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.

Originally, I thought these certificates were intended to provide evidence of the individual’s expertise, and that’s what most patients/clients believe. I was wrong. It provided nothing more than an indication that they had paid for that certificate. One of those bought certificates was on the wall of someone who supervised interns. And this was an individual who was highly regarded by people in the field in that state.

At the time, I decided I needed to do something, and I wrote an article that was published here on the internet. I believe I called it “Beware the Strike of an Evil Therapist.” Unfortunately, people practicing in all areas of healthcare can be a danger to those who come to them for care, expertise, and help in desperate circumstances.

It’s not limited to therapists. I’ve seen psychiatrists who hallucinated because of their alcoholism. They still worked at hospitals. Another psychiatrist was addicted to specific stimulants and stole scripts from his supervisor’s prescription pad, which was conveniently left on a desk. If you think this practice has been eliminated by digital prescribing, you would be wrong.

I was also a member of a licensing board, where I gained firsthand knowledge of unscrupulous practices by licensed psychologists. Recently, I read a DOJ document online regarding one of them, who, after her license was revoked, continued to practice for two more years before she was caught again. She’s only one. How many more are out there?

Why Do I Write This Today?

I decided I had to write this article because of a comment that was made by Rob Reiner, an incredibly talented film director, regarding one of his children and a problem with addiction and rehab services. Reiner and his wife were murdered over the weekend, having their throats slashed in their home. As of this writing, their son has been arrested but not charged with homicide.

In the article’s quotes, Rob Reiner still clearly remembers specific words. After years of seeing his son Nick go through seventeen rehab centers, he finally realized what had happened. “When Nick would tell us that it wasn’t working for him, we wouldn’t listen,” he told the Los Angeles Times in 2015, as reported in The Hollywood Reporter. “We were desperate and because the people had diplomas on their wall, we listened to them when we should have been listening to our son.”

His wife, Michele, shared more: “We were so influenced by these people. They would tell us he’s a liar, that he was trying to manipulate us. And we believed them.”

The Reiners’ experience isn’t unique. It highlights a broader problem in healthcare, where certificates and impressive titles can sometimes mask incompetence, ethical issues, or even fraud.

The Diploma Dilemma

We are taught to trust signs of expertise. That’s an error on our part. Diplomas, certifications, and licenses on office walls suggest skill and trust. But sometimes, these symbols can hide problems and dishonesty. Today’s impressive digital printers can provide any diploma or certificate you require, and they do it from afar for a fee. Using appropriate AI software, you can create IDs with your photo on anything you wish.

The reality is that healthcare, especially mental health and addiction services, has a problem with credentials. This puts vulnerable patients in danger.

In 2023, federal authorities uncovered a massive fraudulent nursing diploma scheme in Florida. Over 7,600 fake nursing diplomas were sold to individuals who never completed their education. These people then passed national board exams and obtained legitimate licenses, working in healthcare facilities across multiple states.

It’s clear that across the country, 7,600 people with fraudulent nursing credentials are providing care in various facilities and treating patients without the appropriate training. The Justice Department has singled this out as a serious matter, and all of us should be aware of who is providing care for our loved ones and what credentials they possess.

Background checks are not always thorough at all facilities. Do any of you know of the case of Dr. Michel Swango? He was killing patients until one physician decided to do a more intense background check on him, and called one of the prior facilities where he said he had worked. They caught Swango as he was about to board a plane to Asia, where he had another job.

Fake credentials are only part of the problem. A bigger issue is the confusion around credentials, which makes it hard for patients to know who is genuinely qualified to help them. Of course, there’s also the matter of people who, on their letterhead, seem to indicate they have a license number when, in one case, with which I have firsthand knowledge, it was a tax ID number, not a license number. He also liked people to call him “doctor” when he didn’t have a doctorate. The sign in front of his office said “DR….”

The Alphabet Soup of Mental Health Credentials

Mental health and addiction treatment have a confusing mix of credentials. A therapist’s business card might display letters such as PhD, PsyD, LCSW, LPC, LCPC, MA, MS, PA, CAC, and many others. Each stands for a different education, training, and role. A woman who regularly appeared on television as a psychological expert had a doctorate in school administration.

Some addiction counselor certifications only require a high school diploma. Others require a doctorate and years of training. But to families looking for help, all the credentials look impressive. Therein lies one of the major issues here. Remember, palm trees and swimming pools don’t create honest-to-goodness helpful rehab.

In fact, I worked in a facility where the addiction counselors were telling the patients, who had schizophrenia, that they should not be taking any form of medication because that would continue their addiction. The contradiction at that facility between the two types of therapies patients were receiving was mind-boggling. Little was done to improve the situation. And that facility was not unique because another major addiction-related hospital facility told patients they couldn’t even take an aspirin.

A cleric with questionable expertise was also brought in to attend treatment team meetings. He wore a cleric’s collar, and no one ever questioned whether, in fact, he was an ordained minister or had any experience or education in mental health issues. He came and went on the wards as he pleased.

This confusion leaves people vulnerable. When families are in crisis, whether their child is addicted, their spouse is suicidal, or their parent is getting worse, they don’t have time to look up what the credentials mean. They see the diplomas, hear the confident words, and trust. Is “trust” a dirty word now?

The Ethics Crisis in Addiction Treatment

Ethics problems in addiction treatment go beyond fake credentials. Research shows there are ongoing issues with how care is provided to patients.

A 2011 article in Focus, the journal of the American Psychiatric Association, highlighted a troubling pattern: providers develop negative reactions when treating patients who “minimize or lie about their substance use patterns.” These issues can lead clinicians to view normal addiction behaviors — denial, manipulation, inconsistent adherence — as character flaws rather than symptoms of illness. Yes, that’s an old article, but I believe it still has great value.

This is what happened to the Reiners. Providers called Nick manipulative and dishonest, leading his parents to doubt his reports that the programs weren’t helping. The diplomas on the wall made these judgments seem more trustworthy than the family’s own instincts.

Research published in the Journal of Ethics highlights another disturbing reality in that addictions are viewed as associated with a lack of personal control over the behavior, creating concerns about patients’ capacity for autonomy. This philosophical stance can lead to paternalistic treatment approaches that dismiss patient preferences and experiences. Addiction is a biological change in the brain that can make diminished control a given.

A 2024 study in the Journal of Psychoactive Drugs found that ethical issues in substance use treatment often reflect “a delicate balance between provision of person-centered treatment and adherence to program-level policies.” Too often, policies are followed instead of personalizing care, and credentials are valued more than listening.

At one hospital where patients were systematically rotated through units, each unit had a different theoretical orientation. Neither the chief of psychology nor the medical director seemed to find this a problem. How can any patient receive quality care if they are constantly being bounced from one theory to another? To say it’s ludicrous doesn’t do it justice.

The Power Imbalance

A big part of the credential problem in healthcare is the power imbalance. Clinicians have advanced degrees, special knowledge, and authority. Patients and families come in during a crisis, feeling vulnerable and desperate for help.

When clinicians tell worried parents that their child is manipulating them, that their instincts are wrong, or that the program will work if the patient just commits, parents may feel unable to disagree. After all, these professionals have diplomas on their walls. I think there should be a rule that only someone’s license should be on the wall.

This situation is especially risky in addiction treatment, where stigma already makes families think their loved ones are liars or morally weak. When providers repeat these ideas, families may stop advocating for their loved ones. I have always told patients to attend any meeting with an advocate.

Protecting Yourself in a Broken System

So what can patients and families do? How can we get through a system where credentials might be fake, confusing, or used to ignore real concerns?

First, check credentials yourself. Don’t trust what’s on the wall. Look up state licensing boards and confirm degrees with universities. For addiction counselors, check certifications with state boards or national groups. The Federal Trade Commission warns to watch for “out-of-sequence degrees” — someone with a master’s degree should also show evidence of a bachelor’s degree.

Second, trust your own experience. If treatment isn’t working, it’s not just your imagination. If your loved one says the approach is not helping, take that seriously. Credentials and authority don’t make clinicians perfect. As Rob Reiner learned, sometimes the person without the degree knows best what they need.

I heard of one family who took their son to a psychiatrist who promised he could cure the young man of his specific issue for $10,000. The family paid. The work didn’t result in a cure, and the psychiatrist admitted he had no experience in the field.

Third, get a second opinion. In other areas of healthcare, this is normal. Mental health and addiction treatment should be the same. If a provider discourages you from seeking another view or makes you feel bad about it, consider that a warning sign. I don’t believe there should be a fee for a meeting to explore whether this person would be suited for the care required. But I know that’s not always the case.

Fourth, look for care that centers on the patient. Here, the best results might be provided by someone with firsthand experience with that facility. Research shows that treatment works best when providers and patients work together, not when providers give orders. Providers should explain their choices, answer questions, and change their approach if needed.

The Path Forward

The healthcare system needs real changes. Credentialing should be stronger. Ethics training in mental health and addiction programs should focus on patient independence and working with families. Harsh, shame-based methods should be replaced with care grounded in evidence and compassion.

But until these changes are made, patients and families should be careful and ask questions. Diplomas on the wall are just a starting point for trust. They show someone has finished school and passed exams, but they don’t guarantee skill, ethics, or real help.

One psychology intern at a hospital was in the field because he had been told in medical school that he should leave because he didn’t have patient empathy. What did he choose? The worst field of all if you have no empathy — psychology.

Rob Reiner’s regret teaches us something important: “We should have been listening to our son.” In a healthcare system where credentials can mislead and authority can silence questions, listening to patients and trusting our instincts may be the most important thing we can do.

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Human cognition has always been a negotiation or even battle between imagination and experience. We build models and then we test them. We get things wrong, learn, and rejigger against the facts of the real world. Our intelligence lives in that loop between abstraction and embodiment. AI has no loop. It never leaves the page. When a model falters because of a stray phrase—say, when the simple addition of “cats sleep for most of their lives” triples its error rate.  Now, let’s be clear, that’s not confusion, it’s exposure. The system doesn’t know which parts of language belong to meaning and which don’t. It reads everything as pattern. That’s the curious mirage of AI. It’s the words without the world.  Or should I say map?

Korzybski famous and timeless quote was about humans, not machines. He warned that when we mistake a symbol for the thing it represents, we drift toward ambiguity, if not fiction. What’s unsettling now is that we’ve mechanized that ambiguity in the context of AI. We’ve built a technological architecture that embodies it with an odd perfection. And because AI speaks so persuasively, we start to believe it. A generated paragraph about empathy can feel like empathy itself. And a simulated diagnosis can feel like understanding. The danger isn’t deception, it’s equivalence. So, remember, the algorithm doesn’t lie, it just neither knows nor cares.

So, if AI lives in the map, then we remain the territory. The goal isn’t to merge the two but to hold them in tension. That distance—between representation and reality—is where depth arises. I’ve called this parallax cognition: when two distinct forms of knowing observe the same problem from different vantage points. The difference creates critical dimensionality. Consider AlphaFold, the AI that predicted protein structures. It recognized patterns invisible to us, but the discovery only mattered once human scientists interpreted what those patterns meant in biological terms. That’s parallax in action. AI sees the map and we walk the ground. Together, but distinct, we generate insight neither could reach alone.

There’s a fair question that’s often raised: If it works, does it matter how? For translation, maybe not, for navigation, perhaps less. But in meaning-dense domains like medicine, ethics, and fine art, how it works is the difference between simulation and understanding. AI’s competence can mask its detachment and the map can be dazzling enough that we forget it isn’t the journey.

Anti-intelligence isn’t a flaw, it’s the logical endpoint of symbol-based reasoning. It represents the perfection of the map and the potential elimination of the territory. Korzybski’s century-old warning is resonant today.  Once our abstractions become too beautiful, we start living inside them. AI has given us the most complete map humanity has ever drawn. The challenge is to stay grounded and to make sure the map still serves our earth beneath it.

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Thought with purpose.

The Human Side: Purpose as the Compass

For us humans, thought doesn’t just tumble out of nowhere. Even a simple thought is tethered to something such as a memory, a need, or even a curiosity. The purpose is always there, sometimes in plain view, sometimes we barely notice it’s steering us. Nevertheless, it’s there.

That orientation towards an end, whether it’s solving a problem, telling a story, or making sense of loss, shapes everything. It sharpens context, gives weight to our choices, and carries consequences forward.

The Machine Side: Output Without an Inner Why

Now, here’s the curious part, large language models can produce work that looks like it was driven by intent. But the intent isn’t theirs. The “why” behind the output is always imported from a prompt, a training objective, or a line of code.

Even Yoda, the unlikely techno-philosopher of a galaxy far, far away, hinted at this kind of thinking. His counsel to Luke was often binary: “Do. Or do not. There is no try.” In moments like this, the Jedi master stripped away contemplation of purpose in favor of pure execution. It’s a kind of “ateleological” mindset, where output emerges without interrogating the why.  And that has its place in discipline and training. But for us, this is the exception, not the norm. Our thinking almost always is driven by a goal, even when we’re not consciously naming it.

LLMs begin with patterns, not with goals. They finish with polished coherent text, but without ever having set out to “do” anything. This is the inversion I’ve called anti-intelligence—completion without intention, or perhaps better said, performance without the inner compass that orients human thought.

Yes, the Lines Blur

It’s easy to miss the difference. A well-crafted AI essay can read like the work of someone with a clear aim. That’s because we humans are wired to project purpose onto anything that speaks coherently. It’s how we’ve always communicated and to assume a mind with goals is on the other side of the words.

But mistaking thought without purpose for thought with purpose isn’t harmless. It can shift decisions into the hands of systems that can’t weigh values, and make scale look like judgment. And perhaps most insidious,  it can dull our instinct to ask why something was said in the first place.

The Partnership That Works

This doesn’t make AI lesser. In fact, the difference is what makes it valuable. Humans bring the “why.” AI brings the “how” and it can deliver that “how” at a speed and scale we’ll never match.

The essential challenge is keeping the two in their proper lanes, even when a curious cognitive emulsion sometimes emerges. When human purpose sets the direction and AI handles the reach, the result is something neither could accomplish alone. Lose that clarity, and we start letting pattern-generation masquerade as goal-driven thought.

Now, More Than Ever

More and more, the content filling our feeds, inboxes, and dare I say, heads, will come from systems that simulate purpose without ever possessing it. Forget that distinction, and we risk letting the “performance of intelligence” replace the reality of it. That’s a shift we can’t afford.

Thought with purpose is more than a phrase. It’s a reminder that the thinking worth trusting comes from goals we choose, meaning we make, and consequences we’re willing to own. It is the perfectly imperfect part of being human that no machine will ever replace.

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That changed something, even if we didn’t notice it at first.

There was a kind of wonder in seeing language freed from memory and effort, from time and constraint. We wanted to see what knowledge looked like when it didn’t have to be learned. When it could simply be summoned. So, we opened the interface, glowing and ready. And what we found was smooth and seductive. Answers arrived without hesitation, just coherence on cue. And for a moment, we believed, including me, that maybe this was the future. Not just of information, but of thought itself. And I even called it The Cognitive Age.

But something else entered the room. It was a quiet shift in how we think, in what we trust, in what we now take as presence. It didn’t just offer a tool, it offered a new architecture for cognition. Slowly, almost imperceptibly, we began to tune ourselves to its rhythm. We adapted to something that simulates intelligence without ever understanding. What I’ve come to call anti-intelligence. A coherence engine that looks like thinking but isn’t.

Still, it’s useful. Students rely on it to learn. Writers use it to craft their narratives. Therapists use it to summarize long, tangled stories. Certainly, it makes things easier. But perfection doesn’t stay still. Once introduced, it often begins to steer and even drive. At first, we admired the fluency. And then, without much varied fanfare, we let it set the pace.

What we’ve lost is easy to miss. We used to find meaning in the struggle. In the clunky sentence, the pause and even in the contradiction that didn’t resolve. These weren’t flaws, they were signs of someone thinking. But machine logic doesn’t like friction. It uses the hammer of statistics to smooth and brings things to a cohesive conclusion. And somewhere in that shift, the simulation began to feel more real than the flawed voice it was supposed to support.

This isn’t just about tone or writing style, it’s about how we shape thought. AI doesn’t think, but it “performs thinking” so well that we start to believe it does. And when that performance becomes our standard, we adjust ourselves to it.

Curiously, effort may start to feel inefficient. If the answer arrives polished and complete, why struggle? But the struggle is the very thing that gives thought its shape. It’s not noise, it’s the signal. It means someone is reaching and working to understand. Too often, the effort is faked. The surface looks right. But nothing was ever carried to get there.

And the more we grow used to the polish, the less we tolerate the real work behind it. We lose patience with what once made us human. Those defining moments of imperfect moments of doubt, curiosity, and hesitation. That’s what’s being eroded, not just facts, but the expectation that meaning takes time. That truth, when it shows up, carries with it some resistance.

The simple truth is that ambiguity used to be a space we entered, not a flaw we tried to fix. We still hold on to the Mona Lisa for a reason. Not because her expression is clear, but because it isn’t. Her face doesn’t resolve, but it lingers in a poetic injustice to finality. And that used to mean something. But systems built to optimize don’t linger. They conclude and finalize. Push a button and they collapse possibility into answer. And as we spend more time with them, we begin to mirror them.

In the myth, when Pandora opened the box, everything was released but one thing. And I think that it was hope stayed behind. And maybe it still does. Maybe it lives in the rough sentence we haven’t fixed. The thought we haven’t quite found the words for. The moment we choose to write on our own and let perfection be damned. Or maybe, and perhaps most importantly,  hope my lie in what AI can’t do.

Because if we forget how to reach, how to wait, how to not know, then we lose more than just voice. We lose the raw material of thought. And somewhere in the unfinished space, in the gap between what we mean and how we try to say it, something honest and something very human still survives.

Something the machine has not yet learned to fake.

Us.

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In this exclusive conversation, I join Hal Wolf, President and CEO of HIMSS, to explore HIMSS’s evolving role in fostering collaboration between hospitals, startups, and policymakers. With the health-ecosystem landscape tracking the early days of a new administration, uncertainties remain—ranging from regulatory shifts to funding allocations. Yet, as Wolf underscores, HIMSS remains steadfast in advancing health equity, supporting digital transformation, and offering actionable strategies that improve care delivery.

This conversation occurs between ViVE in Nashville and HIMSS in Las Vegas—two health gatherings that bring innovators, policymakers, and industry leaders together. While ViVE spotlights digital health startups, investment trends, and edgy sparks, HIMSS serves as the broader convening ground for professionals shaping the future of health information and technology. HIMSS is where the work happens—the “Davos” of health information.

Wolf outlines key issues such as integrating artificial intelligence in hospital systems, the role of primary care in driving better patient outcomes, and how organizations must balance innovation with financial realities. At HIMSS, essential dialogue between established institutions and emerging disruptors has never been more crucial.

Join us as we delve into the forces shaping the health system’s future—where technology, policy, and leadership converge to improve patient outcomes and system-wide efficiency.

Medika Life Editor Gil Bashe: In examining hospital systems, we focus on how information flows within our industry and who has access to it. We still have a lot to learn. These are the first few weeks of the new administration, and we don’t know how things will unfold, how the Senate Committees will approach these discussions, or how actions will be implemented. Will we rely on Executive Orders? If that’s the case, we know where to focus our attention. You’re a remarkable ambassador for the discipline and the sector, and certainly for HIMSS, a professional association, trade association, and global NGO.

People come to HIMSS with tremendous optimism, hoping to gain insights that will make them more effective. I prefer to focus on current developments and HIMSS priorities rather than just reacting to them; that’s a different conversation. I’ll also note that the administration’s conversation around health access, cost, and priorities is still in motion.

HIMSS CEO Hal Wolf: We don’t know enough to discuss new policies and their potential outcomes. One challenge will be securing funding. While we know things will be different, we don’t know where the policies will land. Still, we know that HIMSS is dedicated to its vision and mission statements as they fundamentally relate to realizing the full health potential of every human everywhere.

We are dedicated to health equity and will stay dedicated to it. Our collaboration with governments and NGOs worldwide and our fundamental principles will not change, nor should they! We’ll work with our principles within the context of whatever comes out of the White House.

We worked well with the previous Trump administration and collaborated effectively with ONC and HHS on various initiatives. We look forward to advancing the HIMSS mission within the established parameters.

Bashe: HIMSS is far more than an annual mammoth gathering; it’s a professional society that covers the full spectrum of health information and technology – from cybersecurity to economics to professional development and government policies. Unlike other popular meetings that primarily focus on networking, HIMSS is where professionals from around the globe come to set objectives, strategies, and operational priorities. It’s 30,000 feet and 3,000 in scope.

Wolf: This morning at 6:00 a.m., I had an interesting conversation with the CEO of a successful start-up that is getting distribution now and beginning to roll. At HIMSS, we see the merging of different worlds.

We have our core population, core members of the health ecosystem– hospitals, clinics, health operations, nurse practitioners, CMIOS, CIOS, physician leaders, and administrators. This group represents a significant portion of the HIMSS membership, which includes over 120,000 members.  

On the other hand, we have the entire global app ecosystem that drives innovation and introduces new ideas. As you know, many of these ideas and innovations are driven by personal experiences. A family member encountered a situation, and they tried to solve it. Or have worked in the industry, identified a gap, and pursued it.

They often have a long list of improvements to address, and, often, they aren’t performing well financially. Their reimbursement processes are a little murky, and this uncertainty might increase in 2025.

How much time do they have to integrate innovations that don’t directly impact their outcomes, quality, access or bottom line? Because everything’s being looked at in that piece.

We need to understand that the situation changes as the market evolves. What is the critical point where innovation intersects with standard operating procedures, and what does it look like? How can information from one area influence the other? We must determine how to identify the good and the bad and how to present them to the market.

What happens at the global conference? What happens in chapter meetings? What happens in the papers that are submitted? What happens in the insights? Much of this depends on how these elements connect.

Bashe: Many diverse health information communities come together yearly at HIMSS. You have consistently made this gathering relevant. This year, a new startup section called Emerge addresses a critical need within the HIMSS community. You just started with the story about a startup enterprise. Could you share some important and innovative aspects that will be highlighted at this year’s gathering?

Wolf: That’s a pressing question, so I’ll divide it into multiple parts because it’s challenging.

We’re part of the industry, so let’s return to your original premises to find the answer. You mentioned “competing,” which refers to people competing against each other. However, you also have specific points of interest to consider.

The benefit engine can determine how much money you’ll receive in reimbursement for a particular service. However, if you’re on the insurance or payer side, the configuration may depend on whether it’s for North America or a Ministry of Health. Here, the goal is to anticipate the costs incurred in treating a patient. This perspective aligns with an actuarial professional trying to understand and guide the process forward.

I’ve observed hospital systems are starting to integrate AI functionalities, but currently, only 5 to 7% are using it effectively, from an operational standpoint,

For example, when someone walks to the front desk and says their right arm is hurting, the staff collects the information by typing it into a form. They ask a couple of questions, such as “Who’s your primary care doctor? Who’s your insurance company? Are you on managed care? Is this new? What other ailments do you have? What other prescriptions do you have?” They must ask those questions if they don’t have that information readily available. That data feeds into new algorithms on the AI side.

In the background, AI analyzes the information and makes predictive models about how long this person would be in the hospital, what resources they will consume, and how much revenue it will generate. It’s occurring in the background, without the front desk staff being aware of AI’s calculations; meanwhile, the administrator is beginning to recognize the impact of these advancements. The inbound process begins with appropriate testing, questioning, and, if necessary, into a bed.

Meanwhile, the hospital administrator or the system managing the situation assesses the resources the patient will need, whether they will need a specialist and whether the specialist will be available when needed. By the time an exam takes place, they can inform the patient about what to expect in the next 24 to 48 hours, whether they will be staying at the hospital or going home. This preparation and communication represent the positive aspects of the process.  

The dark side is that the hospital engine in the background might say, “We’re not going to get a lot of money out of this. This is not a good use of our beds/time. If we maximize profits, we should send this person on and see what the next person will bring because our algorithm told us that five people would come in with congestive heart failure, and we do make money on that.”

The person writing this down may never realize what is happening; they won’t know that the system will indicate that the hospital is full, even though there might be capacity. Instead, they will tell the person to go down the street to Acme Community Hospital, which can take care of them, explaining that their system lacks resources. That is a dark coin flip to what could happen.

Bashe: Many hospital networks are acquiring primary care practices as feeder systems in their facilities. For example, if a patient is told, “You need to do a cardiac stress test. Do you have a cardiologist?” and they respond with “No?” the primary care provider can then say, “Why don’t you let me arrange that for you.” The primary care satellite site is closing the loop on a fragmented system. While the hospital system benefits economically from the service, patients benefit, and the primary care satellite site serves as a conduit for care.

I’m always thinking about the benefits of technology in enhancing the hospital and primary care systems. Imagine a doctor saying, “You know, you’ll have many questions. I will be here to help you frame your thinking around those questions. Our system has an LLM model. Let’s call it Dr. Hal. You can ask Dr. Hal every question regarding your congestive heart failure or prostate cancer. Dr. Hal is the composite wisdom of all the experts in our system and is here to address your questions.”

The creative aspect of our discipline, combined with information, is becoming a superpower. We use data to guide our supply chain resourcing and leverage information to promptly provide patients with confidence and comfort. We ensure greater access to accurate information vetted by the system, so patients do not depend solely on Dr. Google.

Wolf: The actual value of AI is knowledge management. It allows a very broad and capable synthesis of vast amounts of data and information that no human can keep up with. For example, in the 1970s, clinicians had access to three to four journals, where editors picked what was important enough to be published. These journals had to be printed and mailed out, resulting in about 400 peer-reviewed articles per year reaching healthcare professionals. If you read one a day, you could keep up. Today, more than 10,000 articles will be published this year alone. All that information, knowledge management, and sharing will occur collaboratively, and there is no way for anyone to synthesize all that.

AI plays a crucial role in operational and clinical decision support by turning information into knowledge, with recommendations that lead to changes in operations, suggestions, and care.

In clinical care, pharmacy, or whatever path you’re on, these recommendations are communicated back to physicians with an explanation of why they are a recommendation and the source of that information.

I think part of the maturity that we’re seeing, and you’ll see at HIMSS 2025, is the evolution of AI since our session three years ago. Back then, we held a session titled, “What is AI, and what does it mean?” The panel discussed its potential application in healthcare, and at that time, chat had just been introduced, and people were starting to look at it. Some people were on stage calling for a six-month hiatus before we allowed anything to go forward.

Last year, we saw glimpses of initial uses of AI being deployed operationally, albeit only in a few hospital systems. But it was beginning to happen, and we knew that AI was in the background of devices or operational considerations. Where would the benefit engines come from? The algorithms were starting to be built, and we had a particular point of looking out for biases. We started talking about biases within AI and realized that no matter what you do, there will always be some biases. It’s unavoidable. What was the source information for AI, and how do I ensure I utilize it to the best of my ability?

You’ll see the presentation of how people are using it on a scale. What are examples of its success, and what are some of its limitations? Numerous applications are set to emerge. You’re going to see them on the floor, where people are using components of AI in the background to produce better products that are more efficient and can guide operations as well as at-home care, and all those pieces are being brought forward. The common link between it and your point is on the information side of the house. How good is the starting information, and how broad does it go? Where is the opportunity from a linking standpoint?

To achieve this, a private-public partnership is essential. If you’re looking at algorithms and information that utilize global data that gets turned into global information, it has an impact. Most healthcare systems around the globe are publicly held. They’re not privately held. The United States is an aberration due to its vast amounts of privately held institutions versus publicly held ones.

Bashe:  Are you seeing more of that regarding the technology being used proactively?

Wolf: Yes, and that’s a good thing. We’ve always wanted to see that proper reimbursement takes place and proper services rendered. Many things in a system can get missed, but not an overwhelming amount.  If hospital systems perform well, they typically operate on a 2 percent to three percent margin, but many run at a loss, making proper reimbursements difficult. Large actuarial departments played a key role in the past, with various organizations providing revenue support, which was a huge thing even 15 years ago. However, over time, those efforts began to converge.

The real opportunity lies beneath the surface. It must coincide with an understanding of the care that was delivered. Right next to that benefit realization is the value proposition. What was the quality of what was rendered? Was the care appropriately given? Did we miss something in the diagnosis?

Bashe: One of the things that I worry about is not New York City or Los Angeles. Medical centers such as Mount Sinai, NYU Langone, Weil-Cornell, Columbia Presbyterian, and Memorial Sloan Kettering, much like their counterparts in Boston, Chicago, and the Bay area, provide excellent care. However, in rural America, someone can live three hours from a tertiary care center.

Your approach of using information to improve the care of almost 29 percent of the US population applies, I think, to other nations where people live far from centers of excellence. What are your thoughts about devices, wearables, remote patient monitoring and information, and protecting the information from your standpoint?

Wolf:  Wearables and home monitoring have transformed patient engagement, making health data more immediate and actionable. It’s fascinating. My wife and I compare our Oura daily. How did you sleep? How’s your heart rhythm? We’re finding the features and working through them. She lives anonymously. We are very engaged in our health. How far did we walk? What was our heart rate? Let’s do the 6-minute walk today and see. Were you snoring last night?

All of that is going on, and that’s an engagement level. The information flows from me to my ring, and then my ring says, do you want to share it with Apple? I said yes, and my wife said no; she didn’t want it to flow to another company. Apple will know how well I sleep – I don’t worry about it. If they want to dive into it, there is a profile about me and my general health. They could also derive that from the stuff I buy and the credit card information. That’s always been the case.

If you remember, back in the 1980s, we were already using demographic data with Donnelly overlays. I worked for Time Warner in the early 1990s when Time magazines were delivered to your door. The Time magazine that arrived at your next-door neighbor was different from yours—not the content, but the cover and the ads in the back. You may have gotten an ad for a sports car, and your neighbor may have gotten one for a minivan.

It was specifically designed based on the Donnelly reports, which provided insights about the household. We’re starting to shape recommendations at the personal level of the care an individual should receive.

Why wouldn’t a physician or a clinician want every piece of information on this Oura ring to be included in a patient’s profile? This information would help complete the picture needed to utilize sophisticated knowledge management systems, tapping into tens of thousands of research papers and combining that data with the person’s unique health details. The richer that information becomes, the more accurate it becomes, the more mistakes it makes, the more positively it helps the next person.

Bashe: Often, when I speak to doctors and nurses in the health system, we talk about the Electronic Medical Record (EMR). They’re candid: “We have an EMR system—it’s not perfect, we know that, and it’s getting better and better.” Yet, they often say, “Did you read that patient’s EMR data?” and then they’ll say, “I don’t have time to read the EMR.” While best practices come from committees, you play a unique role as an advisor to corporations. You’re the sounding board for major corporations, whether AWS, Epic, Microsoft, or Oracle. I’m sure they will listen to you because you’re the voice of the global community.

Wolf: We don’t have a dog in the race against them as a competitor.

Bashe: As a not-for-profit society that operates at a global NGO level, when you look at your role and the challenges you face, how does HIMSS address constant sector transformation? HIMSS and its members are constantly evolving because you represent applied information. The system is getting more interesting and more creative.

Look at the challenges that HIMSS owns and represents and your mission, which is obviously to improve access to care. As the organization’s leader, you’re clear and committed to this role, but you’ve seen difficulties implementing cultural or systemic changes.

What’s your guidance for the community? Please don’t take out a ruler and slap people on their hands. You’re obviously about supporting the system’s evolution, making it better. Can you share insights on how you’re filtering down best practices within this evolving landscape? How do you reflect on these challenges that arise and guide systems to understand that care is delivered to the front lines and is not always in hospitals? It’s specialists or primary care—physicians in their little offices worldwide.

Wolf: This is precisely what we discuss daily at HIMSS, and it’s central to our global work. Let’s walk through our view of the ecosystem and how we influence what you just related to because it’s our core.

Hospital systems – or, more importantly, governments worldwide – including our own, recognize their fundamental responsibility to care for their populations. Let’s set the United States aside for a second.

Ministries of Health in countries around the world are accountable for the well-being of their citizens. We’ll talk about citizens for a minute. The people living within their country want a healthy population, which improves the economy. They’re smart enough to know that a healthier population, or one cared for, efficiently reduces the constant increase in costs within healthcare systems. No one is looking to save money; instead, the goal is to slow the escalating costs of healthcare systems, which seem to rise every year.  

Information is the driver behind everything, but to your point, the combination of people, processes, and technology shapes the outcome. Technology is rarely an issue here; the challenge lies in implementing and changing culture. The pandemic forced a significant global cultural change, and while it may seem that it’s deeply in our rear-view mirror, its impact is still felt. Telemedicine, the idea of using information, and the idea of remote care to alleviate the pressures on the front line became a standard feature, and people recognize that.

We see the impact in our relationships with organizations like the WHO in Europe. Take Romania, for example, where we just signed an agreement to help them develop a strategic plan to deliver digital health transformation. HIMSS is focused on four major points.

1. First is digital health transformation.
2. Second is the deployment and utilization of AI as a tool.
3. Third is cyber security to protect that information and ensure that it works for the betterment of their ecosystem with less hassle.
4. Fourth is workforce development, which trains people to understand these tools before they can utilize them to their fullest extent.

Those are our four main areas. When we think about digital health transformation, we start with the HIMSS maturity models from five to seven years ago.

Back then, our maturity models were a checklist of technology. Do you have that technology? Are you wired? That used to be the baseline, what we now consider table stakes. It’s not table stakes anymore.

We’ve transformed our maturity models to reflect quality, access, correctness, and fundamental value. How are you using the information? How does it improve the flow?

From an IT standpoint, we began looking at our maturity models like a stack. It starts with the information layer. What does the infrastructure look like? How is it laid out? How does your data need to be laid out? Where does the electronic medical record go on top of that? How do those two pieces feed into each other? How do you utilize the radiology and the pictures that are in there? How does that flow? What’s your analytical layer? How does this work?

Where are you getting your information, and how are you handling your analytics? How does that tie itself back into the infrastructure? How does that information flow from your reporting back into your EMR and the data layer? How does that data layer tie in when discussing the imaging ecosystem? What’s your continuity of care, the CCMM? How does it flow across the board to ensure you’re not dropping a patient?

We’ve created a stack of maturity models that form the foundation of how information flows from the patient across hospitals, clinics, and homes, wherever the case is provided, to ensure you can keep up with them. And we present these maturity models not just as a technology checklist. Anyone can do that—it’s not meaningless—but anyone can do that. The true focus is on how you use these technologies.

How do you ensure that the relationship between the patient and pharmacy utilization, as well as the benefit realization, is maintained? And how does all this tie together?

Whether it’s community service, a hospital system, or a home, what we’ve created in those stacks is a blueprint that any hospital system, country, or large-scale region can use to identify the technology needed and deploy it for its maximum benefit. 

People do assessments in hospital systems. For HIMSS members in the United States, these assessments are part of the membership, allowing them unlimited access to evaluate their systems. They can conduct these assessments online, check their status, and aim for levels 6 and 7, which is when all those benefits kick in. That’s when we do our validations.

We also do white papers, thought leadership, and HIMSS events, panels and educational programs. More than 300 academic programs are coming up at HIMSS in 2025, with more than 150 offering CE credits.

But these experiences are all based on the output, what worked, and what didn’t work. As you know, learning from others’ mistakes is just as valuable as learning from their successes. Some of the most impactful lessons come from those who try something, fail, and then fix it.

That’s where HIMSS and advisory services come in. We’re presenting the aggregated global knowledge of what’s working and what isn’t.

Most ecosystems don’t work the same way the United States does because most don’t have the same amount of money invested in it. We draw from many healthcare systems- from the U.S., to Romania, Italy, Germany, Singapore, Indonesia, Malaysia and Australia. We learn from all these countries, bring it together in our membership, and figure out what we have learned. How does it impact the models? We do these reviews in a constant session. That’s how we make the society work.

Bashe: It’s a brilliant use of human capital and composite wisdom. As we’re gearing toward the end of our conversation, I wanted to ask you about the Emerge Innovation Experience– this is a first-time gathering, but the concept of start-ups at HIMSS is nothing new. What’s different now is that you’ve recognized that start-ups are a unique culture with unique needs. You’ve assembled a cohort of leaders dedicated to helping these start-ups succeed. What are your expectations from Emerge?

Wolf: First, I’m very interested in the outcome of Emerge. This is the first time that we’re going to try to bring that mesh point I mentioned earlier, where innovations meet operations. They’ve chosen some excellent examples of what can come forward. I think it’s got the right practicality and innovative forethought. From what I’ve heard from people involved in it and talking to people on the committee, I’ve listened to everything from “Wow! This is fantastic and very innovative!” to “It could have been stronger.”

If I talk to heavy innovator startups, they reply that it doesn’t go far enough and could be really “wow.” Meanwhile, those focused on operations often reply that it’s “really pushing the edge.” What that tells me is that it’s in the right mesh point.

What I’m curious to see is how it is received. Many smart people have been working on it, focusing on what will have the biggest impact on operations and be ready for prime time tomorrow, especially in areas like AI utilization and operational impact. What is one step beyond? We also have an incubator ecosystem there.

The Emerge Innovation Experience will be unique, and I look forward to that outcome.

Bashe: I always value your candor.

Wolf: Sometimes, I can get criticized for it, but I believe in absolute transparency. The beautiful part about thought leadership is that we share these thoughts, which makes HIMSS thrive. Transparency is a strength in a positive society. If we’re not transparent with each other, we can’t advance. My grandfather taught me a long time ago that the three most essential phrases in business are “I don’t know, I’ll find out, and I’ll get back to you.” “I don’t know” is critically important.

What’s beautiful about healthcare is that you learn something new every day. It’s impossible to be in the health sector without learning something new every day unless you don’t ask a single question, read nothing, or stay in a room and shut the door.  

Just today, I learned something about HIMSS. I didn’t know because I was asking about a process. A question was raised, and I followed the thread through the organization and found one I’d never seen before, which was exciting.

I appreciate the philosophical and real questions you’re asking. We’re excited about HIMSS 2025 and the learning opportunities it will offer. It’s also about the big picture of what’s happening globally. We call it the Global Conference because it brings together Ministries of Health and NGOs worldwide. It all comes together. This is our largest membership meeting, and we’re thrilled that there’s at least a 35% increase in people signing up for HIMSS membership compared to last year.

Bashe: I’ll be attending this year. As always, thank you for the in-depth exchange. *****

In this insightful conversation, Hal Wolf, President and CEO of HIMSS, explores the critical forces shaping the sector’s future. As industry and governments navigate a rapidly evolving policy landscape under a new administration’s eyes, hospital systems, startups and policymakers must adapt to changing regulations, funding challenges, and digital transformation. Wolf highlights HIMSS’ role as a global leader in uniting a diverse ecosystem to advance health equity, interoperability, and patient-centered care.

A key theme of the discussion is how data and AI are transforming payer, provider and product innovation operations – how information can improve people’s lives. Wolf explains how AI-driven predictive models are integrated to optimize patient care and resource allocation. However, he also warns of ethical concerns—such as the potential for financial-driven decision-making that could prioritize revenue over patient needs. HIMSS plays a vital role in ensuring there is a balance between digital health innovation aligns with quality care and equitable access.

As digital tools, AI, and large language models (LLMs) become more integrated into healthcare, Wolf and Bashe discuss how these advancements can empower providers and patient-enhancing decision-making, improving operational efficiency and offering trusted, system-vetted health information.

As HIMSS prepares for its annual global conference, Wolf emphasizes its role in shaping industry priorities. HIMSS is not just an event; it’s a society that defines strategies, policies, and innovations that drive the future of health. With an expanding ecosystem of startups and industry veterans, HIMSS remains a pivotal force in bridging technology, policy and patient care.

The post The Future of Health Information and Innovation: A Conversation with HIMSS CEO Hal Wolf appeared first on Medika Life.