Has your college given its academic offering an AI update?
AI is changing how people work in almost any given profession. Colleges across the U.S. are starting to move: in Florida for example, AI degrees grew from just 3 in 2022 to 30 in 2025. AI is becoming part of the higher education landscape, as it should.
But what are 30 degrees for more than 1 million higher education students in Florida? And how much can traditional two- to four-year degrees help when demand for AI specialists is skyrocketing? Colleges need to move much faster to adapt and expand AI education, with greater emphasis on shorter, practical courses that can respond quickly to employer demand.
So, how do you know whether your own institution’s education portfolio is keeping up or falling behind? This blog discusses six signs that it’s time for an AI update, what’s relevant for students, and practical ways to bring AI into your degree portfolio.
Is Your Curriculum Ready for the AI Era?
AI does not necessarily mean replacing existing degrees with entirely new ones. In many cases, it means looking at what students are already learning and asking a simple question: Does this still reflect how the job is actually done in the AI era? Here are six signs that the answer may be no.
1. You’ve never reviewed your curriculum for AI
Two or three years may not sound like a long time in higher education, but in AI, it is a very long time. New Generative AI tools emerge daily, existing tools release new versions, and everyday workplace workflows are evolving to incorporate AI and automation.
If your programs were designed before AI became accessible to everybody – or have only received minor updates since – it is worth looking again.
Think about what seemed unrealistic just a few years ago. Would you have imagined that in-depth research on a field could be carried out in minutes? That someone with no coding skills could build websites and applications in seconds? Or that people without graphic design skills could create realistic images, not to mention Hollywood-level videos? These are everyday realities with AI. If the tools and workflows have changed this much, the skills students need have changed too.
2. You’re teaching students to do manually what AI can do in seconds
Take a look at your class and home assignments. Are students spending hours producing something – a draft, a paper, a summary, a piece of code, a report – that AI can now help accomplish in seconds? The learning outcome needs to move up a level. Instead of simply teaching students to produce the output, teach them how to use AI to get there faster, evaluate what gets produced, identify mistakes, improve the result, and apply their own judgment. After all, employers won’t hire someone to do a job if AI can do it much faster and cheaper. Only people who know how to work with AI effectively bring value, with the critical thinking, creativity, context, decision-making, and human judgment that AI cannot replace – for now.
3. AI is only taught in your Computer Science department
If AI at your college is still treated exclusively as a technology subject, that is another warning sign. AI is increasingly relevant to business, marketing, finance, product management, data, design, cybersecurity, HR, healthcare, and almost any other profession. The question should therefore be, “How is AI changing the degrees we already offer?” A marketing student needs to learn how to use AI for content generation and research, while a medical student needs to understand AI-assisted prognosis and drug matching. AI literacy is relevant for any job and industry out there.
4. Employers are asking for skills your programs don’t teach
The employers that hire your graduates can give you the clearest indication. If advisory boards, hiring companies, or local businesses increasingly talk about AI, automation, data, prompt engineering, or AI-assisted workflows – but those capabilities barely appear in your curricula – there is a gap. If employers complain that your graduates are not job-ready, because they are not familiar with the AI aspects of their roles, that’s the writing on the wall. Colleges need to stay close to employers and use their feedback to identify which programs need updates and which AI skills students should actually gain and practice before entering the workforce.
5. Your students are already using AI but your curriculum and tests pretend otherwise
Here is perhaps the easiest sign to spot: your students are using AI. They do. AI use among students is nearly universal, at 92%.
And sometimes, that use is not exactly subtle. One professor caught 32 out of 35 students using AI on an exam after embedding a hidden instruction in white text telling chatbots to include the word “Madagascar.” Students who copied the question directly into AI tools submitted answers with the completely irrelevant word, revealing that they had not properly read or reviewed the AI-generated responses.
If AI only enters the classroom through conversations about cheating or what students are not allowed to do, it’s a missed opportunity. Students also need to learn how AI is useful, when it is not, how to verify its output, how to protect sensitive information, and when human judgment is needed. Employers still value human capabilities such as analytical thinking, creative thinking, leadership, resilience, and collaboration alongside growing AI and tech skills. The opportunity for colleges is therefore to teach students how to work with AI while developing the skills that remain human, at least for now.
6. Your programs may not be positioned for Workforce Pell
Workforce Pell is designed for high-quality, short-term programs that prepare students for high-skill, high-wage, or in-demand occupations and meet employer hiring needs. Eligible programs generally must provide at least 150 but fewer than 600 clock hours of instruction over at least 8 but fewer than 15 weeks, lead to a recognized postsecondary credential, and satisfy additional approval, performance, and value requirements.
That makes employer alignment more important than ever. For many occupations, employers increasingly expect graduates to understand AI tools, AI-enabled workflows, data literacy, or the responsible use of automation. If your short-term workforce programs do not reflect AI technologies and practices used in the jobs they prepare students for, that may be a sign your curriculum needs another look.
Updating programs around documented employer demand – including relevant AI skills where appropriate – can help colleges improve workforce relevance, strengthen student outcomes, and position eligible programs for potential Workforce Pell consideration. AI does not guarantee Workforce Pell eligibility, but ignoring AI-driven changes in the workplace could make a program less competitive and less aligned with employer needs.
What’s Relevant for Students in the AI Era?
Students have always lived with some uncertainty about the future. Many enter college without knowing exactly what career they want, where their degree will lead, or what their job will look like a few years after graduation. Today, that uncertainty is much greater. AI is expected to displace 92 million jobs while creating 170 million new ones, which can make students question whether what they are learning will still be relevant by the time they graduate.
The goal is to help students understand how AI is changing the industry and profession they are aiming for and what they need to learn to best prepare for the near future. Colleges should look at each degree, course, and continuing education program, and ask: What parts of this program are outdated? What job tasks related to this course are being automated? What new tasks are appearing? What new skills – technical or soft skills – are needed, given AI? And what will make our graduates more valuable at the workplace?
For example, a marketing student should no longer learn how to write copy, but rather how to use AI to generate ideas, research audiences, analyze campaign data, generate content with AI, review it manually, and then judge what is actually worth publishing. A data student should learn how AI can support data cleaning, analysis, visualization, and querying – while still understanding the data well enough to spot errors and draw the right conclusions. A software development student should know how to use AI coding assistants to build, debug, document, and test faster, while still understanding the code well enough to know when the AI is wrong.
This means colleges should think beyond adding one general “Introduction to AI” course. AI can also be integrated directly into existing subjects and assignments. Ask students to complete a task with AI, critique the result, improve it, explain what the AI got wrong, or compare an AI-assisted approach with a traditional one. That way, students learn how to think while using AI.
A useful rule for colleges is this: don’t ask only what students need to know about AI. Ask what they need to know about their profession now that AI exists. That is where the most relevant curriculum updates are to be found.
How Wawiwa Supports Colleges for the AI Era
Wawiwa is a global education provider that supports colleges, universities, and training centers across the U.S. and around the world with education solutions built for the AI era.
Wawiwa offers applied AI programs and courses designed around industry trends, employer needs, and the rapidly changing workplace. Examples include the Enterprise AI Implementation Specialist and AI Product Manager programs. Wawiwa also provides practical AI courses for professionals across a wide range of fields, including HR, finance, and marketing, helping people apply AI effectively within their specific roles. Short upskilling courses include the AI Pro Software Developer and Vibe Coding: Building Apps with AI.
Moreover, Wawiwa updates its programs and courses continuously as jobs and technology evolve. Colleges and universities don’t need to wait for curriculum changes. Every new cohort gets the latest curriculum given industry demands from graduates.
Colleges can integrate Wawiwa’s programs and courses in several ways, depending on their goals and student population. They can embed applied AI education into existing academic degrees and certificate programs; offer bespoke continuing education AI courses for alumni, lifelong learners, and working professionals; or launch career-oriented AI and tech bootcamps for students exploring new domains. This gives educational institutions the flexibility to strengthen existing degrees, expand credit, non-credit and professional education offerings, and create new career-focused learning opportunities without having to build everything from scratch.
