40+ AI prompt examples for different department use cases in an organization

An AI prompt example is a specific, well-structured instruction that tells a tool like ChatGPT, Claude, or Glean Assistant exactly what to do. For instance, "Draft a 200-word product launch email for our premium plan." Good prompts give the model a role, context, and a clear output format. This article provides 40+ ready-to-use prompts organized by department, plus a quick framework for writing your own.

Table of contents

1. How to write an effective AI prompt
2. AI prompts for marketing
3. AI prompts for human resources
4. AI prompts for customer service
5. AI prompts for finance
6. AI prompts for sales
7. AI prompts for operations
8. Advanced prompting techniques
9. Frequently asked questions

How to write an effective AI prompt

The best prompts share a simple pattern. Before copying the examples below, understand the structure so you can adapt them to any situation:

1. Assign a role. Tell the model who it should be: "Act as a financial analyst" or "You are an HR manager."
2. Give context. Describe the situation, audience, or constraints: "Our company sells B2B software to mid-market retailers."
3. Be specific about the task. Say exactly what you want: "Summarize the Q3 earnings call in 150 words."
4. Specify the output format. Request a bullet list, table, paragraph, or tone: "Use a friendly, professional tone."
5. Iterate. Review the first response, then refine: "Make it shorter" or "Add a call-to-action."

These principles apply whether you're prompting a public LLM or Glean Assistant, which grounds answers in your company's knowledge and returns permission-aware, cited responses. With Glean's enterprise search, the context you would normally paste in is already available through the Enterprise Graph.

AI prompts for marketing

Marketing teams generate content, run campaigns, and make data-driven decisions. AI can automate these tasks and spark creativity.

a) Content creation

• Prompt: "Generate a 500-word blog post about the benefits of using AI in content marketing for SaaS companies."
• Outcome: AI produces an engaging blog post with SEO-optimized content, reducing the content creation cycle.

b) Social media posts

• Prompt: "Write a series of five tweets promoting our upcoming webinar on 'Future of AI in Business.' Include relevant hashtags."
• Outcome: The AI generates a creative, cohesive set of tweets that engage the audience and drive webinar registrations.

c) Email campaigns

• Prompt: "Draft an email announcing a 20% discount on our premium services. Highlight the limited-time offer and include a call-to-action for early bird sign-ups."
• Outcome: An AI-generated email template that marketing teams can quickly personalize and distribute.

d) SEO optimization

• Prompt: "Provide keyword-rich meta descriptions for our new blog post about cloud security trends in 2024."
• Outcome: AI delivers SEO-optimized meta descriptions, improving search engine rankings and online visibility.

Glean tie-in: Glean Assistant can run these marketing prompts against your brand guidelines and past campaigns, producing grounded, on-brand drafts without copy-pasting context.

AI prompts for human resources (HR)

HR departments handle recruitment, employee engagement, performance management, and compliance. AI streamlines these processes.

a) Job descriptions

• Prompt: "Create a detailed job description for a senior-level HR manager role. Include responsibilities, qualifications, and company culture."
• Outcome: A detailed job description that attracts top talent, aligned with company values and goals.

b) Candidate screening

• Prompt: "Summarize the strengths and weaknesses of the following candidate based on their resume: [insert resume text]."
• Outcome: AI analyzes resumes and highlights key attributes, helping HR teams make faster, data-driven hiring decisions.

c) Employee surveys

• Prompt: "Create a survey to assess employee satisfaction and gather feedback on remote working conditions."
• Outcome: AI generates a well-structured survey, enabling HR to collect insights into employee well-being and engagement.

d) Performance reviews

• Prompt: "Generate constructive feedback for an employee who consistently meets deadlines but needs improvement in team collaboration."
• Outcome: AI provides personalized feedback that managers can use in performance reviews.

Glean tie-in: HR teams use Glean Assistant to keep employee FAQs current and answer policy questions from permission-aware company knowledge, no manual updates required.

AI prompts for customer service

Customer service teams handle a variety of inquiries that require quick, accurate responses. AI automates responses and improves customer experience.

a) Frequently asked questions (FAQs)

• Prompt: "Provide a list of answers to common customer questions about the features and pricing of our product."
• Outcome: AI drafts accurate, informative answers that can be used in FAQ sections.

b) Complaint resolution

• Prompt: "Generate a polite response to a customer complaint about a delayed product shipment. Offer a discount on their next order as a token of apology."
• Outcome: AI generates empathetic and professional responses, helping maintain positive customer relationships.

c) Customer feedback summaries

• Prompt: "Summarize customer feedback on our latest product update. Highlight any recurring issues or praise."
• Outcome: AI analyzes large volumes of customer feedback, providing a clear, concise summary that teams can act on.

d) Chatbot scripts

• Prompt: "Create a chatbot script that guides customers through the process of resetting their password."
• Outcome: AI-generated scripts enable self-service, freeing human agents to focus on complex inquiries.

Glean tie-in: Glean Agents draft grounded support responses from your help center and past tickets, citing sources so agents can verify before sending.

AI prompts for finance

Finance departments handle data analysis, budgeting, forecasting, and compliance management. AI enhances decision-making and automates routine tasks.

a) Financial reporting

• Prompt: "Summarize our quarterly financial performance, focusing on revenue growth and cost reductions."
• Outcome: AI generates a well-organized financial summary that executives can present to stakeholders.

b) Budget forecasting

• Prompt: "Generate a budget forecast for the next fiscal year based on the following historical data: [insert data]."
• Outcome: AI provides accurate projections, helping finance teams plan and allocate resources.

c) Expense analysis

• Prompt: "Analyze company expenses over the last six months and identify areas where cost reductions can be made."
• Outcome: AI identifies spending patterns, helping finance teams pinpoint cost-cutting opportunities.

d) Compliance reports

• Prompt: "Generate a compliance report detailing how our company adheres to financial regulations in the SaaS industry."
• Outcome: AI assists in creating detailed, regulatory-compliant reports, reducing the manual documentation burden.

Glean tie-in: Glean returns cited, permission-aware answers from finance documents, so summaries trace back to source files and respect access controls.

AI prompts for sales

Sales teams rely on data, communication, and persuasion to close deals. AI enhances lead generation, outreach, and deal management.

a) Lead qualification

• Prompt: "Summarize the key characteristics of a qualified lead based on the following customer profile data: [insert data]."
• Outcome: AI helps sales teams identify high-value leads by analyzing customer data and suggesting prospects with the highest conversion potential.

b) Sales pitch writing

• Prompt: "Write a personalized sales email to a prospective client in the retail industry, highlighting how our AI-driven analytics platform can improve their operational efficiency."
• Outcome: AI generates compelling sales pitches that reps can tailor to individual prospects.

c) Deal pipeline insights

• Prompt: "Provide insights into our sales pipeline and identify any deals at risk of stalling."
• Outcome: AI helps sales teams identify bottlenecks, enabling them to prioritize deals that require immediate attention.

d) Proposal writing

• Prompt: "Create a proposal template for a new SaaS product we're pitching to a medium-sized business. Focus on features, benefits, and pricing."
• Outcome: AI generates a professional proposal, helping sales teams save time while maintaining quality.

Glean tie-in: Glean surfaces CRM data and enablement content in the rep's workflow, so these prompts run on real account context rather than generic assumptions.

AI prompts for operations

Operations departments handle supply chain management, process optimization, and logistics. AI enhances efficiency and automates workflows.

a) Process optimization

• Prompt: "Analyze the following operational data and suggest ways to improve production efficiency in our manufacturing process: [insert data]."
• Outcome: AI generates data-driven suggestions for optimizing workflows and reducing bottlenecks.

b) Inventory management

• Prompt: "Provide an analysis of current inventory levels and suggest when and how much of each product we should reorder."
• Outcome: AI maintains optimal inventory levels, reducing the risk of overstock or stockouts.

c) Supplier management

• Prompt: "Generate a list of potential suppliers for raw materials, including pros and cons of each option."
• Outcome: AI compiles a list of vetted suppliers, enabling informed sourcing decisions.

d) Risk management

• Prompt: "Summarize the potential risks in our supply chain and provide mitigation strategies."
• Outcome: AI identifies supply chain vulnerabilities and suggests contingency plans.

Glean tie-in: Glean Agents automate recurring operations workflows and trigger actions with enterprise-grade governance, from inventory alerts to vendor report generation.

Advanced prompting techniques

Once you've mastered the basics, three techniques can improve your results:

• Role prompting: Start with "Act as a [role]…" to shape the model's perspective. Example: "Act as a financial advisor reviewing a client's portfolio."
• Few-shot prompting: Give one or two input-output examples before your request so the model follows the pattern. Example: "Input: 'The product broke after one week.' Output: 'Negative.' Now classify: 'Shipping was faster than expected.'"
• Chain-of-thought prompting: Ask the model to reason step by step before answering. Example: "Think step by step and calculate the ROI of this marketing campaign."

For a curated set of prompts you can use right away, explore Glean's Prompt Library, organized by role and task so you can start generating value immediately.

Frequently asked questions

What is an AI prompt example?

An AI prompt example is a sample instruction you give to a language model to get a specific output. For instance, "Write three subject lines for an email announcing a product launch" tells the model exactly what format and topic you need.

What makes a good AI prompt?

A good prompt assigns a role, provides context, states the task clearly, and specifies the output format. The more specific you are, the closer the output matches your intent.

What are some common AI prompts for work?

Common work prompts fall into four categories: summarize (meeting notes, documents), draft (emails, proposals), analyze (data, feedback), and brainstorm (ideas, strategies). The department-specific examples above cover all four.

What is chain-of-thought prompting?

Chain-of-thought prompting asks the model to reason step by step before giving a final answer. This technique improves accuracy for math, logic, and multi-step analysis tasks.

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