structure works for any document type. The “questions this raises” section is especially valuable — it points you toward follow-up research and interview questions.

✅ Quick Check: Why is the instruction “cite page numbers or section references” important when asking AI to summarize a document?

Because you need to verify. A summary that says “the company reported $4.2 million in losses” is only useful if you can quickly find that figure in the original document. Page references turn an AI summary from a vague overview into a research tool with traceable claims.

Building Background Dossiers

Before an interview or investigation, build a comprehensive background using AI:

I'm preparing to interview [person's name and title] about [topic].

Based on publicly available information, compile:
1. Professional biography and career timeline
2. Published quotes and public positions on [topic]
3. Organizations they're affiliated with
4. Previous media appearances or interviews
5. Potential areas of controversy or conflict of interest
6. Suggested interview questions based on gaps in public knowledge

Use only publicly verifiable information. Flag anything uncertain.

The dossier won’t replace your own reporting, but it ensures you walk into the interview prepared. You’ll know what they’ve already said publicly, so you can push into new territory rather than covering old ground.

Public Records Analysis

Government documents are goldmines — but they’re often buried in PDFs, spreadsheets, and databases that are hard to search. AI changes that:

Campaign finance records: Feed in donor lists and ask AI to identify patterns — large donations, corporate clusters, timing relative to legislative votes.

Government budgets: Upload budget documents and ask AI to compare year-over-year changes, flag unusual line items, and identify which departments saw the biggest increases or cuts.

Meeting minutes: Provide months of city council or board meeting minutes and ask AI to track how specific topics evolved, who voted which way, and when key decisions were made.

I have [N months/years] of [city council minutes / budget documents / inspection reports].

Analyze for:
1. How has [specific topic] been discussed over time?
2. Which individuals or organizations appear most frequently?
3. What decisions were made, and what were the vote breakdowns?
4. Are there any patterns or anomalies worth investigating?
5. What changed between [date] and [date]?

Source Discovery

Finding the right source is often the hardest part of a story. AI helps you cast a wider net:

Expert identification: Describe your story topic and ask AI to suggest types of experts who would have relevant knowledge — academic researchers, industry professionals, regulatory officials, community leaders.

Organizational mapping: For stories involving institutions, ask AI to help you understand the org chart. Who reports to whom? Who has decision-making authority? Who might have dissenting views?

Previous coverage analysis: Feed AI a collection of articles on your topic and ask it to identify sources quoted in previous coverage, perspectives that are missing, and angles that haven’t been explored.

Research Verification Habits

AI research requires a verification layer that traditional research doesn’t:

The 3-source rule: Any fact surfaced by AI must be confirmed by at least one independent source. Ideally, verify with the original document or a direct source.

Hallucination awareness: AI can generate plausible-sounding but fabricated details — fake court case names, non-existent studies, invented quotes. Always check.

Date sensitivity: AI training data has a cutoff. For recent events, supplement AI research with direct searches of news databases and primary sources.

Bias detection: AI summaries may reflect the biases in their training data. If you’re researching a controversial topic, ask AI to present multiple perspectives and note where sources disagree.

Exercise: AI-Assisted Research Sprint

Choose a topic you’re working on (or a story in today’s news):

1. Find a relevant public document (government report, court filing, corporate filing)
2. Feed it to an AI tool and use the summarization prompt above
3. Verify three specific claims from the summary against the original document
4. Use the background dossier prompt on a key figure in the story
5. Evaluate: How much time did AI save? What would you still need to check?

Key Takeaways

• AI summarization turns days of document review into hours — but always verify key claims against originals
• Background dossiers ensure you enter interviews prepared with knowledge of public positions and potential gaps
• Public records analysis with AI reveals patterns in campaign finance, budgets, and government proceedings that manual review would miss
• Source discovery is amplified by AI’s ability to map organizations, identify experts, and find overlooked perspectives
• Every AI research finding needs verification — the 3-source rule protects you from hallucinations and errors
• AI is your research assistant, not your source. You still do the journalism.

Up Next: In the next lesson, you’ll learn AI-assisted fact-checking — how to verify claims, cross-reference data, and catch errors before they become published mistakes.