Artificial intelligence is entering a new phase, transitioning from automation and task-based chatbots to AI companions designed for emotional connection, personalization, and ongoing dialogue. As these companions gain traction across demographics and become daily touch points for millions of users, they’re opening up an emerging frontier for marketers.
This FAQ breaks down what AI companions are, how they differ from traditional chatbots, why they’re reshaping consumer loyalty, and what marketers need to prepare for as engagement, monetization, and advertising opportunities begin to take shape within these conversational environments.
An AI companion is a conversational digital persona designed to offer users emotional support, entertainment, and assistance. Companions often take the role of friend, coach, or partner and can be customized based on the user’s preferences and goals.
Several companies specialize in AI companion products, including customizable chatbot characters from Character AI and Replika and wearable devices for social interaction like Friend. The availability of these products is rapidly increasing: Companion app releases grew from 16 to 128 options between 2022 and 2025.
Many people also form companion-like relationships with mainstream AI chatbots like ChatGPT and Meta AI. These chatbots are built for practical or informational purposes, and many initially use them to assist with various tasks, while a sense of companionship develops organically as a byproduct of their utility and repeated interactions.
Traditional, non-AI chatbots focus on narrow task execution and are useful for simple requests, relying on basic natural language processing (NLP) like keyword matching. They handle narrow tasks efficiently but lack deeper emotional awareness and adaptability.
By contrast, AI companions and agents use large language models (LLMs) to interpret context, intent, and nuanced language. As Microsoft notes, companions and modern AI systems differ from traditional chatbots in personalization, complexity, and adaptability; they are capable of responding in ways that feel intuitive and contextually aware.
AI companions extend this even further. Built on the same LLM foundations, companions emphasize computational emotional intelligence to adapt personalities and behaviors over longer periods of time. For people using them for emotional support or relationship-like interactions, this distinction is especially pronounced: The companion experience hinges on persistent, highly personalized engagement, and conversations are continuous—unfolding over days, weeks, or months rather than resetting with each new interaction.
The most promising monetization models for AI companions are still taking shape, but several clear paths are emerging. Subscription tiers are one of the most dominant models used by companion platforms like Replika and chatbots like ChatGPT. Higher tiers offer deeper personalization and priority access.
Freemium experiences with in-app purchases are also gaining traction on platforms like Character AI and Replika, where users buy add-ons that expand the companion’s functionality and personality.
While advertising is likely to emerge as a more common monetization strategy for AI companions, only limited experimentation in that area—like minor ad exposure in Character AI—exists today. But as engagement spreads and companions become daily touch points, conversational advertising and brand integrations could become high-value opportunities.
Consumer demand for personalized and engaging digital experiences. AI companions deliver a level of personalization that most digital products can’t match. Companions provide always-on conversations, adapt their personalities to users’ moods and preferences, and allow people to customize their avatars and behaviors.
Eighty percent of consumers prefer brands that offer personalized experiences and spend 50% more with these brands, per Deloitte—expectations that now extend across the entire digital ecosystem. This indicates that hyper-personalized, intention-aware engagement is becoming paramount among core demographics.
Seventy-two percent of teens alone have used an AI tool for companionship purposes at least once, per Common Sense Media, while 33% of single Gen Z adults and 23% of single millennials have interacted with an AI platform for companionship or for emotional support, according to Match and The Kinsey Institute. Meanwhile, 21% of adults worldwide have used AI tools for companionship, per Kantar.
AI companions reflect consumers’ increasing desire for personal connection and the need for authentic interactions. For marketers, AI companion adoption trends signal a potential opportunity to reach emerging audiences in highly personalized environments if advertising in companions becomes widespread.
Marketers already have localization playbooks they can use to adapt AI-companion experiences across regions and cultures. Foundational practices like tailoring messaging to cultural norms, ensuring compliance with local AI regulations, and adjusting content for regional preferences still apply.
However, AI companions introduce new variables. Personality, tone, and conversational style may require region-specific tuning; regulations around AI vary significantly; and companion platforms may roll out ad formats at different speeds globally. Accounting for these factors will help marketers design experiences and campaigns that are culturally aligned, regulatory compliant, and consistent with how AI companions naturally interact with users in each region.
Ethical concerns surrounding AI companions are multiplying, and marketers need to approach the field with caution. Recent controversies—like a Character AI lawsuit over a young user dying by suicide after engaging with the platform—and regulatory investigations highlight public skepticism around the safety and emotional influence of these platforms.
When developing AI companion experiences or placing ads within them, marketers must consider the risks of being associated with content that is scrutinized for being deceptive, emotionally manipulative, or harmful to vulnerable users. Monitoring platforms for transparency, emotional safeguards, and age-appropriate restrictions is critical to protect users and maintain brand trust amid intensifying scrutiny.
This means that marketers must:
Early tests show that ads within AI chatbots are already delivering meaningful results. Microsoft Copilot, one of the first major AI platforms to integrate advertising, reported a 153% lift in clickthrough rates and a 54% improvement in user experience from Copilot ads across verticals compared with traditional search. Microsoft’s AI-powered Performance Max campaigns in Copilot have raised clickthrough rates by an average 273% across major categories versus traditional search. Together, these outcomes indicate that advertising within AI interfaces is already proving itself to be a key performance driver.
Marketers should expect both rising consumer adoption of AI companions and expanding opportunities to advertise within these environments as platforms look for new monetization paths. At the same time, ethical and safety concerns will continue to attract public and regulatory attention, making brand-safe execution a key priority over the next 12–24 months.
To position themselves now, marketers can begin working with general-purpose chatbots like Microsoft Copilot to understand how ads perform within AI environments. Experimentation will inform marketers on whether advertising within dedicated AI companion environments—if these opportunities arise—is a worthwhile investment.
Brands understand that consumers are more receptive to purchase recommendations from trusted sources. AI companions—by building familiarity, emotional rapport, and daily conversational habits—have strong potential to become one of those sources if platforms begin offering ads.
Experimenting with AI companions now also offers early adopter advantages: Brands that work with the first platforms to incorporate ads could build deeper affinity with users who show high levels of emotional engagement, foster brand familiarity with consumers before competitors, and gain first access to richer engagement opportunities in companions that track users’ moods, preferences, and long-term goals. And given that many companion users engage for extended conversational sessions, early adopters would benefit from high-attention environments.
Rather than relying on traditional advertising, which struggles to overcome record-low trust, AI companions can introduce products and recommendations as part of an ongoing, trusted dialogue. Companions are seen as sincere, authentic, and trustworthy—creating an opportunity for ads placed within these environments to achieve higher retention, more frequent interactions, and repeat purchases driven by comfort and credibility.
AI companions face growing regulatory scrutiny regarding how minors interact with the platforms. In September, the Federal Trade Commission (FTC) launched an investigation into seven providers—including mainstream chatbots like OpenAI and companions like Character Technologies—to assess potential risks to minors. The inquiry examines how these platforms monetize engagement, shape character behavior, and enforce age controls.
This suggests stricter rules are coming to address addictive engagement patterns, data use, and protections for young users. For brands, the investigation underscores that while AI companions offer new avenues for engagement, any marketing or partnership strategy must account for future regulatory clampdowns and greater accountability for how brand content appears within companion experiences.
Brands need to make sure they can support safe, high-trust, conversational engagement before they integrate advertising into AI companions.
Categories like lifestyle, wellness, entertainment, and education are generally better suited to companion environments. Higher-risk categories such as alcohol or gambling face steeper safety and regulatory challenges when ads appear alongside emotionally sensitive conversations.
Technologically, brands must ensure they can provide structured product and content data (e.g., tagged product catalogs, FAQs, or usage guides) that platforms can ingest to deliver accurate, contextual recommendations within the companion’s dialogue. They also need the ability to review and audit how their brand is surfaced, including through conversation-context logs, brand-mention dashboards, safety flags, or transcripts associated with triggered recommendations.
Organizationally, brands need cross-functional teams—marketing, legal, privacy, and brand safety—to review partner capabilities, approve guardrails, and monitor how ads are delivered inside real user conversations. Brands require clear escalation protocols for when a platform identifies risky placements or when an ad appears near sensitive content, ensuring fast remediation and consistent, responsible participation in AI-companion ecosystems.
This FAQ was prepared with the assistance of generative AI tools to support content organization, summarization, and drafting. All AI-generated contributions have been reviewed, fact-checked, and verified for accuracy and originality by EMARKETER editors. Any recommendations reflect EMARKETER’s research and human judgment.
First Published on Dec 16, 2025