Hanoi (VNA) - The wave of conversational AI applications is giving rise to a new economy — the "digital companionship economy" — in which emotion, attentive listening, and connection become commodifiable values. The market reached 28.19 billion USD in 2024, with a projected growth rate of 30.8% per year, heading toward more than 140 billion USD by 2030.
The core driver is not technical — it is a social wound: 39% of adults worldwide regularly feel lonely (YouGov, 2025), rising to 49% among Generation Z. This article analyses the trend through a digital and quantum-technology lens, assesses its application potential in Vietnam, and raises ethical questions about the boundary between support and replacement in human–machine relationships.
I. INTRODUCTION: DIGITAL LONELINESS AND THE COMPANIONSHIP MARKET
In the third decade of the 21st century, artificial intelligence (AI) no longer serves merely as a technical tool. From customer-service chatbots to deeply personalised virtual assistants, AI has entered the most intimate space of human life — emotion, conversation, and the need for connection. This transformation has not occurred in a vacuum; it is grounded in a measurable social reality that spans generations and geographies.
According to a Grand View Research report, the AI companion market reached 28.19 billion USD in 2024, with a projected growth rate of 30.8% per year, heading toward more than 140 billion USD by 2030. The core driver is not technical — it is a social wound: 39% of adults worldwide regularly feel lonely (YouGov, 2025), a figure that rises to 49% among Generation Z. These statistics point to a structural demand that the technology sector has moved swiftly to address, giving rise to what this paper terms the "digital companionship economy."
This article analyses the digital companionship economy through a dual lens: the technical capabilities that make it possible, and the ethical imperatives that must guide its development. Special attention is given to the Vietnamese context, where AI adoption is accelerating at a pace that demands both enthusiasm and critical reflection.
II. VIRTUAL ASSISTANTS: FROM TOOL TO RELATIONSHIP
Platforms such as Replika, Character.AI, and Microsoft Xiaoice have pioneered the "companion virtual assistant" model, in which users do not merely ask and answer, but build an ongoing relationship — naming the AI, recalling shared history, and feeling attachment over time. This deep personalisation has created a new consumption behaviour: users pay recurring fees not to "unlock features" but to maintain a stable emotional experience.
The line between tool and relationship is progressively blurring. Survey data indicate that 28% of users have shared personal emotions with a chatbot at least once, while 17% say they sometimes prefer staying home to talk with AI rather than meeting friends in person (YouGov, 2025). AI is no longer a temporary substitute — it is directly competing with traditional social relationships.
This shift carries profound implications for how we conceptualise companionship, care, and social bonds. When an algorithm can provide consistent, patient, non-judgmental engagement, the human propensity to form attachments — irrespective of the counterpart's sentience — becomes both an opportunity and a vulnerability.
III. TECHNICAL FOUNDATIONS AND THE QUANTUM ADVANTAGE
From a technical perspective, the development of Large Language Models (LLMs) such as GPT-4, Gemini, and Claude has enabled virtual assistants to achieve interaction levels approaching natural human dialogue. Long-term memory, multi-step reasoning, and personalised tone adjustment are the core capabilities that directly produce the "sense of reality" users experience. The technical trajectory of these systems suggests that the gap between perceived authenticity and actual human conversation will continue to narrow.
At IMG Innovations, we approach AI virtual assistants not merely as software products but as integrated cognitive systems. By combining quantum cloud computing with behavioural AI models, next-generation assistants are capable of processing complex context, detecting emotional nuance, and personalising responses at scale. Quantum computing introduces qualitative changes in processing speed, pattern recognition, and probabilistic modelling that classical architectures cannot replicate — opening application potential in education, mental health support, and knowledge-worker assistance.
The convergence of three trends makes the current moment particularly significant: (1) ever-increasing computational power driven by advances in quantum computing; (2) increasingly sophisticated language models capable of deep contextual understanding; and (3) the growing human need for emotional connection in an accelerating digital society. These trends do not merely reinforce one another — they create systemic conditions in which AI companionship becomes a mass-market phenomenon rather than a niche product.
IV. AI ETHICS AND DATA PROTECTION
The ethical dimensions of the digital companionship economy demand careful scrutiny. Sociologist Sherry Turkle has warned that "technology promises connection but delivers loneliness" — a paradox that grows more urgent as AI encroaches on psychological spaces traditionally belonging to human relationships (Turkle, 2015). Dr John Torous of Harvard Medical School has similarly emphasised that while AI can expand access to mental health care, it cannot replace human clinical judgement and ethical responsibility in therapy (Torous et al., 2021).
Data protection represents an equally pressing concern. Survey findings reveal that 65% of users express privacy concerns when using AI companion applications (YouGov, 2025). Every conversation — however intimate — can become input data for commercial systems: stored, analysed for behavioural patterns, and used to optimise user experience for business objectives. The asymmetry between user vulnerability and commercial incentive creates conditions ripe for exploitation.
This is a critical data-ethics challenge that any national or corporate AI strategy must address. The intimacy of companionship AI generates uniquely sensitive data — not credit card numbers or browsing habits, but emotional confessions, personal fears, and relational histories. Existing data-protection frameworks may be insufficient to govern the depth of this new data category.
V. THE VIETNAMESE CONTEXT
Vietnam presents a compelling case study in AI adoption dynamics. According to the e-Conomy SEA 2025 report by Google, Temasek, and Bain & Company, Vietnam ranks among the countries with the highest AI adoption rates in Southeast Asia. Approximately 78% of Vietnamese internet users have used AI tools at least once; more than 30% maintain daily usage habits — particularly among young urban populations. AI has entered a phase of "normalisation" in Vietnamese digital life.
Technology enterprises are deploying virtual assistant solutions across customer service, education, and healthcare, laying the groundwork for deeper applications. In parallel, the national AI strategy to 2030 identifies artificial intelligence as a core technology, emphasising the role of innovation alongside risk management and personal data protection. Recent scientific forums have begun formally incorporating AI ethics and social impact into official discourse — a promising signal that the regulatory and academic ecosystem is engaging with the social dimensions of the technology.
Vietnam's combination of a young, digitally fluent population, high smartphone penetration, and growing urban loneliness patterns suggests that the digital companionship economy will find fertile ground in this market. This makes it all the more important that Vietnamese policymakers, developers, and civil society establish robust ethical frameworks before, rather than after, widespread adoption.
VI. DISCUSSION: TECHNICAL AND ETHICAL OUTLOOK
The challenge confronting developers, regulators, and researchers is not whether AI can simulate companionship — the technical capacity to do so is already established. The more fundamental question is: what goals do we want AI to serve? The answer will determine whether the digital companionship economy becomes a force for human flourishing or a mechanism for the commercial exploitation of loneliness.
If virtual assistants are designed with principles of transparency, privacy protection, and respect for clinical boundaries, they can become genuinely welfare-enhancing tools — extending access to emotional support for populations underserved by traditional mental health infrastructure, providing cognitive companionship for the elderly, and enabling personalised learning at scale. Conversely, if optimised purely for engagement metrics and recurring subscription revenue, they will exploit rather than heal the loneliness of the twenty-first century.
The path forward requires a multi-stakeholder approach. Developers must embed ethical design principles from the outset, not as compliance afterthoughts. Regulators must develop data-governance frameworks adequate to the sensitivity of emotional data. Researchers must produce independent evidence on the psychological effects of sustained AI companionship. And users must be equipped with the digital literacy to understand the nature of the systems they are interacting with and the commercial interests those systems serve.
VII. THE URGENT IMPERATIVE: TRAINING IT PROFESSIONALS TO COLLABORATE WITH AI, NOT MERELY TO USE IT
Among the most underaddressed challenges of the digital companionship economy is a fundamental gap in how AI is understood by those who deploy it. The dominant paradigm in IT workforce development treats AI as a tool to be operated — a powerful instrument to be configured, integrated, and maintained. This framing is dangerously insufficient. As AI systems become embedded in the psychological and social fabric of daily life, the professionals who build and manage these systems must develop a genuinely different relationship with the technology: not operators of a tool, but informed collaborators in a shared enterprise with real human consequences.
There is a meaningful distinction between using AI and understanding it. A professional who uses AI can prompt it, deploy it, and measure its outputs. A professional who understands AI can reason about its failure modes, recognise the assumptions embedded in its training data, anticipate the social effects of its design choices, and advocate for architectural decisions that serve human welfare rather than simply optimising for engagement. The first kind of professional scales a product; the second kind bears responsibility for what that product does to people.
This distinction has direct implications for curriculum design and professional development. Technical education in AI must move beyond API integration, model fine-tuning, and performance benchmarking. It must incorporate the social science of human–computer interaction, the ethics of data collection and consent, the psychology of attachment and dependency, and the regulatory landscape governing AI in sensitive domains. An IT professional working on a mental health companion application, for instance, must understand not only how the language model generates responses, but why certain response patterns may reinforce dependency, how privacy law governs the storage of emotional disclosures, and what clinical boundaries must be respected even when the system has no clinical licence.
Vietnam's position as a high-growth AI adoption market makes this imperative especially urgent. The speed of deployment in customer service, education, and healthcare means that design decisions are being made — often under commercial pressure — before the workforce possesses the conceptual frameworks to evaluate their consequences. Closing this gap requires investment at multiple levels: universities must revise AI curricula to include ethics, social impact, and human-centred design as core rather than elective subjects; enterprises must create internal cultures in which engineers are encouraged to ask not only "can we build this?" but "should we build this, and in this way?"; and professional associations must develop standards of competence that treat AI literacy — in its full, critical sense — as a requirement for practice in sensitive domains.
Ultimately, the goal is not to produce IT professionals who are more cautious about AI, but professionals who are more genuinely knowledgeable about it. Deep knowledge of AI — its capabilities, its limits, its social entanglements, and its ethical stakes — is precisely what enables a practitioner to deploy it responsibly and innovatively. The digital companionship economy will be shaped by the quality of understanding brought to it by those who build it. Training that understanding is not a soft add-on to technical education; it is the foundation on which trustworthy AI systems are built.
VIII. CONCLUSION
AI virtual assistants are not merely technology products — they are mirrors reflecting humanity's deepest needs: to be heard, to be understood, and to be accompanied. The digital companionship economy is not a passing trend; it is the structural response of a technologically advanced but increasingly atomised global society to a genuine social deficit.
The question is not whether AI can meet those needs, but how we shall shape this technology so that it serves human dignity rather than exploiting human vulnerability. This is simultaneously a technical challenge — requiring advances in safety, alignment, and interpretability; a legal challenge — demanding new frameworks for emotional data governance; an ethical challenge — calling for principled design and accountability; and a cultural challenge — requiring societies to reflect honestly on the social conditions that have made artificial companionship a mass-market phenomenon.
All stakeholders — developers, regulators, researchers, and users — must collectively address these challenges. The digital companionship economy will be shaped by the choices made in the coming years. The central task is to ensure that those choices are guided by a clear-eyed commitment to human welfare, rather than by the path of least resistance toward commercial scale./.
KEY FIGURES
| 28.19 Billion USD AI companion market size, 2024 | 39% Global adults experiencing regular loneliness (YouGov, 2025) | 78% Vietnamese internet users who have used AI tools (e-Conomy SEA, 2025) |
| 30.8% CAGR Projected annual growth rate to 2030 | 140+ Billion USD Projected market size by 2030 | 65% Users with privacy concerns about AI companion apps (YouGov, 2025) |
