Research, ideation and scripting with AI

Ideas and scripts are where many creators first try AI. A blank page is intimidating, and a chat assistant will happily produce 20 video ideas, an outline and a draft script in seconds. That speed is real, but so are the risks: generic ideas that hundreds of other creators also received, scripts that sound like no one in particular, and factual errors delivered with total confidence. This lesson shows how to use AI as a research assistant and writing partner while keeping your own voice and protecting your credibility.

Where AI helps in pre-production

Pre-production covers everything before the camera rolls: choosing topics, researching, outlining, scripting, planning shots and preparing questions for interviews. AI can help at each step, but in different ways:

• Ideation: generating long lists of angles, hooks, titles and formats to react to. Quantity is the point; you supply the judgment.
• Research orientation: getting a quick overview of an unfamiliar topic, a list of questions to investigate and the names of key concepts, organizations and experts.
• Source digestion: summarizing long reports, transcripts or papers you provide, and pulling out the passages relevant to your angle.
• Structuring: turning messy notes into an outline, or testing different structures for the same material.
• Drafting and editing: producing a rough draft from your outline, tightening wordy passages, and checking reading level and pacing.
• Interview preparation: suggesting questions, follow-ups and possible objections, based on background material you provide.

What AI should not do is decide what is true, what you believe or what is worth saying. Those remain the creator's job.

Prompting basics

A prompt is the instruction you give an AI tool. Clear prompts get better results, and the principles are much the same as briefing a human assistant. Good prompts usually include:

• Role and audience: who the output is for and what they already know. "Write for first-time home bakers in Canada who have never used a sourdough starter."
• Task: exactly what you want, such as "give 15 title options under 60 characters" rather than "help with titles".
• Context and material: your notes, transcript, brand guidelines or examples of your past work.
• Constraints: length, tone, format, words to avoid, and whether to say "I don't know" when unsure.
• Examples: two or three samples of the style you want, which often work better than describing a style in words.

Iteration matters more than the perfect first prompt. Ask for options, react to them, and refine. Telling a model what you liked and disliked about its last answer usually improves the next one.

The last example shows a useful trick: ask the tool to mark claims that need checking and to point to where in the source each claim comes from. This makes your fact-checking faster and exposes claims the model cannot support.

Avoiding generic content

Language models are trained to produce likely text, which pulls them toward the average. If you ask for “ten video ideas about travel”, you will get the same ideas the tool gives everyone else. Audiences notice. Search and recommendation systems also tend to reward originality, depth and genuine expertise rather than recycled summaries.

Several habits push AI output away from the generic:

• Start from your own material: your notes, stories, opinions, data and experiences. Ask the tool to organize and challenge your ideas rather than invent them.
• Feed it your style: include transcripts of your best-performing videos and ask it to match the rhythm, humour and vocabulary.
• Ask for the unusual: request contrarian angles, overlooked sub-topics or questions experts disagree about.
• Use AI to critique, not just create: ask it to list weaknesses, missing counter-arguments or confusing passages in your draft.
• Rewrite in your own words: treat the draft as scaffolding. Read it aloud and change anything that does not sound like you.

A fact-checking workflow for AI-assisted scripts

Every script that uses AI for research or drafting needs a deliberate verification step before recording. A simple workflow that scales from solo creators to teams:

• 1. Tag claims: every statistic, date, name, quotation, scientific statement and legal or health claim gets a marker such as [CHECK] in the draft.
• 2. Extract a claim list: copy the tagged claims into a simple table with columns for the claim, the source and the status.
• 3. Verify against reliable sources: go to primary sources where possible, such as the original study, government data, the official website, court records or the person quoted. Reputable news organizations and reference works are next best. Never accept a citation from an AI tool without opening it and confirming it says what the tool claims.
• 4. Record, correct or cut: note the source link for each claim. Fix claims that are wrong and cut any you cannot confirm.
• 5. Second read: for important or sensitive videos, have someone else read the final script and spot-check the riskiest claims.

Keep the claim list. If a viewer challenges a fact, you can respond quickly with the source, and if you discover an error after publishing, the list shows where it came from.

Research tools that cite sources

Some AI tools search the web or a library of documents and show their sources alongside the answer. These research assistants are more useful for fact-finding than a plain chat model, because you can follow the links. But they can still misquote a source, rely on low-quality pages, or blend information from several sources into a claim none of them actually makes. Open the most important sources yourself, and prefer tools that let you restrict searches to trusted domains or upload the documents you want summarized.

When you summarize a document you supply, ask for page or timestamp references, then spot-check a sample. Summaries tend to drop qualifications, so watch for phrases such as “may”, “in some cases” or “preliminary findings” that disappear in the AI version.

Scripting with AI while keeping your voice

A script is not just information; it is performance. Rhythm, jokes, pauses, personal stories and the way you address viewers are what make content recognizably yours. Many experienced creators use AI at the edges of scripting rather than for the whole draft:

• Generating several possible openings or hooks, then writing their own.
• Asking for a clearer explanation of a hard concept, then rephrasing it in their own words.
• Shortening a draft that runs long, or flagging sentences that are hard to say aloud.
• Producing a version for a different audience, such as a simpler cut for younger viewers or a more technical version for experts.

If you publish under your name, you are the author in the eyes of your audience. Sponsors may also expect that the opinions and endorsements in their integrations are genuinely yours. CRE-320 covered the rule that endorsements must reflect the honest opinions of the endorser; an AI-written endorsement you have not actually formed an opinion about can mislead both audience and sponsor.

Confidentiality and what you upload

Be careful what you paste into AI tools. Unreleased sponsor campaigns, contracts, private messages, personal information about other people and unpublished work may be covered by confidentiality clauses or privacy law. Some services may use your inputs to improve their models unless you opt out or use a business plan with stronger terms. Read the data terms, use settings that turn off training on your content where available, and remove names and identifying details when you only need help with structure or wording. Lesson 10 covers the privacy law that applies.

A worked research session

Here is how a careful AI-assisted research session might run for a video on why bread goes stale. The creator starts by asking an assistant for an overview of the science and a list of key terms. The answer mentions starch retrogradation, moisture migration from crumb to crust and the effect of refrigeration. These terms become search queries for reliable sources: food science textbooks, university extension pages and peer-reviewed reviews.

Next, the creator uploads two review articles and asks for a summary with page references. The summary says refrigeration speeds staling; the creator checks the cited page and confirms it, along with the important qualification that freezing slows staling dramatically. The assistant then suggests three possible structures for the video, and the creator picks a myth-busting format built around common kitchen habits.

Finally, the creator drafts the script themselves from their notes, asks the assistant to flag sentences that are hard to say aloud, and tags 22 claims for checking. Two claims turn out to be overstated and are softened. The whole process takes about four hours instead of the eight a fully manual approach might take, and every claim in the final script has a source the creator has personally read.