Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

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Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.

What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.

Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.

In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom. 

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

  • The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.” 

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson
Research Center in Yorktown Heights, NY
.

By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

  • Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!


Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

 

Blind Spot on AI — from the-job.beehiiv.com by Paul Fain
Office tasks are being automated now, but nobody has answers on how education and worker upskilling should change.

Students and workers will need help adjusting to a labor market that appears to be on the verge of a historic disruption as many business processes are automated. Yet job projections and policy ideas are sorely lacking.

The benefits of agentic AI are already clear for a wide range of organizations, including small nonprofits like CareerVillage. But the ability to automate a broad range of business processes means that education programs and skills training for knowledge workers will need to change. And as Chung writes in a must-read essay, we have a blind spot with predicting the impacts of agentic AI on the labor market.

“Without robust projections,” he writes, “policymakers, businesses, and educators won’t be able to come to terms with how rapidly we need to start this upskilling.”

 

You can now use Deep Research without $200 — from flexos.work


Accelerating scientific breakthroughs with an AI co-scientist — from research.google by Juraj Gottweis and Vivek Natarajan

We introduce AI co-scientist, a multi-agent AI system built with Gemini 2.0 as a virtual scientific collaborator to help scientists generate novel hypotheses and research proposals, and to accelerate the clock speed of scientific and biomedical discoveries.


Now decides next: Generating a new future — from Deloitte.com
Deloitte’s State of Generative AI in the Enterprise Quarter four report

There is a speed limit. GenAI technology continues to advance at incredible speed. However, most organizations are moving at the speed of organizations, not at the speed of technology. No matter how quickly the technology advances—or how hard the companies producing GenAI technology push—organizational change in an enterprise can only happen so fast.

Barriers are evolving. Significant barriers to scaling and value creation are still widespread across key areas. And, over the past year regulatory uncertainty and risk management have risen in organizations’ lists of concerns to address. Also, levels of trust in GenAI are still moderate for the majority of organizations. Even so, with increased customization and accuracy of models—combined with a focus on better governance— adoption of GenAI is becoming more established.

Some uses are outpacing others. Application of GenAI is further along in some business areas than in others in terms of integration, return on investment (ROI) and expectations. The IT function is most mature; cybersecurity, operations, marketing and customer service are also showing strong adoption and results. Organizations reporting higher ROI for their most scaled initiatives are broadly further along in their GenAI journeys.

 

A Code-Red Leadership Crisis: A Wake-Up Call for Talent Development — from learningguild.com by Dr. Arika Pierce Williams

This company’s experience offers three crucial lessons for other organizational leaders who may be contemplating cutting or reducing talent development investments in their 2025 budgets to focus on “growth.”

  1. Leadership development isn’t a luxury – it’s a strategic imperative…
  2. Succession planning must be an ongoing process, not a reactive measure…
  3. The cost of developing leaders is far less than the cost of not having them when you need them most…

Also from The Learning Guild, see:

5 Key EdTech Innovations to Watch — from learningguild.com by Paige Yousey

  1. AI-driven course design
  2. Hyper-personalized content curation
  3. Immersive scenario-based training
  4. Smart chatbots
  5. Wearable devices
 

Here’s why it’s so hard to change a culture — from digitaltonto.com by Greg Satell

Excerpt (emphasis DSC):

Lou Gerstner, writing about his legendary turnaround at IBM, said, “Culture isn’t just one aspect of the game, it is the game. In the end, an organization is nothing more than the collective capacity of its people to create value… What does the culture reward and punish – individual achievement or team play, risk taking or consensus building?”

Most business gurus would readily agree with that, but if you’d ask them what culture actually is they would be hard pressed to give a coherent answer. Anthropologists, on the other hand, are much more rigorous in their approach and most would agree that three essential elements of a culture are norms, rituals and behaviors.

In a positive organizational culture, norms and rituals support behaviors that honor the mission of the enterprise. Negative cultures undermine that mission. A common problem with many transformation initiatives is that they focus on designing incentives to alter behaviors. Unfortunately, unless you can shift norms and rituals, nothing is likely to change.

 

Amid explosive demand, America is running out of power — from washingtonpost.com by Evan Halper
AI and the boom in clean-tech manufacturing are pushing America’s power grid to the brink. Utilities can’t keep up.

Vast swaths of the United States are at risk of running short of power as electricity-hungry data centers and clean-technology factories proliferate around the country, leaving utilities and regulators grasping for credible plans to expand the nation’s creaking power grid.

A major factor behind the skyrocketing demand is the rapid innovation in artificial intelligence, which is driving the construction of large warehouses of computing infrastructure that require exponentially more power than traditional data centers. AI is also part of a huge scale-up of cloud computing. Tech firms like Amazon, Apple, Google, Meta and Microsoft are scouring the nation for sites for new data centers, and many lesser-known firms are also on the hunt.


The Obscene Energy Demands of A.I. — from newyorker.com by Elizabeth Kolbert
How can the world reach net zero if it keeps inventing new ways to consume energy?

“There’s a fundamental mismatch between this technology and environmental sustainability,” de Vries said. Recently, the world’s most prominent A.I. cheerleader, Sam Altman, the C.E.O. of OpenAI, voiced similar concerns, albeit with a different spin. “I think we still don’t appreciate the energy needs of this technology,” Altman said at a public appearance in Davos. He didn’t see how these needs could be met, he went on, “without a breakthrough.” He added, “We need fusion or we need, like, radically cheaper solar plus storage, or something, at massive scale—like, a scale that no one is really planning for.”


A generative AI reset: Rewiring to turn potential into value in 2024 — from mckinsey.com by Eric Lamarre, Alex Singla, Alexander Sukharevsky, and Rodney Zemmel; via Philippa Hardman
The generative AI payoff may only come when companies do deeper organizational surgery on their business.

  • Figure out where gen AI copilots can give you a real competitive advantage
  • Upskill the talent you have but be clear about the gen-AI-specific skills you need
  • Form a centralized team to establish standards that enable responsible scaling
  • Set up the technology architecture to scale
  • Ensure data quality and focus on unstructured data to fuel your models
  • Build trust and reusability to drive adoption and scale

AI Prompt Engineering Is Dead Long live AI prompt engineering — from spectrum.ieee.org

Since ChatGPT dropped in the fall of 2022, everyone and their donkey has tried their hand at prompt engineering—finding a clever way to phrase your query to a large language model (LLM) or AI art or video generator to get the best results or sidestep protections. The Internet is replete with prompt-engineering guides, cheat sheets, and advice threads to help you get the most out of an LLM.

However, new research suggests that prompt engineering is best done by the model itself, and not by a human engineer. This has cast doubt on prompt engineering’s future—and increased suspicions that a fair portion of prompt-engineering jobs may be a passing fad, at least as the field is currently imagined.


What the birth of the spreadsheet teaches us about generative AI — from timharford.com by Tim Harford; via Sam DeBrule

There is one very clear parallel between the digital spreadsheet and generative AI: both are computer apps that collapse time. A task that might have taken hours or days can suddenly be completed in seconds. So accept for a moment the premise that the digital spreadsheet has something to teach us about generative AI. What lessons should we absorb?

It’s that pace of change that gives me pause. Ethan Mollick, author of the forthcoming book Co-Intelligence, tells me “if progress on generative AI stops now, the spreadsheet is not a bad analogy”. We’d get some dramatic shifts in the workplace, a technology that broadly empowers workers and creates good new jobs, and everything would be fine. But is it going to stop any time soon? Mollick doubts that, and so do I.


 

 

6 work and workplace trends to watch in 2024 — from weforum.org by Kate Whiting; via Melanie Booth on LinkedIn

Excerpts (emphasis DSC):

The world of work is changing fast.

By 2027, businesses predict that almost half (44%) of workers’ core skills will be disrupted.

Technology is moving faster than companies can design and scale up their training programmes, found the World Economic Forum’s Future of Jobs Report.

The Forum’s Global Risks Report 2024 found that “lack of economic opportunity” ranked as one of the top 10 biggest risks among risk experts over the next two years.

5. Skills will become even more important
With 23% of jobs expected to change in the next five years, according to the Future of Jobs Report, millions of people will need to move between declining and growing jobs.

 

Learners’ Edition: AI-powered Coaching, Professional Certifications + Inspiring conversations about mastering your learning & speaking skills

Learners’ Edition: AI-powered Coaching, Professional Certifications + Inspiring conversations about mastering your learning & speaking skills — from linkedin.com by Tomer Cohen

Excerpts:

1. Your own AI-powered coaching
Learners can go into LinkedIn Learning and ask a question or explain a challenge they are currently facing at work (we’re focusing on areas within Leadership and Management to start). AI-powered coaching will pull from the collective knowledge of our expansive LinkedIn Learning library and, instantaneously, offer advice, examples, or feedback that is personalized to the learner’s skills, job, and career goals.

What makes us so excited about this launch is we can now take everything we as LinkedIn know about people’s careers and how they navigate them and help accelerate them with AI.

3. Learn exactly what you need to know for your next job
When looking for a new job, it’s often the time we think about refreshing our LinkedIn profiles. It’s also a time we can refresh our skills. And with skill sets for jobs having changed by 25% since 2015 – with the number expected to increase by 65% by 2030– keeping our skills a step ahead is one of the most important things we can do to stand out.

There are a couple of ways we’re making it easier to learn exactly what you need to know for your next job:

When you set a job alert, in addition to being notified about open jobs, we’ll recommend learning courses and Professional Certificate offerings to help you build the skills needed for that role.

When you view a job, we recommend specific courses to help you build the required skills. If you have LinkedIn Learning access through your company or as part of a Premium subscription, you can follow the skills for the job, that way we can let you know when we launch new courses for those skills and recommend you content on LinkedIn that better aligns to your career goals.


2024 Edtech Predictions from Edtech Insiders — from edtechinsiders.substack.com by Alex Sarlin, Ben Kornell, and Sarah Morin
Omni-modal AI, edtech funding prospects, higher ed wake up calls, focus on career training, and more!

Alex: I talked to the 360 Learning folks at one point and they had this really interesting epiphany, which is basically that it’s been almost impossible for every individual company in the past to create a hierarchy of skills and a hierarchy of positions and actually organize what it looks like for people to move around and upskill within the company and get to new paths.

Until now. AI actually can do this very well. It can take not only job description data, but it can take actual performance data. It can actually look at what people do on a daily basis and back fit that to training, create automatic training based on it.

From DSC:
I appreciated how they addressed K-12, higher ed, and the workforce all in one posting. Nice work. We don’t need siloes. We need more overall design thinking re: our learning ecosystems — as well as more collaborations. We need more on-ramps and pathways in a person’s learning/career journey.

 

Expanding Bard’s understanding of YouTube videos — via AI Valley

  • What: We’re taking the first steps in Bard’s ability to understand YouTube videos. For example, if you’re looking for videos on how to make olive oil cake, you can now also ask how many eggs the recipe in the first video requires.
  • Why: We’ve heard you want deeper engagement with YouTube videos. So we’re expanding the YouTube Extension to understand some video content so you can have a richer conversation with Bard about it.

Reshaping the tree: rebuilding organizations for AI — from oneusefulthing.org by Ethan Mollick
Technological change brings organizational change.

I am not sure who said it first, but there are only two ways to react to exponential change: too early or too late. Today’s AIs are flawed and limited in many ways. While that restricts what AI can do, the capabilities of AI are increasing exponentially, both in terms of the models themselves and the tools these models can use. It might seem too early to consider changing an organization to accommodate AI, but I think that there is a strong possibility that it will quickly become too late.

From DSC:
Readers of this blog have seen the following graphic for several years now, but there is no question that we are in a time of exponential change. One would have had an increasingly hard time arguing the opposite of this perspective during that time.

 


 



Nvidia’s revenue triples as AI chip boom continues — from cnbc.com by Jordan Novet; via GSV

KEY POINTS

  • Nvidia’s results surpassed analysts’ projections for revenue and income in the fiscal fourth quarter.
  • Demand for Nvidia’s graphics processing units has been exceeding supply, thanks to the rise of generative artificial intelligence.
  • Nvidia announced the GH200 GPU during the quarter.

Here’s how the company did, compared to the consensus among analysts surveyed by LSEG, formerly known as Refinitiv:

  • Earnings: $4.02 per share, adjusted, vs. $3.37 per share expected
  • Revenue: $18.12 billion, vs. $16.18 billion expected

Nvidia’s revenue grew 206% year over year during the quarter ending Oct. 29, according to a statement. Net income, at $9.24 billion, or $3.71 per share, was up from $680 million, or 27 cents per share, in the same quarter a year ago.



 

From DSC: If this is true, how will we meet this type of demand?!?

RESKILLING NEEDED FOR 40% OF WORKFORCE BECAUSE OF AI, REPORT FROM IBM SAYS — from staffingindustry.com; via GSV

Generative AI will require skills upgrades for workers, according to a report from IBM based on a survey of executives from around the world. One finding: Business leaders say 40% of their workforces will need to reskill as AI and automation are implemented over the next three years. That could translate to 1.4 billion people in the global workforce who require upskilling, according to the company.

 

 

What new grads can expect as they enter the working world — from mckinsey.com by Patrick Guggenberger, Dana Maor, Michael Park, and Patrick Simon

Excerpt:

May 21, 2023 It’s officially the season of caps, gowns, and stoles—and new grads are gearing up for entry into the world of work at a time when organizations are undergoing massive shifts. “The shifts include complex questions about how to organize for speed to shore up resilience, find the right balance between in-person and remote work models, address employees’ declining mental health, and build new institutional capabilities at a time of rapid technological change, among others,” write Patrick Guggenberger, Dana Maor, Michael Park, and Patrick Simon in a new report. These changes have significant implications for structures, processes, and people. How can new grads set themselves up for success in a quickly evolving environment? If you’re a soon-to-be new grad or know one, check out our newly refreshed special collection for insights and interviews on topics including productivity, hybrid work models, worker preferences, tech trends, and much more.


On a somewhat relevant posting (it has to do with career development as well), also see:

From Basic to Brand: How to Build and Use a Purposeful LinkedIn Profile — from er.educause.edu by Ryan MacTaggart and Laurie Burruss
Developing a professional brand helps higher education professionals establish meaningful work-related connections and build credibility in their area of expertise.


 

Leaders who practice foresight stay ahead of the innovation curve — from tfsx.com

Excerpt (emphasis DSC):

According to famed futurist Richard Slaughter, foresight (also known as futures thinking or futuring) is “the ability to create and maintain a high-quality, coherent and functional forward view, and to use the insights arising in useful organizational ways.”2 In other words, foresight is a way to examine the paths the future might take, using qualitative and quantitative metrics, and then use the insights gained from this analysis to navigate our uncertain and changing world with purpose.

“The art and science of futuring is fast becoming a necessary skill, where we read signals, see trends and ruthlessly test our own assumptions…Like the ability to make a budget or think critically, it’s a skill that anyone who has to make long-range decisions should, and can, acquire.”3

From DSC:
The development of these futuring skills needs to begin in K-12 and continue into vocational programs as well as in college.


Also relevant/see:

The future isn’t what it used to be: Here’s how strategic foresight can help — from weforum.org

Excerpt (emphasis DSC):

  • Three-quarters (75%) of organizations are not prepared for the pace of change in and around their industry.
  • Across sectors, we all need to rethink how we operate to both survive and thrive in the future.
  • Foresight can help individuals and organizations be more future prepared, innovative and agile.

The exponential pace of change

 

Deloitte State of AI Report 2022 calls out underachievers — from venturebeat.com by Sharon Goldman

Excerpt:

Deloitte released the fifth edition of its State of AI in the Enterprise research report today, which surveyed more than 2,600 global executives on how businesses and industries are deploying and scaling artificial intelligence (AI) projects.

Most notably, the Deloitte report found that while AI continues to move tantalizingly closer to the core of the enterprise – 94% of business leaders agree that AI is critical to success over the next five years – for some, outcomes seem to be lagging.

What is a surprise, she added, is how quickly the AI landscape is changing – to the point that what began as an every-other-year Deloitte report is now created annually. 

From DSC:
I’m reminded of some graphics here…

 

Also relevant/see:

‘State of AI in the Enterprise’ Fifth Edition Uncovers Four Key Actions to Maximize AI Value — from deloitte.com
Research reveals the key actions leaders can take to accelerate AI outcomes

Key takeaways

For Deloitte’s “State of AI in the Enterprise,” Fifth Edition, we surveyed 2,620 global business leaders representing six industry areas and dozens of sectors. Key findings include:

  • Ninety-four percent of business leaders surveyed agree that AI is critical to success over the next five years.
  • Seventy-nine percent of leaders say they have fully deployed three or more AI applications, compared to 62% last year.
  • There was a 29% increase in the number of respondents self-identifying as “underachievers,” suggesting that many organizations are struggling to achieve meaningful AI outcomes.
  • Top challenges associated with scaling according to respondents are managing AI-related risk (50%), lack of executive commitment (50%), lack of maintenance and post launch support (50%).
 

Communicating the Value of Foresight — from futurist.com by Nikolas Badminton

Excerpt:

After seven years each company’s maturity was measured and it was the vigilant companies – the ones that integrated foresight with their strategic practices – that were ‘33 per cent more profitable than companies on average. In addition, these vigilant companies have achieved a 200 per cent higher growth rate than the average company.’

 
© 2025 | Daniel Christian