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.

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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:

1. 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.
2. Personalized learning, with individual learning paths determined based on learners’ performance and behavioral data.
3. Expansion of VR/AR and immersive learning environments, such as virtual laboratories, realistic educational visits, and scientific or historical simulations.
4. A changing role for educators, shifting from learning designers and content providers to facilitators, mentors, and guides of the learning process.
5. Teaching digital literacy skills, including critical thinking, awareness of algorithmic bias, and effective human–machine collaboration.
6. Greater inclusion and equity, through AI-supported tools for learners with special needs and improved access for underserved regions.
7. 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:

1. 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.
2. 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.
3. 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.
4. In the Middle East, the UAE and Saudi Arabia made substantial investments in smart schools and national AI-driven education initiatives.
5. 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.

1. 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.
2. 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.
3. 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.

1. 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.
2. 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.
3. 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.
4. 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

https://www.edtechinnovationhub.com/news/starrng-ai-vr-microlearning-and-more-etihs-ten-predictions-for-edtech-in-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)

The post What 2025 Taught Us and What 2026 Will Demand appeared first on Medika Life.

Am I blind to the fact that the nosology of psychiatry/psychology requires this distinction? I don’t think so, and I question using a word that appears to have evidence of its biological or “unconscious” base.

Yes, biology is often seen as the cause of so many mental disturbances, but we are still walking in a dark room with our eyes shut on that one. For every “discovery” about a gene connection, we find it’s a dead-end where treatments fail, yet we continue with the treatments as though they will provide a cure. Some of the treatments bring on more symptoms that then require another treatment. Consider the rash of TD (tardive dyskinesia) medications we’re now seeing on TV. It is an iatrogenic disorder.

Today, my substack is prompted by reading about play therapy, its effectiveness, and where it originated. I believe it has a place in treatment for children, but I am also aware of the warped history that came before it.

One of the significant forces that sparked interest in this form of treatment was the Virginia Axline book “Dibs in Search of Self….” Greeted enthusiastically by the public and professionals alike, I don’t believe many looked critically at Axline’s portrayal of her treatment and the boy. I think it’s similar to the case of the Sybil books. Authors can take some liberties with their books, but not when people’s lives are at stake.

I’ll give one example of a problem with Axline’s book. Axline stated the therapeutic intervention lasted six months. I understand it took much longer than that, possibly years, and I have to ask if Axline or her editors made that change in the book. The second point is Axline’s theoretical basis for her interventions, both of which she fails to outline in her book. It’s more of a diary than anything else.

What prompted her to conceive her approach? The critical readers of her book have pointed out that she subscribed to the original idea of the “refrigerator mother.” Cold, emotionally distant mothers were the genesis of the syndrome. One of the strong proponents of this orientation was Bruno Bettelheim, a man discredited for plagiarism after his death when research regarding his book on fairy tales and, allegedly, brutal therapeutic treatments came to light. His book, “The Empty Fortress..” lays the blame for autism squarely on mothers.

Bettelheim appears to have had no training or credentialing in the techniques he espoused and may have given himself a c.v. that was replete with falsehoods. The image he created has been repeatedly questioned, and it is astonishing. Despite all of this, too many hold him in high regard.

Of course, the journal he wrote while in a German prison camp is something we should read. But, considering his slipping into unverified rhetoric, we have to question that, too.

Aside from Freud, Bettelheim, and Axline, we need to, as is being done now, begin the work of repair on theory and treatment of mental disorders. If they are illnesses, let’s say what causes them and, if they are more dependent on environmental issues, okay. More likely, any disturbance is multi-factorial, and many treatments will still not hit the mark solidly enough to “cure” these illnesses. As one patient told me, relief from his auditory hallucinations was what he wanted.

The future is bright and promising in terms of neurobiology and psychological treatments and, for that, we should be grateful. One instance of a book where I believe we can take comfort in parents’ ability to help autistic children is “Son Rise,” written many years ago. I recommend you read how dedication and consistent hard work with a child can have incredible results.

Remember that we create “gods” in medicine and psychology, and too many of them have feet of clay. Psychology has a few presently running around beating their chests like prominent warriors in the war for mental health treatments. But they may provide a crumb of an idea that can be extended to something worthwhile. Worshipping them without recognizing their humanity takes the wrong road on a dangerous highway.

The post Old Theories, Questionable Experts, and Mental Disturbances Need to Be Deconstructed appeared first on Medika Life.