Practical Ways AI Can Scale Your College Marketing and Communications Work
By Brandon Moore, Ed.D.
AI will not replace your marketing and communications team. But it is can change what that team can accomplish — if you know where to apply it.
For small college and university marketing teams, the most persistent challenge is not creativity or strategy. It is capacity. There is always more work to do than time to do it. AI does not solve every capacity problem, but it is genuinely useful for the kinds of work that are time-consuming, repetitive, or structurally complex in ways that do not require deep human judgment to get right.
But first, one foundational point: follow your institutional policies on AI. Use only the tools your institution has approved, and do not expose institutional documents, student data, or sensitive organizational information to non-approved external tools. This is not a bureaucratic caution. It is a real risk that every team member working with AI needs to understand.
With that in mind, here are the practical applications I find most useful for higher education marketing and communications teams.
Create variations faster than you ever could manually
One of the most time-consuming parts of running a marketing campaign is producing variations. Different audiences need different messages. Different channels need different formats. A print advertisement is not the same as a social graphic, which is not the same as a digital display ad. Producing all of those versions from scratch, for every campaign, is genuinely difficult to keep up with at a small institution.
AI shortens that process significantly. Copy written for one audience can be quickly adapted for another — prospective students versus parents, traditional-age students versus adult learners, domestic students versus international students. A graphic designed for print can be reformatted and resized for digital and social applications. The creative thinking still comes from your team. The iteration work that follows it does not have to.
Translation is a particularly strong application here. If your institution serves students from multiple language backgrounds, or if you are recruiting in international markets, producing translated versions of marketing materials has historically been slow and expensive. Tools like Adobe Express now allow you to translate design assets directly within the platform, generating localized versions of a graphic or advertisement without rebuilding it from scratch.
A word of caution: AI translation tools have improved dramatically in recent years, but they are not perfect. Any translated content intended for formal or official use should be reviewed by a fluent speaker before it is published. The tool gets you most of the way there. A human makes sure it’s correct.
Build taxonomy and structure that would take months to do manually
Program pages are one of the most underleveraged assets on a college website. They exist, they list requirements, and then they sit there. But a well-structured program page can do much more — connecting related programs, surfacing relevant career outcomes, and helping prospective students understand how one area of study connects to another.
The challenge is that building that kind of structure across every program at an institution is an enormous amount of work. A music department might offer undergraduate and graduate degrees, performance and education tracks, and connect to career paths in performance, education, arts administration, and music therapy. Mapping all of that thoughtfully, for every program, across an entire institution, is work that rarely gets done because it is too time-consuming to prioritize.
AI was genuinely built for this kind of structured, pattern-based work. You can ask an AI tool to develop a taxonomy of related programs, associated careers, relevant skills, and connected disciplines for a given area of study. That taxonomy can then be used to tag program pages, surface related content, improve internal search, and help end users find what they are actually looking for — which is often not a specific program name, but an outcome or interest area they want to explore.
This is work that improves both the user experience and the search performance of your website. And it is work that a small team can accomplish with AI in a fraction of the time it would take to perform manually.
Let AI find patterns and problems in your existing content
Most college websites accumulate content over time without much systematic review. Pages get added, updated partially, and left in place long after they are relevant. Language becomes inconsistent across departments. Information that was accurate two years ago is now outdated. Gaps exist between what the institution wants to communicate and what the website actually says.
Finding and addressing those issues manually requires reading every page, which almost never happens.
AI can help. By providing your web pages and departmental documents to an approved AI tool, you can ask it to identify patterns, inconsistencies, gaps, and outdated information across a body of content. This is exactly the kind of indexing and pattern-recognition work that AI handles well. It is not going to make editorial judgments for you, but it will surface the issues that need your attention and give you a clearer picture of where the problems are.
This application is particularly useful before a website redesign or content audit. Rather than starting from scratch, you can use AI to do the diagnostic work and focus your team's time on the decisions and revisions that actually require human judgment.
Use AI as a starting point, not a finishing point
For many kinds of writing tasks, the hardest part is the blank page. Getting a first draft down, even a rough one, breaks the inertia and makes the revision process much faster. AI is very good at producing first drafts.
This applies to web page copy, program descriptions, event announcements, social media posts, email campaigns, and more. Give the AI tool a clear prompt, some relevant context about your institution, and the audience you are writing for. What comes back will not be publication-ready, but it will be a useful starting point that your team can shape into something that reflects your institution's voice and values.
AI is also useful for filling in knowledge gaps during the writing process. If your team is writing about a topic they are not deeply familiar with, AI can help build out background information, explain concepts, and suggest angles worth exploring.
Here is the essential caution for these applications: AI hallucinates, so be sure to verify before publishing. Facts need to be checked. Statistics need to be sourced. Claims about your institution, your programs, or your outcomes need to be confirmed by someone who actually knows whether they are accurate.
The workflow that works best is treating AI output the way you would treat a capable but junior colleague who is new to higher education. Smart, fast, and genuinely helpful — but not yet reliable enough to publish without a careful review.
A closing thought
The teams that will get the most out of AI are not the ones that hand the most work over to it. They are the ones that are thoughtful about where AI adds real value and where human judgment is irreplaceable. Iteration, structure, pattern recognition, and first drafts are strong fits. Final editorial decisions, institutional voice, and accuracy validation are not.
Used well, AI gives small marketing and communications teams the capacity to do work they simply could not have done before. That is worth investing some time and attention.
Brandon Moore, Ed.D. is a web strategy and digital marketing consultant with 15+ years of experience working with higher education institutions and mission-driven organizations. He is the founder of Speak LLC.
