Transcribing recordings with AI

Most memberships are sitting on hours of recorded material: monthly Q&A calls, webinars, expert interviews, workshop replays and coaching sessions. Members can only find what is in those recordings by watching them from start to finish, which most will never do. A written transcript changes that. It makes recordings searchable, gives members who cannot or prefer not to listen a way in, and turns every recording into raw material for notes, summaries and new content.

Manual transcription used to take hours for each hour of audio. AI transcription now produces a usable draft in minutes. The draft is not perfect, though, and recordings often contain things members said in confidence. This guide covers choosing a tool, handling privacy properly and getting from rough draft to a transcript you are happy to publish.

What a good transcript gives your members

A transcript is useful in more ways than most owners expect:

• Search. Members can find the exact moment an expert answered their question.
• Accessibility. Members who are deaf or hard of hearing, or who simply prefer reading, get the same value from the session.
• Skimming. Busy members can read a session in ten minutes instead of watching for an hour.
• Quotes and notes. You can pull accurate quotes and create session notes without replaying the audio.

Choosing a transcription tool

There are three common routes:

• Dedicated transcription and editing tools such as Otter.ai and Descript. They are built for the job, usually label speakers and export in several formats.
• Your video meeting platform. Zoom, Microsoft Teams and Google Meet can produce transcripts of calls, depending on your account settings.
• General AI assistants. Some assistants accept audio or video files and can transcribe them, which suits the occasional short recording.

When comparing, look at speaker labels, the ability to add custom vocabulary (your niche's jargon and people's names), timestamps, export formats and, above all, the data and training settings. Run the same twenty-minute recording through two tools and compare the results on your own content, since accuracy varies with accents, audio quality and subject matter. Tools change often, so repeat the test if you have not looked in a while.

Consent and privacy come first

Recordings of member calls contain personal information: names, business details, health questions, family situations. Before you transcribe anything:

• Tell participants at the start that the session is recorded and transcribed, and how the transcript will be used.
• Keep one-to-one coaching calls private unless the member explicitly agrees otherwise.
• Do not upload member recordings to a consumer AI tool on a personal account. Use a business plan, switch off the setting that allows your data to be used for training, and read the vendor's terms on storage and deletion.
• Delete recordings and transcripts you no longer need.

For the wider picture on this, read protecting member privacy when you use AI tools.

Clean up the draft with a careful prompt

Raw AI transcripts include filler words, false starts, misheard terms and long unbroken paragraphs. You can use an AI assistant under your business plan to tidy them, as long as you tell it firmly not to change the meaning. Imagine Brushstroke Academy, a watercolor membership, cleaning up a monthly Q&A transcript:

Below is an AI-generated transcript of a [type of session] for [describe your membership]. Please produce a clean-read version. Remove filler words such as um, uh and you know, and remove false starts. Break the text into short paragraphs and keep the speaker labels. Correct obvious mis-transcriptions of these terms and names: [list your glossary terms and speakers' names]. Do not summarize, reword, add or remove any substantive content. Where a word is unclear and you are guessing, mark it as [unclear]. Transcript: [paste transcript]

A good result reads like the conversation that took place, only tidier. If the assistant has smoothed a hesitant answer into a confident one or merged two speakers, go back and tighten the instructions. Good prompts follow the pattern in prompting basics: how to ask AI for what you actually want, and a short glossary makes the biggest difference.

Review before members see it

A person who knows the subject should read every transcript before it is shared. Focus on the places where AI is most likely to be wrong:

1. Names of people, products, places and organizations.
2. Numbers, such as measurements, amounts, dates and doses, which can be misheard with serious consequences.
3. Technical terms in your niche.
4. Speaker labels, especially when people talk over each other.
5. Anything marked [unclear]. Listen to that section of the recording and fix it.
6. Sensitive details that should be removed before publishing, such as a member mentioning a health condition or a client's name.

For a Q&A session shared with all members, it is courteous to remove surnames and identifying details of members who asked questions, unless they have agreed to be named.

Your first steps

• Choose one recent recording that members would find useful in written form.
• Check the data and training settings of the transcription tools you are considering.
• Write a glossary of names and terms your recordings often include.
• Transcribe the recording in two tools and compare accuracy.
• Clean up the better draft with the prompt above, then review it against the audio.
• Add a recording and transcription notice to the start of your live sessions.

Once you have transcripts, you can do much more with your recordings. For the non-AI side of turning sessions into lasting library content, see turning live sessions into lasting library content.