It is impossible to talk about and predict the future without considering past events. Therefore, in this brief article, as I did last year, I will attempt to compare the events of 2025 with those of 2026. The primary goal is not a quick glance, but a brief analysis to identify potential gaps. Because we all know that without understanding the problem, it will be impossible to find possible solutions.
As the title of the article suggests, this comparison and analysis focuses on developments in the digital world and the major changes that artificial intelligence brought about in the past year. The other part of the article examines the effects these technologies may have on human life and the world around us in the coming year. Finally, I will refer to the gap that emerged in my thinking and the solution I reached after months of study.
The evolution of the digital world in 2025
In 2025, artificial intelligence transitioned from an emerging technology to the primary infrastructure of the digital economy. Massive investments, powerful multimodal models, and the rapid penetration of AI into healthcare, education, and everyday life made 2025 a turning point in the history of technology. Below is a brief overview of the most important developments.
- In 2025, Google’s educational division, Gemini for Education, officially reached more than 10 million students across over 1,000 institutions in the United States.
- Google introduced more than 150 new features, including quizzes, flashcards, and other learning tools for teachers and students. As a result, artificial intelligence—at least in some countries—is no longer merely a research project but has become part of everyday academic life.
- Google and the United Arab Emirates have launched a public education initiative called AI for All, aimed at empowering students, teachers, and small businesses with AI literacy and skills.
- Greece signed a memorandum of understanding with OpenAI to introduce an educational version of AI, ChatGPT Edu, into schools, signaling that not only companies but also governments are integrating AI into national education systems.
- The 2025 EdTech Industry Report indicates that online learning platforms, VR/AR technologies, personalized learning, data-driven education, and AI-powered tools have become part of the mainstream education ecosystem. The convergence of technology, learning, and AI is no longer a temporary trend but a defining direction of the education industry.
- From a regulatory perspective, the European Union, the United States, China, and other countries passed new legislation addressing transparency, risk management, model accountability, and data security.
AI-driven transformations in education
When focusing specifically on education, these developments can be summarized as follows:
- Full integration of AI into teaching and classrooms, including content generation, assessment design, homework evaluation, slide creation, and automated coaching in many schools and universities.
- Personalized learning, with individual learning paths determined based on learners’ performance and behavioral data.
- Expansion of VR/AR and immersive learning environments, such as virtual laboratories, realistic educational visits, and scientific or historical simulations.
- A changing role for educators, shifting from learning designers and content providers to facilitators, mentors, and guides of the learning process.
- Teaching digital literacy skills, including critical thinking, awareness of algorithmic bias, and effective human–machine collaboration.
- Greater inclusion and equity, through AI-supported tools for learners with special needs and improved access for underserved regions.
- Growth of skills-based education, with short-term online programs expanding alongside traditional universities and increased emphasis on labor-market-relevant skills.
Country competition and regional trends
Understanding the pace of AI-driven technological change from a geographical perspective provides insight into both current developments and emerging global competition. In 2025, regional trends were shaped as follows:
- In Europe, regulations became more stringent, and practical guidelines were introduced to ensure transparency and safety in AI systems. Countries such as Finland, Estonia, and France took leading roles in standardizing teacher training and the safe integration of AI in education.
- In Asia, South Korea, China, India, and Singapore experienced significant growth, particularly in applying AI within schools and national education programs. South Korea, Japan, and Singapore emerged as pioneers in personalized learning and smart classroom technologies.
- The United States remained a leader in edtech innovation, infrastructure development, and university-led workforce training in AI. The U.S., China, and India also accounted for the largest investments and the highest number of leading edtech companies.
- In the Middle East, the UAE and Saudi Arabia made substantial investments in smart schools and national AI-driven education initiatives.
- Several African countries and other developing regions focused on leveraging AI to expand affordable and equitable access to education.
Possible developments in 2026
Past developments often make future trends partially predictable. This predictability enables more effective planning and strategic decision-making, as well as earlier identification of potential risks. Based on this perspective, several key developments may shape 2026.
- Unlike the highly enthusiastic and innovation-driven years of recent AI expansion, 2026 is likely to place a stronger emphasis on human responsibility. While 2025 was largely defined by competition in production, innovation, and the widespread application of AI, emerging gaps and challenges may prompt experts—particularly in technology and education—to adopt more human-centered approaches, ethical standards, and intelligent, restrained use of AI. The focus may shift from mere adoption and digitalization toward deeper engagement with the human mind and new perspectives on meaningful learning.
- In a previous article published in this same media outlet, I argued that artificial intelligence would increasingly take on a mentoring role. This trend became visible in 2025 and is expected to intensify in 2026. I believe that AI systems can function as self-regulating psychological support for the human mind and encourage deeper thinking. However, this process requires clear prerequisites. When grounded appropriately in psychological principles, particularly within learning environments, two-way cognitive engagement between humans and AI can be significantly strengthened. This highlights the necessity of applying cognitive and behavioral psychology in the design of learning environments and intelligent systems. This line of thinking has also informed the development of my current research-oriented startup project, details of which I have discussed in another article published in the same media.
- Another major issue is deep personalization of learning. While personalization was already considered important in AI-supported learning in 2025, it will become mandatory in 2026. Advanced educational systems based on large language models must increasingly account for learners’ cognitive load, motivation, emotional states, and cultural backgrounds. Uniform education models will be ineffective in the age of AI. This challenge has been a core motivation behind the design of my current project.
Challenges and requirements in the age of artificial intelligence
Considering the developments discussed above, several major challenges are likely to persist or intensify.
- The risk of weakening independent thinking remains a serious concern. Overreliance on AI technologies and excessive consumption of AI-generated outputs may reduce the perceived importance of higher-order cognitive skills such as critical thinking, creativity, and problem-solving. This issue requires systematic research to determine which cognitive abilities may be weakened, under what conditions, and among which groups of consumers or learners. Conversely, if interaction with large language models is to enhance cognitive capacities, the underlying mechanisms must be clearly understood.
- New forms of educational inequality may emerge. Beyond simple access to technology, a deeper divide may develop between those who learn how to think with AI and those who merely receive outputs from it. Educational equity should therefore focus not only on access statistics but also on teaching learners how to engage cognitively and responsibly with AI systems. Reflection on this challenge has played a significant role in shaping my research trajectory and startup initiative.
- The crisis of educational assessment and learning validity is becoming increasingly evident. Although formative and summative assessment debates predate recent developments in AI, the rise of large language models intensifies existing challenges. As definitions of knowledge, learning, and competence become less clear-cut, education systems must reconsider traditional evaluation practices. Emphasizing process-oriented assessment rather than final products may offer a more appropriate response in the coming years.
- Finally, the redefinition of literacy and skill represents another major challenge. As future selection processes increasingly rely on learning histories and competencies, classical definitions of literacy and expertise may no longer suffice. Education and learning specialists will bear responsibility for revisiting fundamental concepts such as knowledge, literacy, and skill—a task that cannot be accomplished without systematic research.
Summary
In this article, I sought to present a concise analytical comparison of developments in the digital world, particularly in education, between 2025 and the emerging demands of 2026. Drawing on personal experience, academic and research activities, and a review of reputable international sources (some of which are cited in the references section), the article moves beyond descriptive reporting to identify key gaps, challenges, and possible future directions in the age of artificial intelligence. As a psychologist and educational researcher, my primary focus has been on AI’s role in education, the changing nature of learning, the evolving role of educators, and the cognitive, ethical, and educational implications of these technologies.
Furthermore, my studies and observations over the past three to four years—especially regarding challenges such as the weakening of independent thinking, emerging educational inequalities, the crisis of learning assessment, and the necessity of human-centered design—have led to the development of a new research-applied initiative. This initiative is currently being developed as a research-oriented startup titled ETechX-DrAtefehF, which aims to integrate theories from educational psychology and learning sciences into the design and application of AI in education, with the goal of fostering deep learning, self-regulation, and meaningful human–technology interaction.
Resources
Ed-Ex – Global EdTech Trends 2025: How AI Is Reshaping Learning
https://ed-ex.com/en/blog/global-edtech-trends-2025-how-ai-is-reshaping-learning
• Codiste – AI Trends Transforming EdTech (2025)
https://www.codiste.com/ai-trends-transform-edtech
• EdTech Innovation Hub – Ten EdTech Predictions for 2025
• Vocaliv – 10 EdTech Trends to Watch in 2025
arXiv – Integrating Generative AI into Learning Management Systems (2025)
https://arxiv.org/abs/2510.18026
• arXiv – Generative AI in Education: Student Skills & Lecturer Roles (2025)
https://arxiv.org/abs/2504.19673
• arXiv – Ethical Challenges of AI in STEM & K–12 Education (2025)
https://arxiv.org/abs/2510.19196
• arXiv – Accessible AI-Based Learning Tools for Special Needs (2025)
https://arxiv.org/abs/2504.17117
TIME Magazine – World’s Top EdTech Companies of 2025
https://qa.time.com/7335559/worlds-top-edtech-companies-of-2025
LinkedIn News – Global vs. MENA EdTech Funding 2025
EU AI Act documentation & implementation guidelines (2025)


