New Report: HBCUs and AI - A New Vision for Higher Education

We’re excited to release our new report in partnership with Ellucian and Huston-Tillotson University, entitled The Shift Ahead: HBCUs, Artificial Intelligence, and a New Vision for Higher Education.    This joint report explores how HBCUs are uniquely positioned to lead in the age of AI — not just adapt to it. Take a look at some of the high-level findings from the report:    • 96% of faculty and 98% of students at HBCUs already use AI tools.    • Fewer than half of institutions have formal AI adoption strategies, revealing a readiness gap.    • When deployed intentionally, AI can expand access, strengthen institutional capacity, and align learning with workforce needs. • HBCUs can model a justice-centered approach to AI for all of higher education. This data affirms that HBCUs are not behind — they’re poised to lead. Read more about how UNCF ICB and its partners are advancing responsible AI adoption across the sector.    Read the full report here: https://lnkd.in/eHbBgAyz   #HBCUs #ArtificialIntelligence #HigherEducation #DigitalInnovation #UNCFICB #TheShiftAhead 

Survey: 98% of Students, 96% of Faculty at HBCUs Adopt AI Tools Why this matters - This high level of usage demonstrates that AI is already deeply embedded in teaching, learning, and daily academic workflows at HBCUs. - It also reveals a gap: while many are using AI tools, institutional support, training, infrastructure, and formal strategies lag behind. Our take I see this as both exciting and cautionary. It’s encouraging that students and faculty are embracing AI so broadly, it could drive innovation, equity, and better learning outcomes. But without strong institutional backing (policies, ethical frameworks, infrastructure), this adoption risks being uneven, risky, or superficial. The critical challenge will be turning grassroots usage into sustainable, responsible, and inclusive transformation. What do you think? How can colleges ensure that AI adoption by students and faculty is matched by adequate support, governance, and equity, rather than just being ad hoc? Laura Ipsen Ed Smith-Lewis Melva K. Wallace, Ph.D. Read More:- https://lnkd.in/gDMjNiau #HBCU #AIinEducation #HigherEd #EdTech #AcademicAI #AIAdoption #ResponsibleAI #businessnews #businessinsights #businessinsightsjournal #BIJ

What do higher ed leaders really think about AI? More than you might expect—and more urgently than ever before. This important piece from Black Press USA surfaces perspectives from presidents, provosts, and education advocates on the front lines of integrating AI into higher ed. Their message is clear: AI must serve student success, not just institutional efficiency. And getting there requires investment, intention, and a deep focus on equity, governance, and access. At Paritii, these are the very challenges we're addressing through tools like Swyft —supporting institutions as they work to scale support systems without sacrificing care, context, or fairness. AI in higher ed isn’t a question of if—it’s a question of how, by whom, and for whom. Read the full article: https://lnkd.in/e-EeDAyW How is your campus leading—or lagging—on the responsible use of AI? Let’s share learnings ⬇️ #ParityPerspective #SwyftByParitii #AIinHigherEd #ResponsibleAI #StudentSuccess #LeadershipInTech #DigitalEquity #FutureOfLearning #TechForGood #AIandAccess

AI is rapidly reshaping higher education. This recent Nature article captures the scale of adoption millions of students using AI tools daily, and universities racing to redefine what learning means in this new context. From my experience working across innovation, AI adoption, and education, I can see both sides clearly. On one hand, AI offers unprecedented opportunities to personalize learning, enhance productivity, and bridge access gaps. On the other, it challenges us to rethink core questions about assessment, authorship, and what we actually want students to learn. The truth probably lies somewhere in between, not in resisting change, but in learning to integrate it responsibly. AI is here to stay in education. The real test now is whether institutions can evolve fast enough to turn this disruption into lasting improvement. And perhaps, as my current research explores, how prompt literacy and human–AI collaboration can help us get there. https://lnkd.in/dRzJ6bjT (The video is AI-generated, obviously, but it does a great job illustrating why something needs to happen in higher education before this becomes reality 😅 )

As AI becomes embedded in every stage of learning and research, universities face a difficult question: what remains distinctively human about higher education? This post suggests that AI doesn’t diminish universities, instead making their true value visible. The challenge now is to design learning, assessment, and scholarship that cultivate discernment, not just efficiency. https://lnkd.in/erfKMm7v

When Universities Fracture — AI Isn’t the Villain. It’s the Mirror. “Education didn’t collapse because of AI — It collapsed because it forgot to evolve before AI arrived.” The Quiet Crisis in Higher Education Across Canada — and globally — higher education is being redesigned by necessity, not vision. What used to be unthinkable is now happening, fast: Institutional Shrinkage -York University paused admissions to 18 undergraduate programs in 2025 amid a $132 M deficit. -Conestoga College cut campuses and saw a 97% drop in new international study permits this year. -Laurentian University cut 69 programs and laid off ~195 staff after declaring insolvency in 2021. -Georgian College is closing Muskoka and Orillia campuses by 2026. -Seneca Polytechnic shuttered its Markham campus. -Over 10,000 college staff have been laid off across Ontario, with 600+ programs suspended or canceled. The causes are layered — underfunding, demographic shifts, tuition freezes, and overreliance on international student revenue. But the outcome is singular: the industrial model of education is cracking. The AI Factor — Catalyst, Not Culprit -78% of Canadian students now use AI tools weekly. -Over 60% of educators use generative AI for lesson design or grading. -The global AI-in-education market is projected to grow from $5.18 B (2024) → $112 B by 2034. AI is not replacing teachers — it’s replacing systems that refuse to adapt. If AI can generate lectures, grade essays, or personalize tutoring, what remains uniquely human about education? The “Un-AI-able” Dimensions We Must Protect Let’s face it — facts and frameworks are now commodities. But these remain priceless: ✨ Ethics — knowing what should be done, not just what can be done. 💬 Context — seeing how knowledge fits into human history and identity. 🌱 Creativity — imagining beyond the dataset. 🤝 Belonging — the emotional infrastructure of learning. 🧭 Wisdom — pattern-recognition that AI can’t simulate. If the next classroom is partly algorithmic, these are the human subjects we must still teach. The Rebuild: What Comes Next From Degree to Capability: Credentials are losing monopoly power. Skills, adaptability, and real-world outcomes are the new currency. From Campus to Network: Education must decentralize — smaller hybrid nodes, cohort-based microlearning, and lifelong mentorship models. From Teaching to Curating: The new educator’s superpower: guiding students through abundance, not scarcity, of knowledge. From Institution to Ecosystem: Future learning will be built collaboratively between educators, AI, creators, and industry.

A systematic review of 30 recent studies on generative AI in K-12 education reveals both promising trends and significant research gaps that should inform every school's AI strategy. The comprehensive analysis published in Frontiers in Education shows that generative AI is predominantly being used in high school settings and STEM fields, with most research focusing on preservice teacher training rather than direct student outcomes. While enthusiasm for these tools is high across educational settings, the evidence base for their effectiveness remains surprisingly narrow. Here's what the research reveals: most studies used quasi-experimental designs that measured psychological variables like motivation and engagement rather than direct academic achievement. This means we're making implementation decisions based on how students feel about AI rather than concrete evidence of improved learning outcomes. The review emphasizes an urgent need for robust frameworks and longitudinal studies to truly gauge learning outcomes across diverse contexts and student populations. Current research is heavily skewed toward short-term interventions with limited demographic diversity. Schools can address these gaps immediately: Implement systematic data collection protocols to track both engagement and academic outcomes when using AI tools. Create diverse pilot programs that include different grade levels, not just high school. Establish partnerships with local universities to conduct longer-term studies on AI effectiveness in your specific context. Develop clear metrics that go beyond student satisfaction to measure actual learning gains. Document both successes and failures to contribute to the broader evidence base that all schools desperately need. The research calls for theory-driven integration rather than technology-driven adoption—a crucial distinction that should guide every implementation decision. Ethical considerations and equitable access must be embedded in research design from the beginning. What data are you collecting about AI effectiveness in your school? How are you measuring success beyond initial enthusiasm? #AIinEducation #EdTech #K12 #Assessment #SchoolLeadership Source: Systematic review of generative AI in K-12 education — Frontiers in Education — October 2025 — Research Team — Multiple Institutions https://lnkd.in/edGi_b-h

Artificial intelligence is transforming how we live, work, and learn, but our education systems are struggling to keep pace. Our grantee leaders like Chong-Hao Fu of Leading Educators, Cara Stillings Candal of ExcelinEd, Andrew Rotherham of Bellwether, D'Andre Weaver, Ph.D of Digital Promise, and Dacia Toll of Coursemojo will join the inaugural Think Forward Fellowship cohort launched by our grantee, Center on Reinventing Public Education. Their leadership will shape how AI can support more impactful learning ensuring all students are prepared to thrive in a data-driven world.

New tools are transforming what’s possible in learning—but without a coherent strategy, clear guardrails, or shared vision, even the most promising innovations risk deepening existing inequities. That’s why the Center on Reinventing Public Education (CRPE) has launched the Think Forward Fellowship Cohort—a new initiative bringing together leaders from across education, technology, research, and philanthropy to tackle the toughest questions about AI’s role in schools. Over the next year, Fellows will work together to:  🔹 Build a long-term vision for AI-powered learning  🔹 Design systems and infrastructure for responsible adoption  🔹 Shape communication and action strategies that move the field from fragmented experimentation toward durable transformation Read more about the fellowship and meet the inaugural cohort: https://lnkd.in/ebX-VTGT

🚀 Big news: The Center on Reinventing Public Education (CRPE) has officially launched the Think Forward Fellowship Cohort, and our CEO & Founder, Tiffany Green, NCC, LPCC, is honored to be part of it! This November, she’ll join visionary leaders in New Mexico to explore how AI can be harnessed as a tool for equity in education. 🗣️ “I’m excited to come, learn, and build alongside leaders who are reimagining how AI can be a tool of equity—and to ensure these tools are created with compassion and community at the center.” — Tiffany We’re proud to see Uprooted Academy represented in this powerful movement toward inclusive innovation. #ThinkForward #AIforEquity #UprootedAcademy #CRPE