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From Buzz to Business: The Race for Generative AI Integration

AI is here to stay, and institutions that refrain from hopping onboard and implementing tools into their work and learning processes will fall behind those that make it a priority.

Over the last few months, Coursera and 2U announced their AI-powered advising and tutoring bots, followed by Anthology and Instructure announcing new generative AI tools that will be integrated into Blackboard and CANVAS, respectively. Similarly, generative AI is being woven into software applications across all industries—with tangible consequences. As a developer in one of Silicon Valley’s tech giants explained to me recently: “The apps I was developing over the past year—I knew exactly which of my colleagues were going to get laid off when they went live.” So, as a leader in Continuing Education, how much of your time, attention and resources should you allocate to generative AI?

The Bigger Picture Matters

The World Economic Forum Jobs Report 2023 estimates that most recent technological advances, notably generative AI, will eliminate 83 million jobs by 2028 as part of a major labor market churn, creating a need for courses and programs that will allow millions of professionals to upskill or reskill and land one of the 69 million new jobs being created. While these numbers are comparatively conservative, they are already of such scale that most Continuing Education institutions would not nearly have the systems and capacity to accommodate them.

However, because companies like Google, Microsoft and Databricks anticipated the need, employ most subject matter experts in the field and have the systems to provide capacity, they have already created free courses and programs that provide the necessary skills and competences to find new jobs—at scale. Even more involved, Stability AI just announced the integration of a Teacher AI into its new StableCode application, allowing customers to learn coding while using it.

These advancements mean that many traditional Continuing Education institutions have already missed the Generative AI train before even deciding whether they want to take it seriously. It matters because Generative AI is one of several incredibly advanced technologies propelling our current Industrial Revolution. Just imagine what labor market churn we can expect in 2033, when the first artificial general intelligence (AGI) is launched on a quantum computer powered by fusion energy through superconducting transmission lines.

Then consider what our economy and society will look like when these technologies are combined with the latest robots and nanorobots, as well as advanced capabilities to genetically engineered animals, plants and even humans. Put together, it looks like the technological advancements over the last two decades were but a prelude to what is to come. So, if you feel your institution, faculty and staff had a hard time adapting to online and remote education, generative AI is probably a great excuse for everyone to take a step back and consider the bigger picture.

Facing the Competition

An Industrial Revolution is an economic extinction event in which disruptive technology becomes available so quickly that some early adopters manage to become hyper-competitive and take over large portions of the market. By setting new productivity, innovation, quality and service standards, they attract consumers away from organizations that stick with traditional technology. In Continuing Education, we know of examples like Duolingo, which grew its stock price by over 10% since it announced its GPT4-powered conversational AI in March 2023, and Coursera, which acquired 25% more monthly users since announcing its suite of generative AI tools in April 2023.

Even in traditional higher education institutions, systematic and organization-wide engagement in innovation during an industrial revolution proves beneficial, as Arizona State University (ASU) demonstrates with its 5 to 8% annual growth in enrollments and its ability to create university-wide engagement with generative AI. Now, Ivy League institutions like Harvard are openly leaning into generative AI to create more access to their courses, as are other reputable universities across the globe, making this technology a sign of quality, innovation and inclusiveness.

The good news is that most Continuing Education institutions have faculty, academics, instructional designers, advisors and administrators with deep subject matter expertise and years of experience. If offered appropriate training, guidance and ample opportunity to experiment and collaborate, they can capitalize on their expertise to engage effectively with the generative AI tools that will become available throughout the coming months in most software applications. By investing in a team of generative AI developers, your institution can quickly become a trailblazer, unleashing the potential of your faculty and staff across the institution and allowing them to strategically develop leading-edge solutions and new standards themselves.

Adopting New Standards

Embracing generative AI across an entire institution opens radically new opportunities to provide more equitable access to education, and it can help close the skills gap. For example, with AI-powered learning assistants and advisors, every student can enjoy the benefits of personalized tutoring and advising. When used for course development and delivery, generative AI offers the option to dynamically adapt the lectures and learning materials to the tone, voice and code of different communities and even switch between languages.

At the same time, strategic engagement across the organization allows institutions to maintain academic integrity. For example, to mitigate the risk of course developers secretly using generative AI tools to create online courses, they need to be used to create the complete a course before bringing in subject matter experts to review and improve it. Similarly, unless the academic administration is guiding the appropriate use of generative AI tools in the classroom, academic integrity is at risk.

To better appreciate the new standards that will drive competition as well as the opportunities arising from a strategic and holistic approach to generative AI, let’s consider just a few applications in development. Note that this is not an exhaustive list, that many applications are still experimental and that, in all cases, compliance with data protection and other relevant laws is paramount.

1. New Standards for Course Delivery

AI learning assistants

Khan Academy’s learning assistant, Khanmigo, will become available through CANVAS, offering personalized tutoring for each student. Alternatives are, for example, the learning assistant bot from Juji, or services like GPT-trainer. For live lectures, Class is planning on catering to students’ different learning styles and language skills by offering an AI learning assistant that can transcribe in real time, summarize what has been said and provide more detailed explanations and information on demand.

Talking textbook

Using the LangChain framework, for example, or services like GPT-trainer, textbooks can be turned into an interactive chatbot, capable of having robust conversations with students and teach its content to them in a personalized manner.

AI auto-grader

Coursera plans to use generative AI to improve auto-grading. And individual institutions using the LangChain framework, for example, or commercial services like GPT-trainer, can create their own auto-grader bots using course materials and examples of faculty feedback on old assignments.

2. New standards for instructional design

AI course developer

Anthology Blackboard and are two examples of learning management systems (LMS) that allow instructors to use generative AI to create a course outline and, in the case of, even complete online courses including all texts, readings, assignments, case studies, quizzes and exams.

Faculty avatar

Using applications like Synthesio or, for example, faculty can collaborate with instructional design teams to replace themselves with their avatar for recorded lectures, which greatly cuts down on production, post-production and maintenance time and cost.

Course review and maintenance

Using large language models (LLM) like Claude AI that allow uploads of larger files, instructional designers can semi-automate textbook updates and maintenance audits of online courses. They can also reduce the amount of racial and gender bias in existing course materials by having an LLM review them, taking the role of renowned experts and scholars on racism and gender studies, for example.

Personalized voice over PowerPoint (VOPP) lectures

Using ChatGPT, Bard or Claude AI, for example, course developers can create complete slide decks and the script for every slide as a baseline for faculty to review. In addition, institutions that value inclusiveness will be able to offer students the option to individually choose from an array of virtual instructor avatars to deliver their VOPPs in a tone, voice and code that matches their preference.

3. New Standards for Student Services

AI student recruiter and advisor

Companies like 2U, for example, already announced the development of advisor bots that provide more personalized advising based on student profiles and course data across their client base. These bots will only become more effective as institutions drive systems integration to provide access to more data.

Student service bot

Using the LangChain framework, for example, commercial bots like Juji or services like GPT-trainer, institutions can create chatbots that understand student requests, as well as their emotional state, and accurately answer their questions with information traditionally found on the institutional website and associated PDFs—and all of that in multiple languages.

Career counseling and interview training

Career centers can inform students of the many existing applications that specialize in resume reviewing and interview preparation or provide them with specifically designed prompts students can use in ChatGPT, Bard or Claude, for example, to have their resume and cover letter reviewed and optimized for every individual position they would like to apply to, in addition to being able to run complete mock interviews.

Beyond these early adoption cases, there are multiple disruptions happening in the fields of marketing, customer relationship management and sales, which are bound to impact student recruitment and engagement. 2U, for example, has announced a recruitment advisor bot, while Hubspot is releasing AI content generator tools, and services like OXOLO allow marketing teams to create video advertisements in minutes based on program or course webpages. And we have not even mentioned AI-powered applications under development for IT services, HR, accounting, facilities management and others.

In sum, unless your institution fully and comprehensively engages in generative AI transformation, you are likely putting yourself on the sidelines for the rollout of the next disruptive technology. Consequently, if you were wondering how much time, attention and resources you should allocate to generative AI, I would argue: everything you have.

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