ChatGPT is powerful. But it’s not your strategist, your ops lead, or your product expert—until you train it to be.
That’s the shift forward-thinking companies are making:
They’re turning GPTs from generalists into specialists.
And when you train your own GPT on internal assets—sales calls, SOPs, customer feedback—you stop getting generic answers and start getting real leverage.
Why Generic GPTs Fall Short
- They don’t know your voice
- They don’t understand your customers
- They can’t prioritize based on your goals
- They guess. You can’t scale guesswork.
What you need is an internal GPT that speaks your playbook fluently.
What Internal GPTs Actually Do
When trained on your proprietary data, internal GPTs can:
- Answer team questions using actual company SOPs
- Draft sales emails with context from real deals
- Summarize weekly pipeline reports tailored to your definitions
- Flag misaligned content or outdated messaging
- Auto-generate onboarding, docs, or product updates
This isn’t plug-and-play ChatGPT. This is an AI operator trained on your edge.
How to Build an Internal GPT That Works
1. Define Its Role
“You are a B2B growth assistant trained on our sales scripts, onboarding decks, and FAQ documents.”
Don’t let it be a free-for-all. Scope it like a hire.
2. Feed It the Good Stuff
Upload:
- Sales call transcripts
- Objection handling docs
- Buyer personas
- Marketing copy that’s converted
- Win/loss notes
Think of this as its onboarding—train it like you would a new team member.
3. Build a Prompt System
Create a prompt library for:
- “Summarize this call in 3 bullet points for a follow-up email”
- “Draft a landing page for this new fintech use case”
- “Rewrite this blog in our tone of voice with a stronger CTA”
Now your team has reusable workflows—not just a blank prompt box.
4. Review, Refine, Retrain
Use outputs weekly. Gather feedback. Improve the system.
The more you use it, the more it learns your nuance and improves.
What to Do This Week
- Choose one area where you repeatedly answer the same internal questions
- Gather the 10 most used docs or assets for that use case
- Train a GPT on them and assign it a role
- Build 3 go-to prompts
- Use it for one week and track time saved, quality of output, and team feedback
The companies building real moats with AI aren’t using it to replace people.
They’re using it to amplify what already works—and make it scalable.
