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If ever there was a most important era in which we must emphasize discourse with our students, it is today. We are in the midst of major changes in our culture and society as a whole.

I have had a long tenure of teaching in higher education, beginning in 1972 at the instructor level at the University of Illinois Urbana, continuing through spring semester 2022 as a full professor and associate vice chancellor at the University of Illinois Springfield. That is one half of a century in the faculty ranks.

My field of communication technologies has been one of rapid, society-altering change. The thousands of students I engaged over those years faced rapid change in careers that shifted from analog reel-to-reel audio tape to digital video; from over-the-air broadcasting to virtual and augmented reality, and from photoshop to AI-generated videos.

Professionally, I am familiar with dealing with change. Yet, the speed of change in the recent subset of  AI enhanced technologies outpaces the speed of changes in communications fields over the past half century by light years. Nevertheless, that background of five decades of closely following and teaching communication technologies has made me acutely sensitive to the need to engage and prepare students for those changes through deep discussions probing the advanced technologies enabling change, but also the social and societal implications that surround those advances in the “real” world. There has been a non-stop evolution of technologies. For example, from manual  typewriters in the 1950s to the IBM Selectric in the 1960s, to personal computers in the 1970s such as the IBM PC/XT to the ubiquitous smartphones emerging in the 1990s. Each of these huge steps in capabilities and flexibilities came about in years. Now, however, AI technologies are improving far more rapidly. Google Gemini reports that new versions of the three frontier models of AI by Google, OpenAI and Anthropic average every one to two months:

Release Cadence Breakdown:

OpenAI Average Gap: ~32 to 45 days Details: Shifting rapidly from older generational gaps (like the long wait from GPT-4 to GPT-5), OpenAI deploys minor updates, reasoning variants (o-series), and point increments (like GPT-5.3, 5.4, 5.5) in compressed windows of roughly 6 weeks.

Anthropic Average Gap: ~51 to 96 days (3 to 4 months) Details: Maintains a steady drumbeat for the Claude family (such as Sonnet and Opus iterations), preferring deliberate updates to coding and extended-thinking capabilities rather than micro-releases.

Google (Gemini) Average Gap: ~46 days Details: Balances a slower enterprise integration pace for major Pro iterations against a frequent cadence for Flash and Flash-Lite variant drops (e.g., Gemini 3.5 and 3.6 variants).

How, then, do we prepare our learners to enter a job market where the primary tools are making huge advances two or three times within the span of a single semester? First, we, ourselves, must become AI fluent. Through professional development either at our own institution or online via short courses, we need to master the foundations. Then, we must build regular update readings into our weekly schedules. There are scores of high quality blogs, podcasts, and YouTube series designed to keep readers and viewers up to speed. For example, I publish a free and open daily reading list on “AI in Higher Education by UPCEA.”

There are several steps in the process that we should consider applying across our curricula to ensure our graduates and certificate holders are best prepared for job interviews and ensuing careers in the rapidly-changing workplace.

First, in every program, we should introduce beginning learners to the current “state of the art” in the professional field. That might best be done by including a module in the introductory level courses that involves “live” or online guest speakers from associated industries to focus on how AI and advanced computing technologies such as quantum computers are being used or are planned to be used in the coming two or three years. This can provide the baseline as a context for the following steps.

Next, in each course, we should consider an assignment or two that involves conceptualizing how the latest versions of AI and associated technologies could solve problems currently existing in the field, further efficiencies and prepare for advances in the quality and relevance of the services and products in the field. Such assignments can also build the creative and critical problem solving skills of our learners.

As the learners approach the conclusion of their course of study for the degree or certificate, we should include a module that is up to speed with the very day of delivery of the assignment. Once again, this may parallel the original foundation module by bringing in guest speakers from the field. An important part of this process may be the spin-off group discussions or projects in which actual, up-to-date topics are considered. Products of those may be put into learner portfolios to share in the job application process.

Such an approach that integrates AI throughout our contact with learners will enable us to generate an up-to-date AI fluency that will serve the learners and ultimately their employers in most effectively using the technology. Management consulting company, McKinsey observes:

Today, AI fluency is rapidly becoming the common language of work and a prerequisite for the next chapter of competitiveness. Workers’ practical ability to use and manage AI in their day-to-day, integrate it into workflows, evaluate its outputs critically, and, increasingly, create with it is transforming how work gets done. Unlike many earlier technological capabilities (such as cloud computing) that were relevant mainly to specialists, the demand for AI fluency is spreading across all types of workers, industries, and wage groups. What began as a technical skill is becoming a must-have capability for knowledge workers, blue-collar workers, managers, students, and everyday citizens.

Are you integrating AI fluency among the learning outcomes in your courses, degrees and certificates? Have you identified an effective scaffolding for such fluency that accommodates the rapidly changing context of AI in workplaces and society? What impact might you imagine if your institution fails to equip learners who are preparing to enter the workforce? Finally, how might you help lead others at your college or university to facilitate this aspect of learning for your students?

 

This column was originally published in Inside Higher Ed.