AI is Not Just a Tool
In less than two years Adobe Firefly users have produced more than twenty-two billion images, vectors, videos, and audio tracks. That volume isn’t a gimmick; it is a live stress-test proving that generative models can shoulder ideation, variation, and polish at industrial scale. Runway’s Gen-3 and Gen-4 models now do the same for moving pictures, turning storyboard text into serviceable footage in minutes, and they are already finding homes in commercial film pipelines. Figma’s new Make feature goes further: describe a prototype and the system delivers working interaction code on the spot. These leaps don’t feel like plug-ins. They feel like a new operating layer that sits between imagination and execution.
Many faculty still dismiss template-driven platforms such as Canva and Adobe Express as beginner software, yet those apps now power social feeds for Fortune 500 brands and automate design tasks that once filled junior desks. Their one-click layouts, brand kits, and AI copy helpers are the new default for small businesses that cannot afford a full studio. If we ignore these tools in class, we leave graduates to face them cold in the workplace, and we reinforce the false idea that “serious” design happens only in the Adobe Creative Cloud. Showing students how to push beyond presets—how to critique template choices, adapt them to real brand systems, and layer original thinking on top—is no longer optional. It is basic career prep, because the first job many of them land will involve turning a brief into a Canva deck before lunch.
LinkedIn’s 2025 talent report shows postings that mention generative-AI skills have grown almost five-fold in a year, and the fastest-rising creative titles now blend design fluency with machine-learning literacy. The World Economic Forum’s latest Future of Jobs survey confirms the demand side: forty-one percent of employers expect to reduce roles that can be automated, yet seventy percent plan to hire specifically for AI-driven creativity and strategy—think junior designers building prompt libraries or editors refining Gen-4 rough cuts. If graduates walk into interviews without hands-on experience, the gap is ours, not theirs.
Creative teams that adopted generative co-pilots reclaimed up to sixty percent of their production hours, McKinsey found in 2024. If our assignments still reward speed or surface polish, we are grading precisely what a model can handle. Value has shifted to upstream framing, informed prompting, discriminating between iterations, and articulating why one solution solves the brief better than another. Those are judgment calls, not button presses.
This summer, those in higher ed should be rewriting rubrics while the release cycle is still predictable. Watch the most recent Adobe MAX London 2025 and Microsoft Build keynotes, skim the Figma Config recaps, track the Runway Academy to see how these tools are changing the playbook for what will soon be baseline capability, and make sure to see what Google have been quietly developing, new tools that will surely put pressure on all other companies working in the GenAI space. It is important to note that this is the worst these models will be, they will only get better over time, and that time is fast approaching. It is clear that AI is not just a tool. Anything the demos automate can leave our syllabi. Whatever remains untouched is exactly where human insight, taste, and ethics matter most.
This summer higher-ed needs to rewrite rubrics while the release cycle is still predictable. Watch the Adobe MAX London 2025 and Microsoft Build keynotes. Skim the Figma Config recap and follow the tutorials in Runway Academy to see how fast baseline capability is shifting. Keep an eye on Google releases too; their coming tools will push the whole field forward. Remember, this is the worst these models will ever be. Their improvement curve is steep and getting steeper. AI is no longer just a tool. Anything the demos already automate can leave our syllabi. Whatever remains untouched is where human insight, taste, and ethics matter most.
Calling AI “just a tool” downplays a structural shift that has already landed on students’ screens. Treat it as the new creative OS. Teach them to drive it without crashing their integrity. Update measures of success so curiosity, critical thinking, and ethical direction carry the weight once given to rote production. If we act now, next year’s assessments will fit the industry our students are entering, not the one we remember.
