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The rapid evolution of new technology is a double-edged sword for higher education. Advancements in fields such as artificial intelligence (AI) come with big promises of revolutionizing the way we teach and learn, but with a lack of funding, resources, and structural reform, technology is winning the race while educational institutions haven’t even had the chance to lace up their shoes. The red tape that leaders, administrators, educators, and students have to navigate significantly slows the adoption of new technologies, potentially leaving graduates underprepared for the demands of the modern workforce.
As an Assistant Professor specializing in communication and emerging technologies, with experience running the full gamut of careers in higher education, I have firsthand knowledge of the challenges and opportunities that technological advancements bring to academia. From watching my students experiment with ChatGPT in the classroom, to revamping 10 different programs as an administrator, and being a part of the leadership team developing new programs in AI that can (hopefully) withstand its light-speed evolution – I’ve seen my fair share of modern technological challenges. Today I’d like to take you along to highlight just a few of the challenges students and educators are currently facing and give you a better idea of what the future looks like for the new faces in your companies.
Challenge 1: The ever-moving starting line
When we think about new and emerging technology, AI is quite often the first to come to mind. Despite its recent explosion in the public sphere, AI has actually been around for quite a while with the first work being done in the 1940s and ‘50’s. Today, AI’s capabilities are expanding from simple task automation to complex decision-making processes, transforming industries and creating new opportunities. The rapid acceleration we are now seeing can be attributed to our current ecosystem, including advances in machine learning algorithms, increased computational power, big data availability, and a thriving open-source ecosystem, all supported by significant investment and global collaboration. These same resources, cross-industry collaboration, and clear capitalist benefits that attract investors are all areas where education often struggles. In education, AI can personalize learning experiences, streamline administrative tasks, provide data-driven insights to improve student outcomes, and it can even be a helpful tool for students to use in the classroom to help understand higher level concepts. However, integrating these technologies into the fabric of higher education institutions is not straightforward.
Challenge 2: Jumping the bureaucratic hurdles
One of the main challenges is the inherent rigidity of academic institutional processes. The steps required to implement changes in the way courses are designed and delivered are often bogged down by extended timelines and layers of approval that are all institution specific. For example, when ChatGPT became open to the public in November of 2022, universities had mere weeks to develop bandaid solutions for the final papers and projects that would be potentially plagiarized or just plain hallucinated (see this guide for some of the common issues with early versions of generative AI). More permanent policy solutions required committee meetings, approvals at the school, faculty, and university-wide boards each with its own set of requirements and concerns. Changes to the courses that would now be considered outdated can take up to a full academic year to implement and if the changes are large enough to impact the program requirements, they can even require approvals from government agencies. This can take months, if not years, effectively rendering the technology and policy outdated by the time it is finally adopted.
Regulatory bodies and accreditation organizations add another layer of complexity. They mandate strict standards and review cycles that can be misaligned with the rapid pace of technological innovation. While these standards are crucial for maintaining educational quality and integrity, they often do not account for the dynamic nature of new tech. Institutions are not exactly aligned with the motto of “move fast and break things.”
Challenge 3: Some races are longer than others.
In this never-ending race to the next technology, each stakeholder group has their own individual challenges and sometimes solutions – but not all are made equal.
Students: The sprint
Students are arguably the most affected by the slow pace of change on their high-stakes sprint to a future career and paying off their loans. They enter higher education institutions with the expectation that they will be equipped with the skills and knowledge needed for their future careers. However, when curricula fail to incorporate the latest technologies, students may find themselves at a disadvantage upon graduation. In fields such as data science or cybersecurity, where AI is becoming integral, outdated curricula can leave students unfamiliar with current industry practices and tools. To keep up, students often resort to self-learning through online courses, bootcamps, or personal projects, which can only further the time and financial burdens they are facing.
Educators: The relay race
Educators are in a relay race, passing the baton of knowledge while trying to keep up with the latest technological tools and methods. Each handoff represents an opportunity to integrate new technologies, (which many professors are eager to do) but institutional resistance and the need for professional development can slow their progress. The need for professional development and training on these new tools is another hurdle. Outside of the classroom time is already limited enough by pressures to publish and fulfill other academic responsibilities dependent on the institution.
Despite these challenges, some educators find creative ways to circumvent bureaucratic obstacles. For instance, faculty members may pilot new technologies in elective courses or collaborate with external partners to secure funding and support. These “loopholes” can provide valuable proof-of-concept that can eventually lead to broader institutional adoption, but require a lot of front-loading of work, costs, and time on the part of the educators themselves.
One promising development is the rise of interdisciplinary programs that combine traditional fields of study with emerging technologies. Programs in AI ethics and digital humanities are bridging the gap between technology and the social sciences, preparing students to address the complex challenges of the digital age.
Administrators: The marathon
Administrators are running a marathon, balancing the long-term vision of their institutions with the immediate need for innovation. They must ensure that their institutions remain competitive and relevant while adhering to regulatory requirements and managing ever more limited budgets. The pressure to innovate is often tempered by the need to maintain stability and avoid risks, resulting in a preference for incremental changes over transformative ones. Implementing new technologies, like a campus-wide learning management system or AI-driven student advising tools, involves significant planning, investment, and training, which can take years and further slow the pace of technological adoption. Administratively, the adoption of AI at some institutions in can also help streamline processes and reduce bureaucratic delays. AI-driven analytics can provide administrators with insights into student performance and institutional efficiency, enabling more informed decision-making and quicker responses to changing needs.
Bringing all stakeholders into the same race requires a coordinated effort. Institutions must invest in ongoing professional development for educators, ensuring they have the skills to integrate new technologies. This includes workshops, training sessions, and access to cutting-edge tools. Developing flexible curricula that can quickly adapt to technological changes is also crucial, incorporating modular course structures and project-based learning that reflect real-world applications.
Crossing the finish line: Industry collaboration to prepare students for the future
The slow pace of change in higher education significantly impacts students’ readiness for the workforce. Industries today seek graduates proficient in their fields and capable of adapting to new technologies. AI, for instance, is crucial in sectors from healthcare to finance, and employers expect new hires to have a solid grasp of these technologies. To bridge this gap, institutions are increasingly partnering with industry, offering students hands-on experience and exposure to the latest tools. However, these collaborations often face the same bureaucratic hurdles that impede broader technological adoption within academia.
Strengthening industry partnerships provides valuable resources and insights, with collaborative projects, internships, and guest lectures helping bridge the gap between academia and the workforce. Providing incentives for educators and administrators to innovate can foster a culture of experimentation, including grants for innovative teaching projects, recognition programs, and dedicated research time. Actively involving students in technological adoption processes ensures their needs are met and provides fresh perspectives, with student advisory boards or feedback mechanisms guiding institutional decisions.
Looking ahead, the role of emerging technologies in higher education will only continue to grow. Institutions that can effectively integrate these technologies into their curricula and operations will be better positioned to prepare students for the future. This will require a cultural shift within academia, embracing flexibility and innovation while maintaining the rigorous standards that define higher education. By fostering a culture of agility and collaboration, and leveraging AI and other emerging technologies, higher education can better prepare students for the demands of the modern workforce and ensure its relevance in a rapidly changing world. While integrating emerging technologies into higher education is challenging, the potential benefits make it a journey worth undertaking. The race is on, and with the right strategies, higher education can not only keep up but set the pace for the future.
