Using AI at Work

• Drafting responses to common questions
• Improving clarity in instructions or guidance
• Creating consistent messaging
• Translating complex information into plain language

• Generating conceptual ideas for visuals, layouts, or multimedia assets
• Suggesting design variations based on constraints such as brand, format, or audience
• Helping translate abstract ideas or themes into concrete visual or experiential concepts
• Iterating on creative approaches quickly to explore alternatives

• Summarize meeting notes
• Identify action items
• Create meeting agendas
• Turn notes into follow‑up emails

• Create checklists or timelines
• Outline project plans
• Brainstorm options or approaches
• Organize unstructured information

• Summarize sponsor policies, compliance requirements, or regulatory guidance
• Extract key rules, constraints, or eligibility criteria from complex documents
• Assist with checking proposals against lists of required components
• Drafting initial versions of documentation or guidance on research protocols

• Assist with debugging by identifying likely causes of errors and suggesting fixes
• Translate logic or requirements into working code examples
• Refactor code to improve readability, structure, or performance
• Assist with accessibility checks, such as identifying common WCAG issues in front‑end code

• Draft emails, memos, and announcements
• Rewrite content to be more concise or clearer
• Adjust tone (professional, friendly, plain language)
• Create first drafts for web pages or FAQs

Northwestern Role: Research core administrator

Use Case: I had a spreadsheet with location data that was entered in a form. I forgot to specify the format for the location entries on the form, so it had a combination of just cities, cities and states, and just states. The entries were in different formats as well. I have a Microsoft Copilot add-on license, so I was able to have Copilot in Excel clean up the data, creating two new columns with clean city and state values.

Example Prompt: I want to clean up the location column. I need to convert it into two columns for city and state and make the formatting consistent.

Consider: Copilot, and other AI tools, make assumptions when processing data. After any data cleaning steps, ask it to be explicit about how it made any decisions and what assumptions it made. For example, in my file, it saw that most of the cities were in Illinois, so it assumed locations were in Illinois when the state was missing and the city name could be in Illinois. To follow-up on this, I asked Copilot to add a new column marking rows where it made an assumption about the state.

Northwestern Role: Research faculty

Use Case: We built a new software package as a part of a research project and wanted to create a logo for the package.

Example Prompt: Create a logo for a Python package that helps people process family tree data. The name of the package is [package name]. The logo should be inside a triangle. Use purple and green as the primary colors.

Consider: Some of the options the AI tool generated looked very similar to other logos. Make sure to check any images to make sure they aren’t copying others’ work. We didn’t have anyone on our team who felt they had the graphic design experience to create the logo, but if you do, letting a person create it may be a better choice.

Northwestern Role: Department staffer who responds to questions, provides guidance, or supports services

Use Case: When I need to respond to common questions or explain a process, AI can help draft a clear, consistent response. I’ll paste in an existing reply, instructions, or technical description and ask the tool to simplify the language or adjust the tone for a general audience. This helps me respond more efficiently while improving clarity and reducing confusion for the person receiving the information.

Example Prompt: Here’s a response I often send to people who ask about [topic]. Rewrite it so it’s clear, friendly, and easy to understand for someone who isn’t familiar with the technical details. Keep it accurate, but use plain language.

Consider: AI is helpful for clarity and consistency, but I still review everything carefully before sending. I make sure the information is correct, up to date, and appropriate for the situation. I also personalize my responses when needed so they don’t feel automated or impersonal.

Northwestern Role: Department human resources representative

Use Case: Our team uses behavioral interview questions for staff job openings. We ask each member of the interview committee to assess different skills and experience related to the job. We used to find ideas from online lists of interview questions, but AI helps us find relevant questions faster, and we can also use AI to modify the questions to fit our team or the job better.

Example Prompt: I am interviewing a candidate for a [job title] position in the [department or group name] at Northwestern. I’ve uploaded the job description. Please generate a list of 15 behavioral interview questions I can ask to assess their user support skills and experience working across teams.

Consider: AI tools can also generate lists of things to look for in candidate answers, but these are often overly general. We choose interviewers because we value their experience and judgment, and we don’t want to replace that with AI output. We don’t use AI to evaluate candidates.

Northwestern Role: Department staff with communications responsibilities

Use Case: When I’m having trouble getting started writing something, I use an AI chat tool to help me get something on the page. If I have relevant information in a different format already, I upload those documents and tell the tool what I want to write. If I don’t have anything to work from, I just start writing without worrying about grammar or getting the right tone, and then ask the AI tool to help me structure and format it into what I need. I have it ask me questions if it needs more information, which helps me fill in the details. Once I have something to work from, I can rewrite and edit.

Example Prompt: I need to write a three- to four-paragraph article on our team’s recent project on [fill in details] for our department newsletter. The audience is faculty and staff in the [department name] department at Northwestern. I’ve uploaded a document with the project summary. I want to give a high-level overview of the impact of the project. Make the tone professional but engaging. If you need additional details to write a draft, ask me.

Consider: AI writing can all sound similar after a while. You don’t want to lose your voice. I try to avoid copying and pasting large chunks of AI-generated text into my document. Seeing the output in the chat tool is enough to help me get started. I can pick and choose what I want to incorporate and put things into my own words as I write.

Northwestern Role: Manager of an IT team

Use Case: We need the tone and writing of our team’s user documentation to remain consistent even though over a dozen people are contributing to it. We have a team style guide that we used to generate a series of AI prompts team members can use to review their drafts. These cover proofreading, checks for clarity and consistency, audience alignment, and whether the tone matches a handful of characteristics.

Example Prompt: Please act as a professional senior-level copy editor and review the text in the uploaded document for spelling, grammar, and punctuation errors. Provide detailed corrections and explanations for each issue found. Specific areas to check: [fill in details].

Consider: Across different AI tools, we’ve seen them apply our guidelines too strictly. For example, when asking it to find areas where writing can be more concise, they sometimes will suggest we use a slightly shorter word just because it’s shorter. We remind the team that they need to use their judgment in evaluating the AI suggestions.

Northwestern Role: Department staffer who coordinates projects, events, or operational tasks

Use Case: When I’m juggling multiple tasks or starting a new project, I use an AI chat tool to help me organize my work. I’ll paste in notes from emails, meeting summaries, or a rough list of ideas, and ask the tool to turn that information into a checklist, timeline, or simple project plan. If I’m not sure where to start, I describe my goal and constraints and let the AI suggest an initial structure. I can then refine priorities, adjust timelines, and add context based on what I know about the work and the teams involved.

Example Prompt: I’m coordinating a small internal project that involves [brief description]. I have notes from emails and meetings, which I’ve pasted below. Help me organize this into a clear checklist with key steps and suggested timing. If you need more information to make this useful, ask me questions.

Consider: AI can help make things feel more manageable, but it doesn’t know what’s most important in my environment. I review and adjust the output to reflect real deadlines, stakeholder expectations, and dependencies. The tool gives me a starting point, not a final plan.

Northwestern Role: Web developer

Use Case: We help different groups in our school create custom websites and applications. The people we are creating a site for often want to see alternative layouts. We used to draw them, or in more formal meetings, we might mockup options using Adobe Illustrator. Now, we can build a basic layout in the framework we’re using for the project and then use a coding agent to make changes during a discussion.

Example Prompt: We ask the coding agent to get familiar with our codebase, documentation, and project plan first. We only give it access to a copy of our code so that we always have the original as a backup. When we ask it to make changes, we include both what we want to change and what should stay the same. If the outcome doesn’t match what we wanted, we have it revert to the previous code and try again.

Consider: This works well for prototyping, but once we have agreement on a direction, we rework the code ourselves. The code AI agents generate is usually well-documented and looks polished, but we’ve found that it can miss edge cases, make strange assumptions, and be organized in a way that doesn’t work with the rest of our application.

Northwestern Role: Department administrator

Use Case: We run an orientation event for students in our department and ask for their feedback afterward. The survey includes several free response questions. In the end, we need to generate a summary of the responses.

Example Prompt: The responses in the uploaded document are answers students at an orientation event gave to the question [survey question]. Can you tell me what the themes are across answers and pull out direct quotes from the responses as examples of each theme?

Consider: The first time I asked Copilot to summarize the responses was in a conversation where I had given it other information about the program and what I thought the survey responses might say. The initial summary of the responses matched closely to what I expected. When I started a new chat a few days later and asked it to summarize the responses again, the output was different. Your chat history can influence what the output is.