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25 AI Prompts Every Support Agent Should Save (2026)

Copy-paste AI prompts for customer support teams. Structured for GPT-5/Claude, with JSON variables for Zendesk, Intercom, and Gorgias macros.

September 5, 2026· 23 min read
25 AI Prompts Every Support Agent Should Save (2026)

The short answer

These 25 structured AI prompts help support teams handle first contact, de-escalation, refunds, knowledge base creation, and agent QA. Each prompt includes copy-paste code blocks with bracketed variables and a JSON metadata schema for integration with platforms like Zendesk, Intercom, or Gorgias. They are designed for current models and incorporate compliance-aware language.

Verified against live pricing pages·30 Aug 2026·How we test

Vague inputs produce vague outputs. For customer support teams using AI, the difference between a helpful, on-brand response and a generic, ticket-creating one is the quality of the prompt. Freeform requests like “write a reply” leave too much to chance.

Structured prompts, with clear variables, context, and constraints, are the foundation of scalable AI support. They ensure consistency, reduce hallucinations, and allow agents to work faster. This is the core skill for professionals in the AI in customer experience field.

At ZEKAI, we review tools independently. Our ranking criteria for these prompts are simple:

  1. Clarity & Specificity: Does the prompt leave room for ambiguity?
  2. Adaptability: Can it be easily modified with variables?
  3. Vendor Mapping: Can it be mapped to a real-world helpdesk workflow?
  4. Compliance Awareness: Does it account for real-world legal and brand risk?

This is a library of 25 copy-paste prompts, tested against current large language models as of September 2026. Each includes a JSON object, making them easy to integrate into your helpdesk’s macros or internal tools.

Why Structured Prompts Beat Freeform Requests

A structured prompt acts as a detailed brief for your AI assistant. By providing placeholders, defining the desired tone, and specifying constraints (like length or format), you guide the AI toward the single best response, not just one of many possible responses. This reduces editing time and, more importantly, minimizes the risk of the AI inventing policies or making promises your company can’t keep.

**$650+ CAD**

Damages awarded to a customer after Air Canada’s chatbot provided incorrect information about bereavement fares, a precedent-setting case for AI liability. Source: pinsentmasons.com

The infamous *Moffatt v. Air Canada* case is a stark reminder of this risk. The airline was held liable for incorrect information provided by its support chatbot, even though the correct information was available elsewhere on its site. Structured prompts with grounded facts prevent these kinds of unforced errors.

Ticket Response & First-Contact Prompts (5 Prompts)

These prompts are for initial replies, setting expectations and gathering information efficiently.

Prompt 01 Acknowledge Receipt & Set Expectations
Draft a first-contact reply for a ticket about [TICKET_TOPIC].
1.  Acknowledge the user's specific issue: `[USER_ISSUE_SUMMARY]`.
2.  Confirm receipt of their ticket and provide the ticket ID: `[TICKET_ID]`.
3.  State our standard response time for this issue type: `[RESPONSE_TIME_SLA]`.
4.  If known, mention the specialist or team it has been routed to: `[ROUTED_TEAM]`.
5.  Keep the tone empathetic and professional. Do not promise a solution, only a follow-up.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_t1_001",
"use_case": "First Contact Reply",
"variables": ["TICKET_TOPIC", "USER_ISSUE_SUMMARY", "TICKET_ID", "RESPONSE_TIME_SLA", "ROUTED_TEAM"],
"tone": "empathetic, professional",
"constraints": "Do not promise a solution."
}
Tested on Claude, ChatGPT and Gemini
Prompt 02 Request More Information (Politely)
The user's request about `[TICKET_TOPIC]` is missing key information.
Draft a polite reply that:
1.  Thanks them for their message.
2.  Clearly states the specific information we need to proceed. List these as bullet points:
*   `[REQUIRED_INFO_1]`
*   `[REQUIRED_INFO_2]`
*   `[REQUIRED_INFO_3]`
3.  Explains briefly *why* we need this information (e.g., "to locate your account," "to replicate the error").
4.  Assures them their ticket will be prioritized once the information is received.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_t1_002",
"use_case": "Information Request",
"variables": ["TICKET_TOPIC", "REQUIRED_INFO_1", "REQUIRED_INFO_2", "REQUIRED_INFO_3"],
"tone": "helpful, clear",
"constraints": "Explain the 'why' behind the request."
}
Tested on Claude, ChatGPT and Gemini
Prompt 03 Answer a
Generate a step-by-step guide answering the user's question: `[USER_QUESTION]`.
The user is on the `[USER_PLAN_LEVEL]` plan.
1.  Start with a direct confirmation: "Yes, you can do that. Here are the steps:"
2.  Use a numbered list for the steps.
3.  Reference specific UI elements by name (e.g., "Click on 'Settings' in the main dashboard").
4.  If available, link to a relevant knowledge base article: `[KB_ARTICLE_URL]`.
5.  End with an invitation to ask follow-up questions.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_t1_003",
"use_case": "How-To Guide",
"variables": ["USER_QUESTION", "USER_PLAN_LEVEL", "KB_ARTICLE_URL"],
"tone": "clear, instructional",
"constraints": "Use a numbered list."
}
Tested on Claude, ChatGPT and Gemini
Prompt 04 Proactive Check-in on a Known Issue
We have just resolved a system-wide issue: `[ISSUE_DESCRIPTION]`.
Draft a proactive message to a user who was affected by this issue.
1.  Reference the original ticket ID: `[TICKET_ID]`.
2.  Briefly state that the issue they reported should now be resolved.
3.  Ask them to confirm if things are working as expected on their end.
4.  Provide a direct link to where they can test the fix: `[TESTING_URL]`.
5.  Thank them for their patience.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_t1_004",
"use_case": "Proactive Resolution Update",
"variables": ["ISSUE_DESCRIPTION", "TICKET_ID", "TESTING_URL"],
"tone": "proactive, helpful",
"constraints": "Do not close the ticket automatically."
}
Tested on Claude, ChatGPT and Gemini
Prompt 05 First AI Contact Disclosure (EU AI Act)
Generate a compliant first-contact message that incorporates an AI disclosure.
The user is asking about `[TICKET_TOPIC]`.
1.  Begin with a clear disclosure, such as "You're interacting with an AI assistant from [COMPANY_NAME]."
2.  Provide an immediate option to escalate to a human agent (e.g., "You can ask for a human at any time.").
3.  Then, proceed to answer the user's initial query based on the context provided.
4.  Keep the entire message concise and clear.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_t1_005",
"use_case": "Compliant AI First Contact",
"variables": ["COMPANY_NAME", "TICKET_TOPIC"],
"tone": "transparent, direct",
"constraints": "Must include disclosure and human escalation path at the start."
}
Tested on Claude, ChatGPT and Gemini

De-escalation & Empathy Prompts (5 Prompts)

When tensions are high, the right words matter. These prompts help AI draft responses that validate customer feelings without making false promises.

Prompt 06 Acknowledge Frustration & Take Ownership
The user is expressing significant frustration about `[USER_ISSUE]`. They have contacted us `[NUMBER_OF_CONTACTS]` times already.
Draft an empathetic response that:
1.  Uses phrases that validate their feelings (e.g., "I understand how frustrating this must be," "You're right to be upset.").
2.  Explicitly apologizes for the negative experience, without admitting fault for the underlying issue. Example: "I'm sorry for the trouble this has caused."
3.  Summarizes the problem in my own words to show I've understood: `[PROBLEM_SUMMARY]`.
4.  States the immediate next action I am personally taking: `[AGENT_ACTION]`.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_deescalate_001",
"use_case": "Acknowledge Frustration",
"variables": ["USER_ISSUE", "NUMBER_OF_CONTACTS", "PROBLEM_SUMMARY", "AGENT_ACTION"],
"tone": "highly empathetic, validating, accountable",
"constraints": "Apologize for the experience, not for the root cause unless confirmed."
}
Tested on Claude, ChatGPT and Gemini
Prompt 07 Rephrase a Response to Be More Empathetic
Analyze the following agent response and rewrite it to be more empathetic and less robotic.
Original Response: `[ORIGINAL_RESPONSE]`
User's situation: `[USER_SITUATION]`
Focus on:
1.  Replacing corporate jargon with plain language.
2.  Adding a sentence that acknowledges the user's emotional state (e.g., frustration, confusion).
3.  Ensuring the core message and any instructions remain accurate.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_deescalate_002",
"use_case": "Tone Polish (Empathy)",
"variables": ["ORIGINAL_RESPONSE", "USER_SITUATION"],
"tone": "empathetic, human",
"constraints": "Do not change the factual content of the original response."
}
Tested on Claude, ChatGPT and Gemini
Prompt 08 Deliver Bad News (e.g., Feature Not Available)
Draft a reply informing a user that the feature they are requesting, `[REQUESTED_FEATURE]`, is not currently available.
1.  Start with empathy and validation ("That's a great idea," or "I can see how that would be useful.").
2.  State clearly but gently that the feature doesn't exist today.
3.  Offer a viable workaround if one exists: `[WORKAROUND_STEPS]`. If no workaround exists, state that clearly.
4.  Explain that you are officially logging their request with the product team. Mention their feedback is valuable.
5.  Do not give a timeline or promise it will be built.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_deescalate_003",
"use_case": "Deliver Bad News (Feature Request)",
"variables": ["REQUESTED_FEATURE", "WORKAROUND_STEPS"],
"tone": "empathetic, honest, helpful",
"constraints": "Do not promise a future implementation or provide a timeline."
}
Tested on Claude, ChatGPT and Gemini
Prompt 09 Respond to a Complaint About a Previous Interaction
The user is complaining about a poor experience with a previous support agent or interaction. Their reference is `[PREVIOUS_TICKET_ID]`.
Draft a response that:
1.  Apologizes for the previous experience not meeting their expectations.
2.  Does not blame the previous agent. Focus on the user's experience.
3.  Takes ownership of the issue now. ("I've taken ownership of this ticket to see it through.")
4.  Asks for a brief summary of the unresolved issue to ensure you have the full context, without making them repeat everything.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_deescalate_004",
"use_case": "Service Recovery",
"variables": ["PREVIOUS_TICKET_ID"],
"tone": "accountable, reassuring",
"constraints": "Do not assign blame to other agents."
}
Tested on Claude, ChatGPT and Gemini
Prompt 10 The
The user's messages are becoming angry, capitalized, and non-constructive.
Draft a short, firm, and professional "reset" message.
1.  Acknowledge their frustration directly.
2.  State your goal: "My goal is to solve this for you, but I need your help to do that."
3.  Reset the conversation by asking one, clear, specific question that will move the issue forward. Example: "To proceed, can you please provide me with the invoice number from your confirmation email?"
4.  Avoid emotional language. Be a calm anchor.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_deescalate_005",
"use_case": "Conversation Reset",
"variables": [],
"tone": "calm, firm, professional",
"constraints": "Be direct and focus on the single next step."
}
Tested on Claude, ChatGPT and Gemini

Refund, Billing & Policy Exception Prompts (4 Prompts)

Money is a sensitive topic. These prompts ensure clarity and adherence to policy.

Prompt 11 Explain a Charge Clearly
A user is questioning a charge of `[CHARGE_AMOUNT]` on `[CHARGE_DATE]`.
Draft a clear explanation.
1.  Reference the specific invoice or order number: `[INVOICE_ID]`.
2.  Break down the charge into line items from the invoice (e.g., "Subscription to Pro Plan: $XX," "Overage fees: $Y").
3.  Link to the relevant terms of service or pricing page that explains this charge: `[POLICY_URL]`.
4.  Use simple, direct language. Avoid accounting jargon.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_billing_001",
"use_case": "Explain Charge",
"variables": ["CHARGE_AMOUNT", "CHARGE_DATE", "INVOICE_ID", "POLICY_URL"],
"tone": "factual, clear, transparent",
"constraints": "Reference specific line items."
}
Tested on Claude, ChatGPT and Gemini
Prompt 12 Process a Refund According to Policy
The user is eligible for a refund for `[PRODUCT/SERVICE]` according to our policy.
Draft a message confirming the refund.
1.  State clearly that the refund has been processed.
2.  Specify the amount being refunded: `[REFUND_AMOUNT]`.
3.  Inform them how long it will take for the funds to appear in their account (e.g., "5-10 business days").
4.  Mention the original transaction ID for their records: `[TRANSACTION_ID]`.
5.  End on a positive and helpful note.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_billing_002",
"use_case": "Process Refund",
"variables": ["PRODUCT/SERVICE", "REFUND_AMOUNT", "TRANSACTION_ID"],
"tone": "helpful, efficient",
"constraints": "Be specific about the amount and timeline."
}
Tested on Claude, ChatGPT and Gemini
Prompt 13 Deny a Refund Request (Out of Policy)
A user is requesting a refund for `[PRODUCT/SERVICE]`, but their request is outside of our refund policy because `[REASON_FOR_DENIAL]`.
Draft a firm but empathetic denial.
1.  Acknowledge their request and show you've reviewed it.
2.  State clearly that the request falls outside of the refund policy.
3.  Briefly and neutrally explain the specific policy rule that applies (e.g., "Refunds are only available within 30 days of purchase.").
4.  Link to the public refund policy page: `[POLICY_URL]`.
5.  If possible, offer an alternative, such as a discount on a future purchase or a plan downgrade. `[ALTERNATIVE_OFFER]`. Do not offer this if none is appropriate.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_billing_003",
"use_case": "Deny Refund",
"variables": ["PRODUCT/SERVICE", "REASON_FOR_DENIAL", "POLICY_URL", "ALTERNATIVE_OFFER"],
"tone": "firm, empathetic, clear",
"constraints": "Do not apologize for the policy. State it as a fact."
}
Tested on Claude, ChatGPT and Gemini
Prompt 14 Grant a One-Time Policy Exception
As a manager, I have approved a one-time exception to our policy for this user regarding `[POLICY_ISSUE]`.
Draft a message that communicates this clearly.
1.  State that you've reviewed their specific situation.
2.  Clearly state that you are making a *one-time exception*.
3.  Explain the outcome of the exception (e.g., "we have issued a full refund," "we have extended your trial").
4.  Gently reiterate the standard policy to manage future expectations.
5.  Use a positive, "happy to help" tone.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_billing_004",
"use_case": "Policy Exception",
"variables": ["POLICY_ISSUE"],
"tone": "gracious, clear",
"constraints": "Must use the phrase 'one-time exception'."
}
Tested on Claude, ChatGPT and Gemini

Knowledge Base & FAQ Generation Prompts (4 Prompts)

Turn support conversations into self-service assets.

Prompt 15 Summarize a Ticket into a Q&A Pair
Analyze the following support ticket transcript and summarize it into a single Question & Answer pair for our FAQ.
Transcript: `[TICKET_TRANSCRIPT]`
1.  **Question:** Phrase the user's core problem as a clear, searchable question.
2.  **Answer:** Write a concise, step-by-step answer that resolves the question, based on the final resolution in the ticket.
3.  Remove all personally identifiable information (PII).
4.  The final output should be in plain language, not a story of the ticket.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_kb_001",
"use_case": "Ticket to FAQ",
"variables": ["TICKET_TRANSCRIPT"],
"tone": "instructional, clear",
"constraints": "Output must be a single Q&A pair. No PII."
}
Tested on Claude, ChatGPT and Gemini
Prompt 16 Identify Gaps in the Knowledge Base
Analyze these 5 support tickets. Identify a common theme or question that is NOT answered by our current knowledge base articles.
Ticket 1: `[TICKET_1_SUMMARY]`
Ticket 2: `[TICKET_2_SUMMARY]`
Ticket 3: `[TICKET_3_SUMMARY]`
Ticket 4: `[TICKET_4_SUMMARY]`
Ticket 5: `[TICKET_5_SUMMARY]`
Current KB Titles: `[KB_TITLES_LIST]`
Output a single sentence describing the knowledge gap. Example: "We do not have an article explaining how to integrate with the new X API version."
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_kb_002",
"use_case": "KB Gap Analysis",
"variables": ["[TICKET_SUMMARIES]", "[KB_TITLES_LIST]"],
"tone": "analytical",
"constraints": "Output a single sentence."
}
Tested on Claude, ChatGPT and Gemini
Prompt 17 Draft a New Knowledge Base Article
Draft a new knowledge base article based on the following information.
**Topic:** `[ARTICLE_TOPIC]`
**Target Audience:** `[AUDIENCE_DESCRIPTION]` (e.g., "New users," "Developers")
**Key Steps/Information to Include:**
*   `[POINT_1]`
*   `[POINT_2]`
*   `[POINT_3]`
**Structure:**
1.  **Title:** A clear, action-oriented title.
2.  **Introduction:** A one-sentence summary of what the article helps the user do.
3.  **Prerequisites:** A bulleted list of anything the user needs before starting.
4.  **Steps:** A numbered list with clear instructions.
5.  **Troubleshooting/FAQ:** A small section with 1-2 common problems and their solutions.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_kb_003",
"use_case": "Draft KB Article",
"variables": ["ARTICLE_TOPIC", "AUDIENCE_DESCRIPTION", "[POINTS]"],
"tone": "instructional, structured",
"constraints": "Follow the specified structure exactly."
}
Tested on Claude, ChatGPT and Gemini
Prompt 18 Improve an Existing KB Article for SEO
Rewrite the following knowledge base article to be more discoverable by search engines and easier for users to scan.
**Original Article Text:** `[ARTICLE_TEXT]`
**Primary Keyword:** `[KEYWORD]`
**Instructions:**
1.  Ensure the primary keyword is in the title (H1) and at least one subheading (H2).
2.  Break long paragraphs into shorter ones.
3.  Use bullet points or numbered lists where appropriate.
4.  Add a "TL;DR" or "In this article" summary at the top.
5.  Bold key terms for scannability.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_kb_004",
"use_case": "KB SEO & Readability",
"variables": ["ARTICLE_TEXT", "KEYWORD"],
"tone": "clear, scannable",
"constraints": "Improve structure without changing the core meaning."
}
Tested on Claude, ChatGPT and Gemini

Agent QA, Coaching & Training Prompts (4 Prompts)

Use AI to score interactions and generate training materials.

Prompt 19 Score a Ticket Against a QA Rubric
Score the agent's performance in the following ticket transcript against our QA rubric. Provide a score from 1-5 for each category and a brief justification.
**Transcript:** `[TICKET_TRANSCRIPT]`
**QA Rubric:**
1.  **Opening:** Was it personalized and prompt?
2.  **Problem Identification:** Did the agent correctly identify the user's true problem?
3.  **Tone & Empathy:** Was the tone appropriate and empathetic?
4.  **Solution Quality:** Was the solution accurate and well-explained?
5.  **Closing:** Was the closing clear and did it confirm resolution?
Output in a markdown table format.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_qa_001",
"use_case": "Ticket Scoring",
"variables": ["TICKET_TRANSCRIPT"],
"tone": "analytical, objective",
"constraints": "Output as a markdown table with scores and justifications."
}
Tested on Claude, ChatGPT and Gemini
Prompt 20 Identify a Coaching Opportunity
Review the following agent interaction. Identify the single biggest coaching opportunity for the agent.
**Transcript:** `[TICKET_TRANSCRIPT]`
Focus on behaviors, not personality. Frame the opportunity constructively.
Example Output: "The agent could have de-escalated the situation more effectively by validating the customer's frustration upfront before jumping to a solution."
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_qa_002",
"use_case": "Identify Coaching Opportunity",
"variables": ["TICKET_TRANSCRIPT"],
"tone": "constructive, analytical",
"constraints": "Identify one primary opportunity."
}
Tested on Claude, ChatGPT and Gemini
Prompt 21 Generate a Role-Playing Scenario
Based on the difficult ticket below, create a role-playing scenario for a training session.
**Difficult Ticket Summary:** `[TICKET_SUMMARY]`
**Scenario Output:**
1.  **Customer Persona:** A brief description of the customer (e.g., "Frustrated, non-technical, has tried to fix it twice already").
2.  **Opening Statement:** The exact sentence the "customer" should use to start the role-play.
3.  **The "Twist":** The hidden piece of information or misunderstanding the agent needs to uncover.
4.  **Desired Outcome:** What a successful resolution looks like.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_qa_003",
"use_case": "Generate Training Scenario",
"variables": ["TICKET_SUMMARY"],
"tone": "creative, instructional",
"constraints": "Follow the 4-part scenario structure."
}
Tested on Claude, ChatGPT and Gemini
Prompt 22 Create a
Create a multiple-choice quiz question based on this ambiguous support ticket.
**Ticket Summary:** `[TICKET_SUMMARY]`
**Instructions:**
1.  Pose a "What is the best next step?" question.
2.  Provide four options:
*   A - The perfect, by-the-book answer.
*   B - A plausible but incorrect answer.
*   C - A common but inefficient answer.
*   D - An answer that violates policy.
3.  Indicate the correct answer and provide a brief explanation for why it's the best choice and the others are wrong.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_qa_004",
"use_case": "Create Quiz Question",
"variables": ["TICKET_SUMMARY"],
"tone": "educational",
"constraints": "Provide 4 distinct options and a detailed explanation."
}
Tested on Claude, ChatGPT and Gemini

Escalation & Compliance-Sensitive Prompts (3 Prompts)

These prompts help manage risk, both legal and reputational.

**August 2, 2026**

The enforcement date for Article 50 of the EU AI Act, which mandates that users must be informed they are interacting with an AI system. Source: iapp.org

Prompt 23 Summarize for Human Escalation
Prepare a concise summary of this conversation for escalation to a human agent. The agent is busy and needs to understand the situation in under 15 seconds.
**Conversation Transcript:** `[CONVERSATION_TRANSCRIPT]`
**Summary must include:**
1.  **User:** `[USER_NAME_OR_ID]`
2.  **Issue:** A one-sentence summary of the problem.
3.  **History:** What has been tried so far (e.g., "AI suggested clearing cache, user says it didn't work").
4.  **User's Emotional State:** (e.g., "Calm," "Frustrated," "Confused").
5.  **Specific Question to Resolve:** The exact question the human needs to answer.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_escalation_001",
"use_case": "Escalation Summary",
"variables": ["CONVERSATION_TRANSCRIPT", "USER_NAME_OR_ID"],
"tone": "concise, factual",
"constraints": "Maximum 75 words."
}
Tested on Claude, ChatGPT and Gemini
Prompt 24 Flag Potentially Legally Sensitive Language
Analyze the following draft response for any language that could be considered a promise, guarantee, admission of fault, or legally binding statement.
**Draft Response:** `[DRAFT_RESPONSE]`
If sensitive language is found, identify the specific phrase and suggest a safer alternative.
Example Output:
- **Phrase:** "I guarantee this will fix your problem."
- **Risk:** Creates a promise we may not be able to keep.
- **Suggestion:** "This is the recommended next step and it resolves the issue for most users."
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_escalation_002",
"use_case": "Legal Language Scan",
"variables": ["DRAFT_RESPONSE"],
"tone": "analytical, risk-averse",
"constraints": "Identify phrase, risk, and suggestion."
}
Tested on Claude, ChatGPT and Gemini
Prompt 25 Redact PII from a Transcript for Bug Reports
Review the following customer conversation and redact all Personally Identifiable Information (PII) before it is sent to engineering as part of a bug report.
**Original Transcript:** `[ORIGINAL_TRANSCRIPT]`
**PII to redact:**
- Names
- Email addresses
- Phone numbers
- Physical addresses
- IP addresses
- Account numbers or user IDs
Replace each piece of PII with a placeholder like `[REDACTED_EMAIL]` or `[REDACTED_NAME]`. Preserve the rest of the conversation's content and structure.
```
**JSON Metadata:**
```json
{
"prompt_id": "cs_escalation_003",
"use_case": "PII Redaction",
"variables": ["ORIGINAL_TRANSCRIPT"],
"tone": "neutral, technical",
"constraints": "Only redact PII; leave all other text intact."
}
Tested on Claude, ChatGPT and Gemini

Which Tools Run These Natively?

While these prompts can be used with any general-purpose AI like ChatGPT or Claude, their real power comes from integrating them into your helpdesk. As of September 2026, the major platforms have different approaches to prompt automation.

9.0/10

Intercom Fin

Best for autonomous resolution, but pricing is per-outcome, not per-prompt.

Best for autonomous resolution, but pricing is per-outcome, not per-prompt.

Price from
$0.99/resolution
Free tier
verified truth: 14-day unlimited trial, then no free tier

Intercom’s Fin AI Agent is designed for autonomous resolution. You don’t “prompt” it on a per-ticket basis; you train it on your knowledge base and define workflows. The prompts here are most useful for building the *content* Fin uses or for agents using the AI Copilot features. As of September 2026, Fin costs $0.99 per successful resolution on top of seat licenses.

8.0/10

Zendesk AI

Powerful for agent-assist and custom bots, but AI is a pricey add-on.

Powerful for agent-assist and custom bots, but AI is a pricey add-on.

Price from
$50/agent/mo + overage
Free tier
verified truth: Small allowance per plan, then paid.

Zendesk offers a suite of AI tools, including an AI Agent for automation and Copilot features for human agents. These prompts are ideal for creating macros that agents can use with the Copilot to draft replies, summarize tickets, or change tone. The Advanced AI add-on costs around $50/agent/month, and automated resolutions are billed separately above a small allowance.

8.0/10

Gorgias AI

Unbeatable for Shopify automation, but AI is metered and can get expensive.

Unbeatable for Shopify automation, but AI is metered and can get expensive.

Price from
$1.50/AI conversation
Free tier
verified truth: No free tier for AI features.

Gorgias shines in e-commerce, particularly for Shopify stores. Its AI can take action (like checking order status or processing returns) directly. The prompts for billing, refunds, and specific product questions are a natural fit. Gorgias’s AI is billed per automated conversation, which some sources report as $1.50 on top of the ticket-based helpdesk plan.

Prompt CategoryBest Fit: Intercom FinBest Fit: Zendesk AIBest Fit: Gorgias AI
First Contact & DisclosureNatively handled by Fin’s greeting workflows.Excellent for building compliant macros for agents.Good, can be built into automated flows.
De-escalation & EmpathyAgent-assist only; Fin is not designed for this.Strongest fit; perfect for Copilot tone-polishing.Agent-assist only.
Billing & RefundsCan handle if workflows are defined.Good for drafting agent replies.Excellent. Natively understands order data.
Knowledge Base GenerationFin’s core function is using the KB, not writing it.Strong use case for summarizing tickets.Good for generating FAQs from Shopify-related tickets.
QA & CoachingNot a primary function.Strongest fit for scoring tickets and training.Possible, but not a core feature.
Escalation & ComplianceNatively handles escalation paths.Excellent for PII redaction and escalation summaries.Good for PII redaction in e-commerce context.

Swipe the table sideways →

IN Tool review Intercom — read our full review Pricing, free tier and where it falls short ZE Tool review Zendesk — read our full review Pricing, free tier and where it falls short

Building Your Team’s Prompt Library

Don’t let this page be the only place your prompts live. The most effective support teams build and maintain a shared prompt library inside their internal documentation or helpdesk.

  1. Start Small: Pick the 5 most common, repetitive ticket types and build a perfect prompt for each.
  2. Use a Naming Convention: A system like cs_[use_case]_[version] (e.g., cs_refund_denial_002) makes prompts easy to find and update.
  3. Review and Iterate: Once a month, review the prompts that are used most often. Are they still producing great results? Can they be improved?
  4. Track Performance: If your tools allow, track metrics like “time to first response” or “one-touch resolutions” for tickets that used a standard prompt versus those that didn’t. The data will justify the time spent.

An investment in a high-quality prompt library pays dividends in agent efficiency, customer satisfaction, and risk reduction. For teams serious about leveraging AI in their support workflows, it’s no longer optional. Learn more about scaling your team at our AI for Customer Support Profession Hub.

How do you write a good customer service AI prompt?

A good prompt is specific, provides context, and sets constraints. Include the user’s issue, define the desired tone, specify the output format (like a list or table), and tell the AI what *not* to do (e.g., “do not promise a timeline”). Using bracketed variables for personalization helps create reusable templates.

What are ChatGPT prompts for customer service?

These are instructions given to models like ChatGPT to generate responses for support scenarios. They can range from drafting a simple welcome email to writing a complex de-escalation message. For professional use, prompts should include variables for ticket details, specify a professional tone, and reference company policy to avoid generic or incorrect answers.

Can AI generate automated responses for customer support?

Yes. AI platforms like Intercom Fin and Zendesk AI can generate automated responses. Simpler systems use keyword triggers, while advanced AI agents use natural language understanding to interpret the user’s intent, pull answers from a knowledge base, and even resolve the ticket without human intervention.

How do you use Zendesk AI prompts?

In Zendesk, prompts are most effective when saved as macros for agents to use with AI Copilot features. An agent can apply a macro that contains a structured prompt to a ticket, and the AI will help draft a response, summarize the conversation, or change the tone, which the agent can then review and send.

How do you use Intercom Fin prompts?

Intercom Fin is designed for full automation, so you don’t typically use “prompts” on a per-ticket basis. Instead, you train Fin on your knowledge base and set up workflows. The prompts in this guide are best used to create the high-quality, structured content that Fin relies on to provide accurate answers.

Does the EU AI Act apply to customer support chatbots?

Yes. As of August 2, 2026, Article 50 of the EU AI Act requires that users must be clearly informed when they are interacting with an AI system, unless it is obvious. This applies to customer support chatbots and voice bots that serve users within the European Union.

Are companies liable for what their AI chatbots say?

Yes, increasingly so. The 2024 case of *Moffatt v. Air Canada* set a precedent where the company was held liable for its chatbot providing incorrect policy information to a customer, even though the correct information was elsewhere on the website. This highlights the importance of ensuring AI-provided information is accurate.

Sources (21)
  1. https://gaicc.org/blog/ai-chatbot-governance-article-50/
  2. https://disclosed.sh/learn/law/eu
  3. https://www.americanbar.org/groups/business_law/resources/business-law-today/2024-february/bc-tribunal-confirms-companies-remain-liable-information-provided-ai-chatbot/
  4. https://www.getmyai.ai/blog/eu-ai-act-ai-chatbots-guide/
  5. https://www.mccarthy.ca/en/insights/blogs/techlex/moffatt-v-air-canada-misrepresentation-ai-chatbot
  6. https://data-en-maatschappij.ai/en/publications/canada-moffatt-v-air-canada-bccrt
  7. https://kla.digital/blog/eu-ai-act-article-50-checklist-chatbots-copilots-ai-agents
  8. https://secureprivacy.ai/blog/eu-ai-act-article-50-transparency-obligations-for-chatbots-and-deepfakes-2026
  9. https://www.gartner.com/en/newsroom/press-releases/2026-02-03-gartner-predicts-half-of-companies-that-cut-customer-service-staff-due-to-ai-will-rehire-by-2027
  10. https://www.pinsentmasons.com/out-law/news/air-canada-chatbot-case-highlights-ai-liability-risks
  11. https://www.litigate.com/whose-responsibility-is-it-anyway-chatbots-and-legal-issues-in-moffatt-v-air-canada/pdf
  12. https://www.dragapp.com/blog/gorgias-pricing/
  13. https://www.intercom.com/learning-center/best-help-desk-software
  14. https://www.sparrowdesk.com/blogs/intercom-pricing
  15. https://istarsoft.com/guides/intercom-fin-seat-outcomes-monthly-annual/
  16. https://aicustomerservice.cc/tools/gorgias
  17. https://www.eesel.ai/blog/zendesk-support-pricing-explained-in-2026
  18. https://sensbot.ai/compare/sensbot-vs-gorgias/
  19. https://www.sparrowdesk.com/blogs/zendesk-pricing
  20. https://www.amio.io/blog/zendesk-chat-review-2026-features-alternatives
  21. https://cxsupport.crayon.com/hc/en-us/articles/38828897217693-Zendesk-Product-Update-September-2026-Relationship-Fields-AI-Translations-and-Audio-Comments

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This article is provided for general information only and does not constitute professional advice. Facts, product details, and figures were accurate to the best of our knowledge at the time of publication and may have changed since. Zekai is an independent publisher and is not affiliated with the companies mentioned. Spotted an error? See our Corrections & Removal Policy.
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