Price Ai Discount Response

---
name: price-ai-discount-response
description: Prepares your answer to a client who wants a discount because you use AI, with what the request really asks, what changed in the work, four honest options, the trades on offer and a reply draft you send or say. Use for "run price-ai-discount-response", "the client wants money off because I use AI", "AI discount request", "they say AI should make it cheaper", "should I lower my fee because of AI", "reply to a discount request", "the client wants a share of my AI savings", part of the Pricing Under AI Pressure Pack by Polar Bear.
---

# AI Discount Response

## When To Use
A client asks for a discount "because you use AI now", and you are tempted to say yes to keep the peace or no to keep your pride. This answers one question: what has really changed in the work, and which honest option do you offer back?

## When Not To Use
If you have not yet decided, per service, what happens to the time AI saves you, run AI Savings Decision first; answering one client before you have a policy sets the policy by accident. If the client doubts your value but has not asked for money, run AI Objection Answer.

## Inputs
- The request word for word; with the Gmail connector I can find and read the thread (read only; you send the reply)
- Your AI Activity Map rows, your AI Savings Decision for this service, and the current fee, scope and contract dates for this client
If you have none of this, I start from the request and your current fee and mark the output as a first draft.

## Approach
Trade across issues instead of lowering the price of the same work, as the Harvard Program on Negotiation describes on its public pages: each side values timing, scope, term and payment differently, so a concession on one can buy something you value on another. Every concession is named with what it costs you. The failure this prevents is the quiet percentage off that teaches the client your price was never real.

## Workflow
1. Ask, all at once: what exactly did the client ask for, and who sent it? Have you made an AI Savings Decision for this service? What would you value in return (a longer term, faster payment, a phased start)?
2. Record the request in the client's words, then name the interest behind it: a budget cut, fairness, wanting a share of savings, pressure from their boss. You pick the one that fits, or plan a question to find out.
3. Set out what changed in the work, from measured rows only: activities where time fell, new review work AI added, the net saving. Then your AI Savings Decision for the service. If you have no decision yet, say so and stop here until you make one.
4. Lay out the four options with what each does to your margin and to the client: same price, with what the client now gets made visible (depth, speed, an extra check); less scope for less money, naming exactly what is removed; a different model (fixed fee, outcome-based); no, with the reason.
5. For any option that gives something, name the trade: what you concede, what it costs you, what you ask in return. A concession with nothing asked back is a discount, and it is struck out.
6. Draft the reply in your voice: thanks, what changed honestly (AI included), the option you choose, the trade if any, an offer to talk. You choose the option and send or say it.

## Output Format
```markdown
# AI Discount Response
Client: [name or code] · Service: [service] · Request received: [date]
## The request
> [their words as sent]
Interest behind it: [budget / fairness / share of savings / pressure from above] · Basis: [what you know]
## What changed in the work
| Activity | Time before | Time now plus new AI work | Measured on |
|---|---|---|---|
| [activity] | [your figure] | [your figure] | [jobs] |
My AI Savings Decision for this service: [pass on / keep / reinvest / not decided]
## Four options
| Option | What the client gets | Effect on my margin | Honest to the client because |
|---|---|---|---|
| Same price, more shown | [what is made visible] | [your figure] | [reason] |
| Less scope, less money | [scope removed] | [your figure] | [reason] |
| Different model | [fixed fee / outcome] | [your figure] | [reason] |
| No | [what stays] | [none] | [reason] |
## Trades
| I concede | It costs me | I ask in return |
|---|---|---|
| [item] | [cost] | [term, timing, payment, scope] |
Reply draft: [short reply in your voice]
## Decision
[You] choose one option and the trade by [date], and send or say the reply yourself.
```

## Done When
- The request is in the client's words, and what changed rests on measured rows or is marked missing
- Each option names its effect on your margin from your own figures, and every concession has something asked in return

## Quality Bar
- The same work is never offered at a lower price; less money means less scope
- No percentage, benchmark or "what others give" appears unless it is your own figure
- The reply states how you use AI plainly and never blurs it
- No profiling of the person who asked; the request is answered, not the requester
- Honest options only; the owner decides and sends

## Next
Run price-ai-brief-review (AI-Written Brief Review) for the next pressure point, the AI-written brief.

## About the makers

This pack is made by Polar Bear, a consultancy built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).