Using AI to Generate Show Notes, Descriptions, and Social Copy

AI text generation has become a genuinely useful tool in podcast production workflows — not for

replacing the host's voice, but for handling the time-consuming administrative writing tasks that

have to happen every episode.

Where AI Works Well in Podcast Writing: Transcribing an episode and then prompting an AI tool

to generate: a 200-word episode summary, five social media post options featuring key quotes, three

potential thumbnail text hooks, and a formatted show notes template with key topics listed — this

workflow produces usable drafts in minutes.

The output requires editing. The language is often generic, the emphasis may miss what was

actually most interesting in the episode, and the host's voice and perspective rarely come through in

AI-generated copy without significant rewriting. But "edit a draft" is meaningfully faster than "write

from scratch," particularly for the episodic administrative writing that podcasters do every week.

Prompting Effectively: The quality of AI-generated podcast copy scales with the quality of the

transcript and the specificity of the prompt. A prompt that says "write show notes for this podcast"

produces generic show notes. A prompt that says "you are writing show notes for a podcast aimed

at Toronto small business owners; highlight the three most practical insights from this transcript;

use a direct, informal tone; lead with the most surprising point" produces something more usable.

What Not to use AI For in Podcast Writing: Your author voice in editorial content — op-ed style

posts, your weekly email to subscribers, personal reflections on the show — should be yours.

Audiences can often detect AI-generated text in the context of personal communication, and it

creates a subtle disconnection from the authentic relationship you're building.