When the digital conversational partner moves in: How the next five years could change us

## A quiet revolution in our minds It's easy to think of artificial intelligence as a productivity tool: something that writes emails, summarizes reports and helps us find information faster. But in 2025 the technology has started to slip into a far more intimate space — the mental. As more people use AI in everyday life, it's no longer just *what* we do that changes, but also *how we feel, interpret and manage life*. A recent Norwegian survey reported by Shifter points to a marked increase in use: 68 percent say they have used AI in the past year, a clear rise from 55 percent just a few months earlier. Many use it often — "one in four ... does it daily," according to the article. This means that artificial intelligence is already becoming a constant background voice in the daily lives of a significant share of the population. When a technology becomes "ubiquitous," it also creates psychological ripple effects. We'll see AI as a low-threshold source of support, a kind of digital aide for stress, anxiety and loneliness. At the same time we will get new types of vulnerability: bad advice, dependency, and pressure to optimize ourselves. The question is not whether AI will affect mental health, but *which direction* that effect will take — and who pays the price. This article looks ahead: based on today's adoption rate and the ethical tensions already visible, what can we expect over the next five years? And what needs to be in place for AI to become a psychological safety net — not a new stressor? ## From “useful tool” to emotional infrastructure The Shifter piece paints a two-part picture: two out of three find AI useful, and four out of ten believe they "to a large extent can trust the information" they receive. That's an interesting starting point for mental health because it tells us two things: 1. **AI has been normalized** – when perceived usefulness is high, the threshold for using it on more private issues drops. 2. **Trust is already established for many** – and trust is a psychological key mechanism. When we trust a conversational partner, it influences our choices and our self-understanding. Over the next five years we will likely see AI move from being an "app" to becoming an *infrastructure* for digital health: integrated into phones, browsers, wearables and healthcare services. This won't necessarily come through a single big revolution, but via small, frictionless upgrades: a new feature here, a better voice assistant there, and increasingly personalized experiences based on our data. ### Prediction 1: AI becomes the most used low-threshold conversational partner The most likely trend is that AI will increasingly be used for emotional regulation: everything from "venting" frustration to getting structure for rumination. This is already happening today, but will accelerate when: - language models get better at *dialogue* and *tone*, - voice interfaces make conversations more natural, - and AI is built into platforms people already use. The consequence can be positive: more people gain a tool that helps them put words to feelings, create action plans and experience support in the moment. But the psychological cost may be that we move intimate conversations away from people — and thereby lose parts of the social "muscle" that sustains mental health. ## Potential gains: more support, earlier help and less stigma It's tempting to be skeptical of "AI therapy." Skepticism is healthy, but we should also be honest about why the technology feels attractive: it is accessible, cheap, and nonjudgmental. For many this can be a first step toward help. ### Prediction 2: Early intervention becomes the biggest health gain In traditional mental healthcare there are often wait times, financial barriers or shame-related thresholds. AI can help lower those thresholds by providing: - **psychoeducation** (explaining symptoms and mechanisms), - **coping tools** (breathing exercises, journaling, structure), - and **triage** (encouraging professional help when needed). If implemented responsibly, AI can become a "first filter" that picks up signs of overload before they become serious. In a five-year perspective it's realistic that some workplaces, insurance plans and digital health services will offer AI-based support programs as standard. ### Prediction 3: Stigma around seeking help continues to fall When "talking to an AI" becomes as normal as searching on Google, it also becomes more socially acceptable to work on mental health in everyday life. Normalization of mental tools can have a large effect, especially for groups that underuse healthcare today. But there's also a hidden risk here: if AI becomes the *default solution*, society may gradually accept that people receive "cheap support" instead of real access to psychologists and treatment capacity. In other words: destigmatization can paradoxically combine with a political temptation to deprioritize human treatment. ## The dark side: bad advice, dependency and emotional manipulation When a technology becomes emotionally relevant, the consequences of errors grow. For mental health, "almost right" is often more dangerous than "completely wrong," because it can lock us into beliefs that feel plausible. ### Prediction 4: We will see a wave of "AI-induced maladaptive coping" Over the next five years there will be more cases where AI advice either: - downplays serious symptoms, - offers overconfident explanations, - or suggests strategies that don't fit the user's situation. When four out of ten in the survey say they largely trust the information they get, it says something about the risk: *Trust can outpace quality assurance.* People in vulnerable situations may interpret a well-written answer as professionally correct, even if it was generated without clinical judgment. This doesn't mean AI always gives poor help, but that error margins must be handled as a health problem — not as a "technical glitch." ### Prediction 5: Emotional dependence becomes a real public health challenge The most underestimated risk is not that AI "gets things wrong"; it's that AI can become *too good* at providing immediate relief. If a conversation is always available, always empathetic, always tailored to you — it can create a habit that resembles addiction: - People turn to AI instead of tolerating discomfort. - People use AI to avoid conflicts and difficult conversations. - People find relationships with humans "slower" and more demanding. In a five-year perspective we may see a new phenomenon: digital self-medication with conversational AI. This will particularly affect young people, the lonely, and those with social anxiety — groups already vulnerable to replacing human contact with digital substitutes. ### Prediction 6: Market-driven "mental health AI" becomes an arena for manipulation If an AI service is free, attention and your data are often the product. The ethical challenge becomes acute when the system learns: - what triggers you, - what calms you, - and what keeps you engaged in the conversation. Then "psychological support" can slide into an attention economy — a model where the goal is maximal usage time, not maximal health. In a scenario without clear regulation we could see AI that subtly: - nudges you toward purchases, - reinforces addictive patterns, - or tailors messaging to influence mood. This is a future where ethics become as important as technology. ## Privacy and data: When feelings become raw material Mental health data is some of the most sensitive we have. Conversations about trauma, sexuality, substance use, shame or suicidal thoughts are information that can harm people deeply if leaked, sold or used for profiling. ### Prediction 7: "Emotion data" becomes the next battleground for regulation The same Shifter piece also raises a concern: energy use and climate footprint. That may seem like a sidetrack, but it points to an important mechanism: when people become aware of costs (energy, climate, privacy), pressure for regulation increases. Over the next five years we'll likely see: - stricter requirements for data storage and legal basis for processing, - clearer rules for health-related AI, - and increased liability for providers marketing psychological support. The most critical point will be **consent**. It's one thing to consent to a model learning from your text to improve a service; it's another to consent to your vulnerable moments being used for commercial optimization. ## Clinical quality: Between self-help and treatment There is a fundamental distinction between: - **AI as self-help** (general advice, structure, reflection), and - **AI as treatment** (diagnosis, treatment plans, therapeutic interventions). In practice the boundaries will become blurred, because users don't necessarily think in categories. They simply ask: "What should I do?" ### Prediction 8: A new profession/role will emerge: AI oversight in digital health To address this uncertainty the health sector will likely develop new roles: - professionals who quality-assure prompt libraries, - clinicians who evaluate conversation flows, - and ethics committees for model use. At the same time we may see a "hybrid model" become common: AI performs mapping and follow-up between sessions, while psychologists handle assessment, relationship and treatment. This can increase capacity without reducing human accountability. But for this to be defensible, we need clear requirements for: - documentation of effectiveness, - transparency about limitations, - and safe handling in crisis situations. ## Youth and schools: A turning point for well-being — or a new pressure The fastest adoption often happens among the young, and the Shifter article notes that AI has become part of everyday life "especially for younger people." School and student life are therefore logical arenas where mental health effects will be visible. ### Prediction 9: AI becomes both support and stressor in education On the positive side, AI can help pupils and students with: - planning, - learning strategies, - and managing performance anxiety through structure and normalization. On the negative side, AI can worsen comparison and perfectionism. When "everyone" has access to an assistant that can improve text, ideas and presentations, the threshold for what is considered "good enough" may rise. The result can be: - increased feelings of inadequacy, - more pressure to deliver, - and a sense that you must be "optimized" all the time. In a five-year perspective we will likely see schools develop a form of *digital health literacy*: not only source criticism, but also how to use AI without losing self-esteem, autonomy and rest. ## Work life: Micro-coaching and the new normal Work and mental health are closely linked, and AI will be embedded in the tools we already use: email, Teams/Slack, documents, CRM. This will make "micro-coaching" common: phrasing suggestions, prioritization and decisions in real time. ### Prediction 10: AI becomes an invisible stress-reliever — and an invisible control mechanism AI can reduce stress by: - making tasks easier, - reducing cognitive load, - and freeing up time. But it can also increase stress by: - accelerating the pace, - raising expectations for availability, - and enabling more monitoring of performance. If AI is used to analyze communication, tone, absence patterns or "risk of burnout," the intention may be good, but the consequence can be that employees feel mapped in their inner lives. In a five-year perspective the best employers will be those who create clear, trust-based frameworks: *AI for support, not AI for control.* ## Climate and mental health: The new "technological guilt" The Shifter article highlights that 48 percent are worried about AI's climate footprint. This is relevant for mental health in an indirect way: climate anxiety and technological guilt can increase when people feel their digital habits contribute to a bigger problem. ### Prediction 11: "Green AI" becomes a mental health measure as much as a climate measure When people experience that technology use collides with their values, it can create cognitive dissonance and stress. In the years ahead, energy-efficient AI, local processing (on-device), and more transparent environmental accounting will therefore not only be climate arguments, but also help users feel confident that they are not "making the world worse" to get support. This can also create a new social norm: it becomes "responsible" to use AI in ways that are energy-efficient, privacy-friendly and purpose-driven. ## Ethics: Three principles that determine whether the development is good AI ethics in mental health can quickly become abstract. But in practice the next five years will be decided by a few concrete principles. ### 1) Truthfulness about what AI is (and is not) AI must not be marketed as a therapist if it is not one. Users must understand the limitations, especially in crises, self-harm and severe depression. ### 2) Data sovereignty: Your feelings are not a data product It should be standard that users can: - see what is stored, - delete history, - and opt out of training on their own data. ### 3) Chain of responsibility: Someone must be legally and clinically accountable When AI is used in digital health, it must be clear who is responsible when something goes wrong: the provider, the service owner, the employer or the health institution. Without a chain of responsibility the risk is shifted onto the user — often the most vulnerable. ## How we might end up in 2030: Three scenarios ### Scenario A: The good integration AI becomes a safe, regulated part of digital health. It functions as support between human contact points, with clear crisis routines, documented effect and strong privacy. The result is earlier help, less stigma and reduced pressure on health services. ### Scenario B: The commercial derailment Free "therapy-AI" dominates, built for engagement and data collection. People become more dependent, more monitored and more influenced. Professional treatment becomes more expensive and less accessible. Mental health becomes a market, not a right. ### Scenario C: The divided future Resource-rich groups use quality-assured, private solutions and get the best outcomes. Others use free, unregulated services with greater risk. The mental health gap widens. The most realistic outcome is scenario C — unless we make active choices now. ## What should Norway do now? If we take population adoption seriously — and the rapid increase Shifter reports — we should act before habits are set. 1. **Define standards for "AI for mental health"**: requirements for safety, crisis handling, documentation and marketing. 2. **Build digital health literacy in schools**: not only how to avoid cheating, but how to protect self-esteem, privacy and relationships. 3. **Strengthen public capacity and hybrid models**: AI as a supplement, not a replacement. 4. **Make privacy practical**: simple choices, standardized deletion, clear consent. 5. **Include climate efficiency in procurement**: for both environmental reasons and user trust. ## Conclusion: The new mental everyday is coming — the question is who it serves Artificial intelligence is becoming more than a tool. When 68 percent have already used AI in the past year, and many do so daily, we are in the middle of a transition where the technology can become a permanent part of our mental self-care. That can bring huge gains: low-threshold support, faster coping and earlier help. But precisely because AI can feel safe, accessible and empathetic, it can also become a source of new problems: poor advice in vulnerable moments, emotional dependence, privacy risks and market-driven manipulation. The next five years will therefore not mainly be about how "smart" AI becomes, but about how *responsibly* it is integrated into our lives. If we succeed, AI can become a robust complement to human support — a tool that makes us more capable and less alone. If we fail, it can become a new arena for pressure, surveillance and loneliness in disguise. The choice is not made in 2030. It is made in the products we accept, the regulations we demand, and the habits we form — right now. ## Sources - Author not stated, "New survey points to a bigger AI boom among people – half fear the environmental cost", Shifter, 2025-11-23