Investors, regulators, campus leaders, and researchers all advanced—or questioned—the role of artificial intelligence in education over the past few days. From a $1 billion private-equity wager on multilingual degrees to new grant-writing limits and a neuroscience wake-up call, the headlines below show how AI is shaping what and how we teach, learn, and fund. Read each story with an eye toward both possibility and responsibility—then decide where you’ll place your next bet.
1. A $1 Billion Play for Global, AI-Translated Degrees
Brightstar Capital Partners, run by former SoftBank executive Marcelo Claure, has acquired half of Arden University and pledged to expand its UK-accredited programs to 150 languages. If it works, students from Bogotá to Bahrain could study the same curriculum in their native tongue—and professors could spend more time coaching than lecturing (Financial Times, 2025).
The Details
- Brightstar’s investment positions Arden’s 40,000 online learners as the anchor of an AI-driven network with new, visa-sponsoring campuses across the Middle East, Latin America, and Europe (Financial Times, 2025).
- 140 programs → 150+ languages. LLMs will translate Arden’s entire UK-accredited catalog for worldwide delivery.
- Built-in adaptive tutoring. The same AI backbone will drive personalized feedback so faculty can focus on coaching.
- Visa-sponsoring hubs. New campuses in the Middle East, Latin America, and Europe give online students short in-person options (Financial Times, 2025).
Why It Matters
A private-equity wager of this size shows rising confidence that large-language models can erase language barriers and deliver personalized tutoring at scale (Financial Times, 2025). More than a growth play, it’s a proof point for border-agnostic higher education: if automated translation and adaptive support meet academic standards, investors will follow, regulators will demand cross-language quality checks, and faculty work will tilt toward mentoring and assessment—leaving institutions without similar capacity at a competitive disadvantage (Financial Times, 2025).
2. Accreditation Now Requires Responsible AI
Colleges in the Middle States Commission on Higher Education (MSCHE) region can no longer treat AI as an optional add-on. The commission’s new policy, effective July 1, 2025, tells institutions to prove that their AI use is lawful, transparent, and ethical—or risk their accreditation status (Middle States Commission on Higher Education, 2025).
The Details
- Schools must align AI tools with data-security rules, verify AI-generated content, and accept full responsibility for anything submitted during reviews (Middle States Commission on Higher Education, 2025).
- Governance on the record. Effective July 1, 2025, institutions must document lawful, ethical, and transparent AI practices in every accreditation filing.
- Security alignment. Any AI tool used for teaching, research, or operations must comply with existing data-security policies.
- Evidence checks. Colleges must verify that AI-generated data, analyses, or content are accurate and take full responsibility for all materials submitted during MSCHE reviews (Middle States Commission on Higher Education, 2025).
Why It Matters
MSCHE’s policy turns responsible AI from a best practice into an accreditation requirement. That shift gives faculty a concrete compliance lever: if leaders deploy tools without robust guardrails—ethics boards, transparency logs, data-security audits—programs and even institutional standing are at risk. Expect sharper scrutiny of AI in syllabi, research workflows, and student services, along with new resources to meet the standard (Middle States Commission on Higher Education, 2025).
3. Washington Opens the Funding Door to AI Literacy
The White House published a 90-step national plan, and the U.S. Department of Education issued a “Dear Colleague” letter clarifying that existing grants may cover AI tutoring, advising, and teacher training (Sourwine, 2025; U.S. Department of Education, 2025).
The Details
- Agencies are directed to prioritize AI skill development; educators must lead ethical use and training (Sourwine, 2025).
- 90-step national plan. A White House road map issued July 22 lists 90 directives that push agencies to weave AI competencies into existing education and workforce grants (Sourwine, 2025).
- “Dear Colleague” letter. The U.S. Department of Education confirms that current funds—think tutoring, advising, faculty training, and teacher-prep grants—may now be used for AI skill development, provided use is educator-led and ethical (U.S. Department of Education, 2025).
- Priority language. Agencies are instructed to elevate proposals that build AI literacy and responsible-use frameworks (Sourwine, 2025).
Why It Matters
Federal guidance rarely arrives without dollars. Institutions that align faculty development, student support, and curriculum projects with these AI-literacy priorities can tap new funding streams—and will be expected to show ethical, educator-guided outcomes in return. Early movers position themselves for both resources and influence as national standards take shape (Sourwine, 2025).
4. NIH Caps AI-Written Grant Proposals
Researchers hoping ChatGPT will finish their next NIH proposal should pause. A fresh notice limits investigators to six submissions per year and warns that “substantially AI-generated” applications may be rejected outright (NIH, 2025).
The Details
- Detection tools will flag AI-heavy text, and violators face cost disallowances or award termination starting with the September 25 deadline (NIH, 2025). Six-proposal limit. Each principal investigator may submit no more than six applications per year across all NIH funding opportunities. AI-generated text flagged. Detection tools will scan submissions; proposals judged “substantially developed by AI” are non-compliant.Strict penalties. Beginning with the September 25, 2025, deadline, violators risk cost disallowances, award termination, and possible misconduct referrals (NIH, 2025).
Why It Matters
Grant writing must remain a human-led craft. Scholars need review routines that balance efficiency with originality (NIH, 2025). NIH is the bellwether for federal research funding: its crackdown makes clear that originality and accountability cannot be outsourced to a chatbot. Institutions now need internal review checkpoints and faculty training that balance efficiency with human intellectual contribution. Missteps could cost researchers their grants—and damage a university’s reputation and future funding prospects (NIH, 2025).
5. Workforce Tools Win—Demand Soars
Two market signals hit the same week: Ellucian’s Journey platform, which maps learning outcomes to job skills, earned an EdTech Award, and Validated Insights projected the AI-education market will grow 22 percent annually to $16.2 billion (Ellucian, 2025; Validated Insights, 2025).
The Details
- Journey uses large-language models to recommend courses and track skill progress; meanwhile, analysts predict a 700,000-worker shortfall by 2027 (Ellucian, 2025; Validated Insights, 2025).
- EdTech accolades. Ellucian’s AI-powered Journey platform took home a 2025 EdTech Award in the Professional Skills category for mapping courses to job-market competencies (Ellucian, 2025).
- Market momentum. A Validated Insights report pegs AI-education revenue at $16.2 billion in 2024 and forecasts 22 percent annual growth—alongside a projected 700,000-worker talent gap by 2027 (Validated Insights, 2025).
- Skill mapping at scale. Journey uses large-language models to recommend upskilling pathways and track learner progress (Ellucian, 2025).
Why It Matters
Employers need AI-literate talent faster than traditional programs can supply it. Platforms like Journey prove that competency mapping and adaptive guidance are moving from pilot to mainstream, creating headroom for credit-bearing micro-credentials that stack into degrees. Faculty who design industry-aligned AI curricula can close the skills gap, attract non-traditional learners, and open new revenue streams as the market accelerates (Validated Insights, 2025).
6. Closing the Faculty Skill Gap
Universities from UT-Austin to Elon are pouring resources into AI workshops, conferences, and toolkits because most presidents say faculty unfamiliarity is the top barrier—while 86 percent of students already use AI regularly (Brereton, 2025; Elon University, 2025).
The Details
- Initiatives range from walled-garden pilots to an “AI Toolbox” website with vetted tools and teaching guides (Brereton, 2025).
- Sandbox pilots. UT-Austin, Vanderbilt, and UCF run “walled-garden” ChatGPT sandboxes so instructors can experiment without risking student data (Brereton, 2025).
- Challenge + toolbox. Elon University’s AI Pedagogy Challenge showcased 80 faculty projects and launched a public “AI Toolbox” featuring vetted tools and lesson templates (Elon University, 2025).
- Leadership view. In a national survey, presidents cited faculty unfamiliarity—not student readiness—as the #1 barrier to campus AI adoption, even though 86 percent of students already use AI regularly (Brereton, 2025).
Why It Matters
When the skill gap flips—students fluent, faculty tentative—three risks emerge: academic integrity slips, learning objectives misalign with tool use, and institutions lose momentum on responsible policy. Universities that invest now in hands-on training, peer showcases, and curated toolkits will convert curiosity into competence, embed ethics before problems scale, and move AI integration from headline pilots to measurable gains in teaching, research support, and student outcomes (Brereton, 2025; Elon University, 2025).
7. Brain-Wave Warning on Copy-and-Paste Writing
MIT Media Lab researchers attached EEG caps to essay writers and found that those who used ChatGPT showed the shallowest neural activity and poorest recall—evidence of “cognitive debt” when AI drafts do the heavy lifting (Kosmyna et al., 2025).
The Details
- Participants who wrote first and revised with AI kept stronger brain-wave patterns, suggesting a draft-then-refine approach protects thinking (Kosmyna et al., 2025).
- EEG evidence. Fifty-four adults (18–39) wrote SAT-style essays while wearing 32-channel EEG caps; the ChatGPT group showed the weakest neural connectivity and lowest recall (Kosmyna et al., 2025).
- Ownership drop-off. Across three sessions, ChatGPT users increasingly pasted output with minimal edits, while a fourth session—rewriting without AI—revealed lingering cognitive “debt.”
- Balanced path. Participants who drafted unaided and then used AI for revision maintained healthier brain-wave patterns and better content recall (Kosmyna et al., 2025).
Why It Matters
The study provides robust neuroscientific evidence that allowing AI to handle initial thinking can impair memory and critical-analysis skills. Faculty can cite these findings to justify “draft-first, refine-with-AI” policies, embed reflective checkpoints in writing assignments, and coach students on where AI assists rather than replaces cognition. Institutions crafting AI guidelines now have data to support guardrails that protect deep learning while still leveraging AI’s editing power (Kosmyna et al., 2025).
8. Peer Review Under the Microscope
Two developments spotlight quality control. An arXiv study of 27,090 AI-assisted reviews uncovered bias toward elite institutions and male authors, while NeurIPS (2025) is recruiting ethics reviewers to flag societal risks (Pataranutaporn et al., 2025; NeurIPS, 2025).
The Details
- The conference will ask academics to review up to five papers each during the summer window, applying an expanded Code of Ethics (NeurIPS, 2025).
- Bias exposed. An arXiv experiment that ran 27,090 AI-assisted reviews found large-language-model reviewers tended to favor submissions from well-known institutions and male authors while sometimes ranking top-tier, AI-generated papers too highly (Pataranutaporn et al., 2025).
- NeurIPS ethics call. To counter such risks, NeurIPS 2025 is recruiting academics to serve as specialized ethics reviewers—each will evaluate up to five papers for potential societal harms under an expanded Code of Ethics (NeurIPS, 2025).
Why It Matters
Editors need hybrid review models that mix algorithmic speed with human judgment to preserve fairness (Pataranutaporn et al., 2025). Peer review is the gatekeeper of scholarly reputation and tenure metrics. If AI reviewers amplify institutional or gender bias—or miss red flags in synthetic work—the credibility of the research pipeline erodes. Hybrid models that blend algorithmic triage with human judgment—and train scholars as ethics reviewers—can speed evaluation without sacrificing fairness or rigor. Faculty who volunteer gain experience in AI ethics while steering the field toward more responsible research practices (Pataranutaporn et al., 2025; NeurIPS, 2025).
9. Faculty Voice Versus Top-Down Tech
An AAUP survey and an Inside Higher Ed commentary reveal most AI decisions happen without faculty input, raising alarms about academic freedom and workload (Palmer, 2025; Inside Higher Ed, 2025).
The Details
- Many institutions lack shared-governance paths for AI adoption; faculty often learn of new tools only after rollout (Palmer, 2025).
- Governance gap. An AAUP survey found the majority of campuses deploy AI without meaningful faculty consultation; many instructors first hear of new tools only after rollout (Palmer, 2025).
- Academic-freedom alarm. Inside Higher Ed’s commentary urges professors to demand transparency, opt-out rights, and shared-governance structures that mirror the “AI Bill of Rights for Educators” (Inside Higher Ed, 2025).
Why It Matters
Professors who step forward now can shape tool selection, protect teaching quality, and bolster shared governance (Palmer, 2025). When administrators adopt AI unilaterally, faculty lose control over course design, assessment integrity, and workload—all pillars of academic freedom. Without clear opt-out provisions and participatory policies, AI systems can be misaligned with disciplinary standards, burden instructors with extra monitoring, and erode trust. Faculty who engage early can shape tool selection, secure resources for training, and ensure AI supports—rather than supplants—their pedagogical expertise (Palmer, 2025; Inside Higher Ed, 2025).
10. Canvas-OpenAI Partnership Embeds AI in the LMS
OpenAI and Instructure announced a direct integration that lets educators create chat-based assignments, track AI interactions in the gradebook, and automate routine communication—while keeping final grading control (OpenAI & Instructure, 2025).
The Details
- LLM-enabled prompts live inside Canvas, tying progress data to existing metrics and keeping educators in charge of approvals (OpenAI & Instructure, 2025).
- Chat-based assignments. Educators can build LLM-powered conversations directly in Canvas so students interact with AI tutors aligned to course objectives.
- Gradebook integration. All AI interactions flow into existing metrics, letting instructors track progress and approve or override suggested scores.
- Admin assistants. Optional agents draft announcements, schedule meetings, and summarize discussions—subject to faculty sign-off (OpenAI & Instructure, 2025).
Why It Matters
When AI is integrated into the LMS, adoption barriers fall. Clear guidelines on originality will be essential (OpenAI & Instructure, 2025). Embedding AI tools where teachers already work lowers adoption barriers and normalizes day-to-day use. That convenience can accelerate instructional innovation—personalized tasks, faster feedback, streamlined admin—but only if institutions pair it with clear originality guidelines, opt-in controls, and faculty training to keep human judgment at the center (OpenAI & Instructure, 2025).
11. OpenAI introduces “Study Mode” to reposition AI as an educational companion
OpenAI’s new ChatGPT “Study Mode” discourages shortcut use by inserting reflective pauses and Socratic questions, recasting the model from answer generator to learning coach across all tiers—including ChatGPT Edu (Barr, 2025).
The Details
- Co-design with educators. More than 40 universities and learning scientists shaped the feature set.
- Built-in friction. The mode withholds direct answers, asking students to clarify prompts, justify reasoning, and correct misconceptions before receiving guidance.
- Deep-dive prompts. Socratic follow-ups push learners to link ideas, compare sources, and articulate next steps.
- Enterprise + Edu rollout. Study Mode will appear first in enterprise and education versions, with wider availability to follow (Barr, 2025).
Why It Matters
Study Mode aligns AI usage with higher-education learning goals, supporting faculty efforts in academic writing development, critical thinking, and pedagogically grounded AI integration. Generative AI can either shortcut learning or elevate it; Study Mode opts for the latter. By embedding metacognitive pauses and inquiry-based dialogue, the feature supports higher-ed goals of critical thinking, academic-writing development, and ethical tool use. Faculty gain a built-in ally that nudges students toward process over product—reinforcing integrity while still leveraging AI’s feedback speed. Institutions that adopt it early can model balanced, pedagogy-first integration for peer campuses (Barr, 2025).
12. Ohio State mandates AI fluency across all majors with faculty capacity-building
Ohio State requires undergraduate students to complete an AI Fluency program embedded in general education and Success Series workshops, coupled with comprehensive faculty training to support implementation (Helmore, 2025)
The Details
- Curriculum components. First-year Launch Seminars and freshman-success courses will cover AI ethics, fundamentals, and hands-on tool practice.
- Faculty capacity-building. Instructors receive workshops and guidance on academic integrity safeguards and discipline-specific AI applications.
- Timeline. The program begins in fall 2025 for all undergraduates and then scales system-wide.
Why It Matters
Institutional mandates like this transform faculty roles and require strategic innovation in pedagogy, curriculum design, research support, and academic writing mentoring. Making AI literacy mandatory resets the baseline for every major: pedagogy, assessment, and writing support must evolve in tandem. Faculty become architects of ethical, discipline-aligned AI use—shifting their roles toward designing assignments that leverage tools responsibly, mentoring students in prompt craft and source vetting, and integrating AI into research workflows. The initiative also offers a public model other universities may follow, raising the bar for institution-wide innovation and capacity-building (Helmore, 2025).
13. CSU faculty submit over 400 AI instructional innovation proposals
In response to its AI Educational Innovations Challenge, CSU faculty across campuses proposed more than 400 projects aimed at integrating AI tools into teaching, research, and learning designs (California State University, 2025).
The Details
- Proposals span disciplines and campuses, including Stanislaus State and Cal State Fullerton efforts.
- Innovations include digital tutors, adaptive bots, and curriculum-integrated AI projects across humanities and STEM.
Why It Matters
When hundreds of faculty design AI-powered projects on their own campuses, innovation stops being a top-down pilot and becomes a system-level movement. CSU’s challenge builds faculty ownership, seeds discipline-specific experiments, and creates a large evidence base that other institutions can study. The result: faster progress on technology-enhanced pedagogy, stronger research-writing support, and a scalable model for embedding AI literacy across diverse programs.
14. Chinese faculty navigate GenAI integration amid institutional and assessment challenges
A large-scale mixed‑methods study of 776 faculty in Chinese universities exploring generative AI in language curricula revealed widespread use for formative assessment but institutional readiness gaps in policy, ethics, and pedagogical design (Iqbal et al., 2025)
The Details
- Faculty commonly employ GenAI for feedback and drafting, but summative assessment integration remains limited.
- Challenges: curriculum adaptation, assessment transformation, student engagement, ethics, and lack of professional development.
Why It Matters
The study makes one message clear: meaningful AI adoption requires robust faculty development, clear shared-governance structures, and assessment designs that safeguard academic rigor. Without those supports, generative tools risk becoming superficial drafting aids rather than instruments that truly elevate scholarly writing and evaluation (Iqbal et al., 2025).
15. New ethical framework defines eight principles guiding institutional AI use
Educause’s Georgieva and Stuart propose an eight‑element framework emphasizing ethics in admissions, classroom use, and research infrastructure deployment of AI across higher education (Georgieva & Stuart, 2025)
The Details
- Framework addresses equity, accountability, transparency, privacy, and continuous learning.
- Encourages mission-aligned AI strategy, stakeholder engagement, and faculty-centred governance.
Why It Matters
An institution-wide ethics framework provides a north star at the very moment AI tools are flooding admissions, classrooms, and research labs. By rooting decisions in equity, transparency, and continuous learning, colleges can earn stakeholder trust, safeguard student data, and keep academic values front and center. When faculty help shape—and enforce—these eight principles, AI becomes a servant of scholarship, not a shortcut that erodes rigor or fairness.
16. Interactive pedagogical agent design addresses AI adoption gap among faculty
A study developing a chatbot agent for instructors found that trust-building features—such as peer transparency and control over usage—are essential to support AI-adoption, especially for faculty skeptical about AI (Chen et al., 2025)
The Details
- Co-design workshops. Pedagogy experts and instructors storyboarded agent workflows for users with high, medium, and low AI literacy.
- Key design cues. Participants prioritized flexible on/off toggles, visible citations (“social proof”), and context-aware teaching prompts.
- Iterative prototypes. Feedback loops refined the agent to surface tips only when requested, reducing cognitive load (Chen et al., 2025).
Why It Matters
Giving instructors granular control and clear provenance data turns a generic chatbot into a trusted colleague. Such design choices can shift faculty from AI skeptics to innovators, paving the way for deeper use of conversational agents in lesson planning, research mentoring, and academic-writing support. Institutions that bake these trust elements into their tools will speed adoption and protect pedagogical integrity (Chen et al., 2025).
Betting on Balanced, Human-Centered AI Leadership
Private capital is pouring into multilingual degrees; regulators are baking responsible AI into accreditation; federal agencies are dangling funds for educator-led innovation; and researchers are reminding us that critical thinking and equity still hinge on human judgment. Together, these signals point to one imperative: successful institutions will pair bold technology moves with equally strong guardrails, faculty agency, and brain-stretching pedagogy. The winners will speak every learner’s language, design credential pathways that match tomorrow’s jobs, and govern AI with the same care they devote to scholarship and student well-being.
With Inspiration Moments, we share motivational nuggets to empower you to make meaningful choices for a more fulfilling future. Stories spur you to champion tools that amplify human insight, insist on policies that safeguard originality, and mentor colleagues toward balanced, ethical AI use.
As always, stay mindful, stay focused, and remember that every great change starts with a single step. So, keep thriving, understanding that “Life happens for you, not to you, to live your purpose.” Until next time.
References
Barr, A. (2025, July 29). Education becomes a new battlefield in the AI war between OpenAI and Google. Business Insider. https://www.businessinsider.com/chatgpt-study-mode-openai-google-gemini-education-2025-7
Brereton, E. (2025, May 15). Colleges and universities offer faculty development for AI use in the classroom. EdTech Magazine. https://edtechmagazine.com/higher/article/2025/05/colleges-and-universities-offer-faculty-development-ai-use-classroom
California State University. (2025, May 14). CSU faculty submit 400+ proposals showcasing AI-driven teaching innovations. CSU News. https://www.calstate.edu/csu-system/news/Pages/CSU-Launches-AI-Faculty-Challenge-to-Spark-Innovation-in-Teaching-and-Learning.aspx
California State University, Stanislaus. (2025, July 9). Stanislaus State among CSU leaders in AI instructional innovation. Stanislaus State News. https://www.csustan.edu/news/stanislaus-state-among-csu-leaders-ai-instructional-innovation
Chen, S., Metoyer, R., Le, K., Acunin, A., Molnar, I., Ambrose, A., Lang, J., Chawla, N., & Metoyer, R. (2025, March 6). Bridging the AI adoption gap: Designing an interactive pedagogical agent for higher-education instructors (Version 1) [Preprint]. arXiv. https://arxiv.org/abs/2503.05039
Ellucian. (2025, July 28). Ellucian Journey recognized in 2025 EdTech Awards for workforce innovation [Press release]. PR Newswire. https://www.prnewswire.com/news-releases/ellucian-journey-recognized-in-2025-edtech-awards-for-workforce-innovation-302514234.html
Elon University. (2025, May 15). AI Pedagogy Challenge. https://www.elon.edu/u/ai/pedagogy-challange
Financial Times. (2025, July 28). Marcelo Claure leads UK for-profit university deal in AI education push. https://www.ft.com/content/48e60911-090f-4226-b5e3-a83c84241d21
Georgieva, M., & Stuart, J. (2025, June 24). Ethics is the edge: The future of AI in higher education. EDUCAUSE Review.
Helmore, E. (2025, June 9). Ohio State University says all students will be required to train in AI. The Guardian. https://www.theguardian.com/us-news/2025/jun/09/ohio-university-ai-training
Inside Higher Ed. (2025, July 25). Faculty better get active on AI and academic freedom. https://www.insidehighered.com/opinion/columns/just-visiting/2025/07/25/faculty-better-get-active-ai-and-academic-freedom
Iqbal, J., Asgarova, V., Hashmi, Z. F., Ngajie, B. N., Asghar, M. Z., & Järvenoja, H. (2025). Exploring faculty experiences with generative artificial-intelligence-tool integration in second-language curricula in Chinese higher education. Discover Computing, 28, Article 128. https://www.businessinsider.com/chatgpt-study-mode-openai-google-gemini-education-2025-7
Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2506.08872
Middle States Commission on Higher Education. (2025, July 2). New use of artificial intelligence accreditation policy and procedures. https://msche.org
NeurIPS. (2025). Call for ethics reviewers. https://neurips.cc/Conferences/2025/CallForEthicsReviewers
NIH. (2025, July 17). Supporting fairness and originality in NIH research applications (Notice No. NOT-OD-25-132). https://grants.nih.gov
OpenAI & Instructure. (2025, July). ChatGPT was a homework cheating tool. Now OpenAI is carving out a more official role in education. https://www.businessinsider.com/chatgpt-openai-education-canvas-ai-2025-7Â
Palmer, K. (2025, July 22). Report: Faculty often missing from university decisions on AI. Inside Higher Ed. https://www.insidehighered.com/news/faculty-issues/shared-governance/2025/07/22/faculty-often-missing-university-decisions-ai
Pataranutaporn, P., Powdthavee, N., & Maes, P. (2025). Can AI solve the peer-review crisis? arXiv. https://arxiv.org/abs/2502.00070
Sourwine, A. (2025, July 25). Federal government’s push to integrate AI reaches classrooms. Government Technology. https://www.govtech.com/education/k-12/federal-governments-push-to-integrate-ai-reaches-classrooms
U.S. Department of Education. (2025, July 22). U.S. Department of Education issues guidance on artificial intelligence use in schools. https://www.ed.gov
Validated Insights. (2025, July 28). Education offerings in AI fields growing very rapidly, dramatic growth expected [Press release]. Business Wire. https://www.businesswire.com/news/home/20250728439909/en/Validated-Insights-Report-Education-Offerings-in-AI-Fields-Growing-Very-Rapidly-Dramatic-Growth-Expected
About the Author
Lynn F. Austin is an author, speaker, and educator dedicated to helping others achieve their highest potential. With a strong foundation in faith, Lynn combines her expertise in business, doctoral work in AI strategy and innovation in higher education, and a deep passion for growth and development. Her proven leadership in education and innovation makes her a trusted speaker, coach, and business consultant.
A valued voice in both academic and business circles, Lynn is a frequent writer on AI in higher education and the author of The BOM: Betting on Me, The Newman Tales series, and other business, motivational, and faith-based books. She empowers professionals, educators, and students alike to thrive with purpose and lead with wisdom.