ChatGPT’s impact on student learning outcomes: a meta-analysis of 35 experimental studies - Xinning Wu, et al; Nature

The analysis included 35 studies published between 2022 and 2024, involving 4193 participants. The results indicated a moderately positive effect of ChatGPT on student learning outcomes (g = 0.670), significantly enhancing both cognitive and non-cognitive skills. In the analysis of moderating variables, the subject, experimental duration, and instructional mode had significant positive effects on student learning outcomes, whereas educational level and knowledge type did not show significant effects. Additionally, the publication bias test revealed no significant publication bias. This meta-analysis confirmed the effectiveness of ChatGPT in improving student learning outcomes and highlighted the roles of the subjects, experimental duration, and instructional mode as key moderating factors. Despite the risks of sample selection bias and limitations in fully covering the multidimensional moderating factors and higher-order thinking, the findings provided important empirical support for applying ChatGPT in education.

https://www.nature.com/articles/s41599-026-07019-z

Cloning Myself with AI: Four Ways to Multiply Faculty Presence for Graduate and Adult Learners - Sherrie Myers Bartell, Faculty Focus

Have you ever wished you could clone yourself? I have. For many faculty in graduate and adult education that longing is more than a passing thought. Balancing the multifaceted needs of students who rely on your expertise, guidance, and presence often feels impossible. While teaching realities mean we can’t be everywhere at once, AI offers practical ways to extend our reach, enabling high-touch interactions even as responsibilities multiply. Thoughtfully leveraged, these tools help orchestrate a more responsive classroom by offering prompt feedback, facilitating richer discussions, and generating tailored resources, all while preserving the essential human connection at the heart of meaningful learning.

https://www.facultyfocus.com/articles/effective-teaching-strategies/cloning-myself-with-ai-four-ways-to-multiply-faculty-presence-for-graduate-and-adult-learners/

What Comes After an MBA? Why Leaders Are Turning to AI - Boston University Virtual

The MBA is the defining credential for a generation of business leaders. It builds financial acumen, strategic thinking, and cross-functional fluency — the toolkit for managing complexity and driving organizational performance. For decades, it was the answer to the question every ambitious professional eventually asked: What’s my next move? That question is back. And for a growing number of leaders, the answer looks different than it once did. AI is not just changing the tools organizations use. It is changing how decisions get made, how processes run, who is accountable for outcomes, and what it means to lead. Business leaders with MBAs are finding themselves navigating a new kind of gap — not a lack of strategic instinct, but a lack of structured fluency in an AI-driven operating environment. And a targeted, business-focused Master’s degree in Artificial Intelligence is increasingly the credential they’re turning to.

https://www.bu.edu/online/2026/03/23/what-comes-after-an-mba-why-leaders-are-turning-to-ai/

Terafab: The World’s Next Generation Chip Factory - Thomas Frey, Futurist Speaker

On March 21st, Elon Musk introduced Terafab—a $25 billion chip facility, jointly owned by Tesla, SpaceX, and xAI—designed to produce one terawatt of compute per year. That’s fifty times the current annual output of the global AI chip industry. Terafab isn’t just about catching up with TSMC, Samsung, and Nvidia; it’s about leaping ahead—and, remarkably, off-planet. Here’s where it moves from bold to unprecedented: 80% of Terafab’s chip output isn’t meant for Earth. SpaceX plans to launch up to a million satellites, each a node in an orbital data center—powered by solar energy, cooled by space, and forming the largest computing network in history. Without Terafab’s radiation-hardened, space-optimized chips, this vision remains science fiction.

https://futuristspeaker.com/future-of-work/terafab-the-worlds-next-generation-chip-factory/

Leading disruption before it leads you - McKinsey

The riskiest disruption isn’t necessarily the one coming. It may be the one CEOs refuse to lead.Today’s leadership mandate requires more than long-term strategy. In a recent interview with McKinsey’s Eric Kutcher, IBM CEO Arvind Krishna had advice for fellow leaders: “You’ve got to be willing to ‘do’: As opposed to getting disrupted by somebody else, disrupt yourself while you still have the cash flow and clients who value your capabilities.” That same urgency runs through recent conversations with CEOs on AI. Sanofi CEO Paul Hudson has been clear that this revolution can’t be delegated to a task force or tucked neatly under “innovation.” It requires CEO ownership. Meanwhile, Citi CEO Jane Fraser has argued that the goal of AI transformation isn’t automation layered onto old workflows—but redesign from the ground up.

https://www.mckinsey.com/featured-insights/themes/leading-disruption-before-it-leads-you

University of Phoenix scholars publish study on academic applications of generative AI tools in higher education - University of Phoenix

Key findings from the study include:

• Generative AI tools are increasingly used in academic workflows, including literature review support, research brainstorming, and academic writing assistance.
• AI can improve research efficiency and idea generation, particularly for complex scholarly tasks such as synthesizing large bodies of literature. 
• Ethical and academic integrity considerations remain critical, including transparency about AI use and maintaining original scholarly analysis.
• Doctoral education may benefit from AI literacy training, helping researchers understand both the capabilities and limitations of generative AI technologies.
• Institutions may need clearer policies and guidance to support responsible AI adoption in research and teaching.

https://www.eurekalert.org/news-releases/1120763

Survey: How Should Universities Prepare for the AI Era? - Institute for the Future of Education

In January of this year, the Digital Education Council (DEC), in collaboration with Tecnológico de Monterrey, published a study it conducted with the participation of professors and students from 29 Latin American universities on the use of Artificial Intelligence (AI) in education. The results confirm a growing student adoption of AI, rising from 86% to 92%, while among teachers the growth was much greater: from 61% to 79%, an increase of 18 percentage points, compared to the 2025 global survey. Students express mature opinions on the use of AI. Although two-thirds of the students surveyed view it positively, 65% fear that its use will lead to superficial learning and discourage both critical thinking and creativity. The study indicates that students also understand the impact of this technology in the workplace: 73% expect to continue using AI in their future jobs, and their mastery of it makes them confident in their performance after graduation.

https://observatory.tec.mx/edu-news/study-how-should-universities-prepare-for-the-ai-era/

US universities pivot to AI degrees as campuses race to match the machine age - Times of India Education

Artificial intelligence has moved decisively from research corridors into the core of undergraduate education across the United States, forcing universities to redraw academic priorities with unusual speed.In the latest move, Northwestern University has announced a standalone undergraduate major in artificial intelligence, scheduled to roll out in the fall of 2026. The decision places the institution squarely within a rapidly expanding cohort of universities formalising AI as a primary field of study rather than a peripheral specialisation as reported by USA Today.The shift is not cosmetic. It signals a structural reorientation of higher education towards a technology that is already reshaping labour markets, governance frameworks, and industrial systems.

https://timesofindia.indiatimes.com/education/news/us-universities-pivot-to-ai-degrees-as-campuses-race-to-match-the-machine-age/articleshow/129698069.cms

Exploring the connections between integrated sustainable curricula, generative AI tools, and perceived climate change capabilities across the global south and north using multi-analytics - Javed Iqbal, et al; Nature

These results highlight the potential of integrated sustainable curricula and climate change sensitivity to enhance climate change capabilities. Although ANN performed comparably with multiple linear regression, fsQCA showed that the presence of any single condition (integrated sustainable curricula, climate change sensitivity, or generative AI tool usage) was sufficient to explain high levels of climate change capabilities. To the authors’ knowledge, this study is the first to measure the moderated mediation among integrated sustainable curricula, generative AI tools, and climate change sensitivity in relation to climate change capabilities within Global South and North contexts, using PLS-SEM, fsQCA, and ANN analytics. Our study also provides implications for practitioners, such as university management, curriculum policymakers and teachers, along with future research directions.

https://www.nature.com/articles/s41599-026-06895-9

How Cal State Became Ground Zero for the Fight over AI in Higher Education - Chris Mills Rodrigo, TechPolicy

 In a statement emailed to Tech Policy Policy, CSU director of media relations and public affairs Amy Bentley-Smith said the system “is focused on ensuring our universities have the tools and resources to meet this moment and lead in the educational application, preparation, and ethical and responsible use of AI.” Bentley-Smith added that access to “relevant technologies” allows faculty and staff “to work together on solutions for the benefit of our students’ education and the broader academic community.” OpenAI did not respond to a request for comment. But according to some professors, integrating AI into classrooms has not been as seamless as Cal State may have hoped for.

https://www.techpolicy.press/how-cal-state-became-ground-zero-for-the-fight-over-ai-in-higher-education/

Report Outlines Framework for University’s Engagement with AI - Alec Gallimore & Ricardo Henao, Duke Today

Following the inaugural Duke AI Summit in 2024, Provost Alec D. Gallimore launched the AI at Duke initiative and charged its steering committee with identifying opportunities for elevating the university’s leadership in AI’s development, application and responsible oversight.  The committee was co-chaired by Joseph Salem, Rita DiGiallonardo Holloway University Librarian and vice provost for library affairs; Tracy Futhey, vice president and chief information officer; and Ricardo Henao, associate professor of biostatistics and bioinformatics. Deliberating from June 2025 to January 2026, the steering committee worked closely with faculty-led advisory committees focused on four pillars – Life with AI, Advancing Discovery in the Age of AI, Sustainability in AI, and Trustworthy & Responsible AI – to develop the report.  The recommendations aim to support Duke’s core missions of research and teaching by building technical capacity for AI development while advancing applications of AI that keep humans at the forefront of innovation.  

https://today.duke.edu/2026/03/report-outlines-framework-universitys-engagement-ai

All Jobs Gone within 18 Months: Microsoft’s AI Chief Terrifying Prediction Explained - AIGrid

This podcast discusses the imminent impact of AI on the white-collar workforce, highlighting predictions from Microsoft’s AI CEO Mustafa Suleyman and Anthropic's Dario Amodei that most professional tasks could be automated within the next 12 to 18 months [00:00]. It explores the "quiet" nature of current job displacement, where data shows a significant drop in white-collar job openings since 2015 [03:22], and notes a 16% fall in employment among workers aged 22 to 25 in AI-exposed fields [11:18]. The video also covers legislative efforts to protect professions like law and medicine by banning AI from providing substantive professional advice [06:30]. The discussion further details a "chaotic" transition period predicted by Gartner, where companies may prematurely replace staff with AI only to rehire humans later due to service quality collapses [13:18]. As AI literacy becomes a formal credential, the labor market is expected to shift toward requiring "AI-free" skills assessments to verify human critical thinking [14:53]. While some firms like Klarna have already moved toward AI-first models, the podcast suggests the displacement will not be a straight line but a messy cycle of experimentation and correction [14:25]. [Summary facilitated by Gemini 3 Fast]

http://www.youtube.com/watch?v=U95Xz-U_cvE

Measuring progress toward AGI: A cognitive framework - Ryan Burnell & Oran Kelly, the Keyword, Google

Our framework draws on decades of research from psychology, neuroscience and cognitive science to develop a cognitive taxonomy. It identifies 10 key cognitive abilities that we hypothesize will be important for general intelligence in AI systems:

Perception: extracting and processing sensory information from the environment

Generation: producing outputs such as text, speech and actions

Attention: focusing cognitive resources on what matters

Learning: acquiring new knowledge through experience and instruction

Memory: storing and retrieving information over time

Reasoning: drawing valid conclusions through logical inference

Metacognition: knowledge and monitoring of one's own cognitive processes

Executive functions: planning, inhibition and cognitive flexibility

Problem solving: finding effective solutions to domain-specific problems

Social cognition: processing and interpreting social information and responding appropriately in social situations

https://blog.google/innovation-and-ai/models-and-research/google-deepmind/measuring-agi-cognitive-framework/

Sovereign AI: Building ecosystems for strategic resilience and impact - McKinsey

Sovereign AI is achievable only through an ecosystem effort that connects energy, compute, data, models, platforms, and applications across multiple actors. Sovereign AI refers to a nation’s or organization’s ability to develop and control its own AI capabilities to ensure strategic independence and alignment with domestic values and laws. That said, sovereign AI does not have a single definition; rather, it is the result of the interaction between four distinct components:

territorial: where data and compute physically reside

operational: who manages and secures data and compute

technological: who owns the underlying stack and intellectual property

legal: which jurisdiction governs access and compliance

https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/sovereign-ai-building-ecosystems-for-strategic-resilience-and-impact