Practical PR
From Message Makers to System Builders:
How Generative AI Is Reshaping the Communications Role
By Patrick Mogge
Technology is evolving at a pace where tools used today can quickly be surpassed by new products or competitors. For school districts, that reality creates both pressure and opportunity. The question is no longer whether generative AI will change how educational organizations communicate and operate — it already has, as it is baked into the tools and platforms districts use for general communications and pedagogical practices. The more important question is whether communications teams are positioned to lead that change or simply respond to it.
Communications teams sit in a particularly strong position within this shift. Instead of serving only as message creators, teams can partner with technology, teaching and learning, research, and operations groups, and others to build systems that improve how work happens. Automation can streamline routine communications processes, AI tools can help cross-check content and ensure consistency, and generative platforms can serve as thought partners that help develop, test, and refine ideas before they are shared publicly. In this way, communications professionals become connectors between systems, helping translate complex work into clear information while also helping design smarter workflows.
But realizing that potential requires more than access to tools; it requires a culture that creates space for experimentation, curiosity, and iteration. Progress increasingly comes from prototyping ideas, testing approaches, failing forward, and refining solutions based on what is learned along the way, and that culture is also changing who can build solutions in the first place. Platforms that use natural language interfaces allow users to design workflows, analyze data, and generate functional code simply by describing what they want to build, opening participation in the creation of digital solutions to people at every level of an organization.
Across organizations of all shapes and sizes, people are identifying workflow problems, describing solutions in plain language, and developing functional tools without a programming background, a development budget, or a request in an IT queue. Those closest to the work are often better positioned than any outside developer to design something that actually fits. Generative AI makes that possible by allowing staff to act as problem solvers and builders, using natural language to describe what they need and iterating toward a working solution. The result is faster problem solving, tools tailored to how a specific team actually works, and staff who develop a deeper understanding of the processes they are improving. The barrier between identifying a problem and building a solution has never been lower.
Many platforms now allow organizations to go further, building customized AI assistants trained on their own content, policies, and workflows. Rather than relying on a general-purpose tool, teams can create purpose-built assistants that understand their organization’s specific language, priorities, and processes. A district might build one assistant to help staff navigate human resources policies, train staff to access a custom assistant in a generative AI platform to support communications drafting or editing in a consistent voice, and purchase another to answer common questions from families on its website in the form of a custom chatbot that scrapes the content of the website to generate relevant responses. These are often not off-the-shelf solutions, and if they are, they can be tailored to the organization’s specific needs. Many of these are tools shaped by the people who know the work best, and they get more useful as they are refined over time.
Informal experimentation matters in ways that are easy to underestimate. Individuals often explore emerging tools on their own time outside of work, learning and bringing new ideas and practices back into the system. Educators, staff members, and administrators who take the initiative to test tools, learn new approaches, and share their experiences often help their organizations adapt more quickly. Continuous learning has become a necessity, not a luxury, as professionals in all fields seek to keep pace with rapidly changing technologies and platforms, and the fast-paced race of generative AI companies to bring newer iterations of their large language models to market.
The productivity gains are already becoming clear inside and outside of education. Tasks that once required significant manual effort, such as reviewing or analyzing communications, organizing information, summarizing reports, and checking work, can now be completed much more quickly. Time saved on repetitive work can be redirected toward higher-value activities, such as strategic thinking, collaboration, and creative problem-solving. Rather than replacing professional expertise, these new tools allow people to focus more energy on the human-centered aspects of their work and complement their thinking.
Education and the communications profession have experienced earlier versions of this shift before. Tools such as spellcheck, grammar check, and search engines represented early forms of AI assistance that helped people write more effectively and access information more quickly. Generative platforms build on that foundation by allowing users to access vast knowledge networks and co-create ideas with technology in real time. These are tools that will continue to grow and evolve to complement the tasks and skills of individuals across various professions and to lead to breakthroughs we can’t yet imagine in all fields, from education to science to law.
Policy and governance frameworks surrounding AI in public education are still taking shape at the state and national level, but districts need not start from scratch. Many existing policies already address the underlying principles at play, including data privacy, acceptable use, and staff conduct, and those frameworks can often be applied to AI-related use cases with targeted updates rather than wholesale revision. An effective approach establishes a working framework that builds on existing policy, fills meaningful gaps, and includes a regular review cycle so the document evolves alongside the tools.
Board members are well-positioned to lead that work by drawing a clear line between student-facing and staff-facing AI use, since the privacy obligations and appropriate guardrails differ significantly between the two. The board’s governance role is to set expectations, ask informed questions, and ensure that administrative teams have the clarity they need to move forward responsibly.
National polling released in March of 2026 by NBC News showed that a majority of the public says the risks of AI outweigh its benefits. Communications leaders have the opportunity to showcase how these tools can have a potential positive impact. Generative AI is not simply another tool for producing content, as it represents an evolving ecosystem that supports experimentation, accelerates learning, and enables teams to rethink how problems are solved across organizations. Used thoughtfully, these tools expand human capability rather than replace it, helping educators and professionals move faster, think more broadly, and bring new knowledge and ideas into the communities they serve.
The opportunity for educational organizations is real. So is the responsibility. Both belong to the people doing the work.
Patrick Mogge is a communications and community engagement professional who holds a master’s degree in public policy from the University of Chicago as well as a master’s degree in school business management from Northern Illinois University. He is also licensed to teach and as a Chief School Business Official in the State of Illinois.