How to Use Gen AI For Storytelling and Content Creation
TLDR: Generative AI tools aren’t magic—they’re data, algorithms, and compute power working together. But their impact on content creation and business storytelling is profound. If you treat language as a system—whether it’s customer queries, video scripts, or internal comms—AI can help you produce better stories, faster, and at scale.
Why storytelling still matters in the age of AI
Storytelling isn’t dead. It's just changed form.
In the past, companies told stories in brochures, scripts, or brand videos. That still happens, but now, story flows through your support chatbot, explainer pages, onboarding emails, product UI, and even code documentation.
Every part of your business “speaks.” And AI helps you write all of it without needing a writer in every room.
That’s why businesses are rethinking content as a system of language: every interface, every function, every touchpoint. According to IBM’s Darío Gil, “If you squint, everything starts to look like a language that can be deciphered and understood.” And once it’s language, it’s trainable.
This isn’t just about automating copy. It’s about building community, clarity, and trust.
What is generative AI, really?
Strip the hype. At its core, generative AI is just a way of predicting what comes next based on patterns in huge volumes of data.
- Early deep learning used labelled data with humans tagging content
- Then came transformers and self-supervised learning
- Now we have foundation models that adapt to your domain, tone, and data
- These models don’t “know” things. They simulate knowledge by predicting words, images, or audio sequences with high probability.
What that means for your business: You can use generative AI to rapidly generate original content—but only if your inputs are strong, your domain is clear, and your purpose is well-scoped.
The model is only as good as what you feed it and how you guide it.
How content creation is being reshaped
Most enterprise content teams don’t need a poet. They need a system.
AI changes how we scale content creation by:
- Turning past documentation into training data for new comms
- Rewriting tone for different channels or audience segments
- Autocompleting templates, reports, onboarding guides, or internal wikis
- Synthesising video transcripts or meeting notes into usable formats
More importantly, AI enables community co-creation. If your audience is engaged, so think forums, comment threads, social channels then you can train on that data, amplify their voice, and produce content with them, not just for them.
Tools You Should Be Using
- ChatGPT / Claude / Gemini: For quick script generation, tone rewriting, or internal wiki drafting.
- Descript or OpusClip: Turn video recordings into text and summarise them for distribution.
- Mem / Notion AI / Scribe: Build living documentation or training guides from scattered inputs.
- ElevenLabs / Murf / Runway: Convert text to synthetic voiceovers or visual B-roll for presentations or short-form video.
Start with one channel: say, your onboarding emails. Use AI to:
- Transcribe and summarise your team walkthrough videos.
- Draft a three-part welcome sequence in your voice.
- Personalise versions based on job role or segment.
Your job shifts from writing everything manually to curating structure, tone, and intent.
Protect your data. It's your content edge.
Gil’s final warning lands clearly: don’t outsource your data.
If your AI storytelling system relies on someone else’s data or model, you’re handing over your differentiation. The businesses doing this well are:
- Treating internal comms, chat logs, customer feedback as gold
- Fine-tuning models on that trusted data
- Layering their tone, vocabulary, and IP on top
Here’s a simple AI-powered framework for small teams:
Your AI-Powered Content System
- Collect your raw material
Pull transcripts, meeting notes, support chats, or internal docs using tools like - Otter or Fireflies.
Summarise into usable outlines - Use ChatGPT or Claude to extract key points, themes, or bullet summaries from messy source material.
- Draft your content
Turn those summaries into first-draft articles, emails, scripts, or social posts with - ChatGPT, Gemini, or Claude.
Adapt for each format or channel - Tweak tone, voice, and structure for different audiences or platforms using Jasper, Copy.ai, or Notion AI.
- Publish and distribute efficiently
Use tools like Notion, Airtable, or Zapier to build a lightweight workflow that gets the right content to the right peoplewithout endless back-and-forth.
Start building your AI content capability
Don’t wait for a Chief AI Story Officer. You already have the pieces:
- SMEs who understand your product
- Ops teams buried in documentation
- Brand people who care about voice
Start with a small project: automate internal FAQs. Build a chatbot on your support docs. Use AI to rewrite your tone guide for five new formats.
That’s how you build capacity, credibility, and content that speaks like your business not a tech demo.
Want to scale your content creation and community impact—without losing your voice? Start by building foundational AI fluency across your team. Our AI Fundamentals Masterclass is designed for non-technical teams ready to experiment, build, and ship value.
FAQs
Q: What kind of content can generative AI create?
A: Text, images, audio, video. If it can be represented in data, it can be generated—provided your inputs and guardrails are strong.
Q: Isn’t AI content generic?
A: Only if your data is. When you fine-tune models on your brand voice, customer data, and domain-specific knowledge, the results reflect your identity.
Q: How does AI help with community building?
A: AI can surface patterns in user feedback, personalise responses, and even generate content alongside users—turning passive audiences into co-creators.
Q: Do I need my own model?
A: No. But you need to control how the model is used—your prompts, your data, your oversight.