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About This Book

Welcome from Sage

Welcome!

Sage the Owl waving welcome Welcome to AI Strategy for Education! I am Sage, your guide through the rapidly shifting world of AI in schools and universities. Whether you are a superintendent staring down a board vote, a teacher wondering how AI will reshape your classroom, or a parent trying to make sense of headlines, this book was written for you. We will take it one step at a time — strategy first, then tools, then action. Let's chart the course!

Why This Intelligent Textbook

Artificial intelligence is not arriving in education — it is already here, and it is improving faster than any school board cycle, curriculum-adoption process, or professional-development calendar was designed to handle. The METR study Measuring AI Ability to Complete Long Tasks (2025) found that frontier AI models' task horizons have doubled roughly every four to seven months for six straight years. That is a two-to-three-times-per-year improvement in autonomous capability — a rate of change that makes last year's assumptions unreliable and this year's planning assumptions urgent.

In the United States (2025–2026):

  • The share of U.S. K-12 teachers who say they use AI tools in their classroom rose to approximately 26% in 2024, up from near-zero in 2022, according to the RAND Corporation's American Educator Panel.1
  • The U.S. Department of Education's 2023 report Artificial Intelligence and the Future of Teaching and Learning identified student privacy, algorithmic bias, and equitable access as the three most urgent policy challenges requiring district-level strategy.2
  • Only 5% of school districts had a published AI policy as of mid-2024, leaving the vast majority of institutions navigating AI adoption without governance frameworks.3
  • $6.1 billion in EdTech venture funding flowed into AI-powered learning products in 2024 alone, creating a vendor landscape that procurement staff are not yet equipped to evaluate.4

Worldwide:

  • UNESCO's 2023 Guidance for Generative AI in Education and Research found that fewer than 10% of countries had developed national-level regulatory or guidance frameworks for AI in schools at the time of publication.5
  • The International Labour Organization projects that automation-related displacement will affect tasks in more than 60% of occupations in high-income countries, making AI literacy a core workforce-readiness competency — not an elective.6

These numbers represent your students, your teachers, your board members, and your community. Institutions that build a deliberate, evidence-based AI strategy now will be positioned to capture the benefits and absorb the risks. Those that wait will make the same decisions reactively, under pressure, with less information.

This book takes a fundamentally different approach from a technology-trend survey or a vendor pitch. It is built on a learning graph of 221 interconnected concepts organized across 13 chapters, with concepts introduced in the order their prerequisites are established — so understanding builds naturally. You will find a single repeatable decision-making framework — the idea funnel — that any school, district, college, or university can run regardless of size, budget, or technical sophistication. The entire textbook is open source and free — no paywalls, no access codes, no expensive annual editions that go out of date before the ink dries.

How to Use This Book

This textbook is designed for self-paced study by administrators, educators, and policy staff. Each chapter builds on prior material, so reading in order is recommended. The book includes:

  • 13 Chapters covering AI literacy, capability trends, strategy frameworks, the idea funnel, intelligent textbooks and xAPI, pedagogical models, responsible AI, governance, agentic AI, and strategic planning
  • Interactive MicroSims embedded in chapters — browser-based simulations you can manipulate to explore concepts without any software installation
  • Quizzes at the end of each chapter for self-assessment and team discussion
  • Annotated References linking to books, articles, and open-access resources for deeper reading
  • Glossary with precise definitions for every key concept
  • FAQ with answers to common questions about AI in education
  • Learning Graph visualizing 221 concept dependencies so you can see how ideas connect across chapters
  • Search available from any page using the search bar at the top

The Learning Graph is especially useful if you come to the course with a specific question — for example, "What do I need to understand before I can evaluate xAPI vendors?" — and want to trace the prerequisite chain rather than reading linearly.

About the Author

Dan McCreary headshot

Dan McCreary is a semi-retired AI researcher, solution architect, and educator who has spent more than three decades helping Fortune 100 organizations reason over massive datasets. At Optum he founded the Generative AI Center of Excellence and led the team that built one of the world's largest healthcare knowledge graphs — spanning over 25 billion vertices — to unify member, provider, and patient insights. Dan's deep background in knowledge representation and systems thinking underpins the precise learning graphs and intelligent textbook workflows used throughout this course.

He is the co-author of Making Sense of NoSQL (Manning Publications), the founding chair of the NoSQL Now! conference, and a frequent keynote speaker on semantic search, ontology strategy, and AI hardware. Beyond industry, Dan has mentored students as a STEM volunteer since 2014 and now applies the same rigor to building open educational resources. You can visit the Intelligent Textbooks Case Studies to see over 87 textbooks that Dan has created or co-created with other authors.

Selected Credentials

  • B.A. in Physics and Computer Science, Carleton College
  • M.S.E.E., University of Minnesota
  • MBA coursework, University of St. Thomas
  • Patent holder in semantic search and ontology management techniques
  • Advocate for large-scale Enterprise Knowledge Graph adoption across healthcare and education
  • Long-time promoter of accessible, low-cost AI-powered learning experiences

How to Cite This Book

If you reference this textbook in academic work, curriculum proposals, lesson plans, or other publications, please use one of the following citation formats.

APA (7th edition)

McCreary, D. (2026). AI Strategy for Education. https://dmccreary.github.io/ai-strategy-for-education/

Chicago (17th edition)

McCreary, Dan. 2026. AI Strategy for Education. https://dmccreary.github.io/ai-strategy-for-education/.

MLA (9th edition)

McCreary, Dan. AI Strategy for Education. 2026, dmccreary.github.io/ai-strategy-for-education/.

BibTeX

@book{mccreary2026aistrategyed,
  title     = {AI Strategy for Education},
  author    = {McCreary, Dan},
  year      = {2026},
  url       = {https://dmccreary.github.io/ai-strategy-for-education/},
  note      = {Interactive intelligent textbook}
}

To cite a specific chapter, append the chapter number and title — for example:

McCreary, D. (2026). Chapter 1: AI Foundations — What Every Educator Needs to Know. In AI Strategy for Education. https://dmccreary.github.io/ai-strategy-for-education/chapters/01-ai-foundations/

License

This work is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). You are free to share and adapt the material for non-commercial purposes as long as you give appropriate credit and share your adaptations under the same license.

References

  1. RAND Corporation. (2024). American Educator Panels: Teachers' Use of AI Tools in the Classroom. https://www.rand.org/pubs/research_reports/RRA956-21.html ↩

  2. U.S. Department of Education, Office of Educational Technology. (2023). Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. https://www2.ed.gov/documents/ai-report/ai-report.pdf ↩

  3. CoSN (Consortium for School Networking). (2024). State of EdTech Leadership Survey: AI Governance Readiness. https://www.cosn.org/ ↩

  4. HolonIQ. (2024). Global EdTech and AI in Education Funding Report 2024. https://www.holoniq.com/ ↩

  5. UNESCO. (2023). Guidance for Generative AI in Education and Research. https://unesdoc.unesco.org/ark:/48223/pf0000386693 ↩

  6. International Labour Organization. (2023). Generative AI and Jobs: A Global Analysis of Potential Effects on Job Quantity and Quality. https://www.ilo.org/global/research/global-reports/world-of-work/2023/lang--en/index.htm ↩