What Happens To Your Data When You Chat With AI Companions?

AI systems are gaining traction within the emerging digital intimacy economy. But with that, the focus shifts to a pressing question: what really happens to the data users provide to these AI companions?

AI companions function on the backbone of large language models (LLMs) that are trained using user interactions.

Photo Credit: WISE

This includes everything from light banter to highly sensitive disclosures involving relationships, trauma, or identity.

While such platforms are presented as private, non-judgemental environments, they are also systems that collect significant amounts of personal data-often in legally ambiguous conditions regarding ownership, consent, and usage.

Data as Commodity

These platforms typically harvest detailed emotional and behavioural data from users. Even though interactions might appear intimate or safe, they are governed by opaque platform policies, reported the Financial Express.

Frequently, user data is employed for profiling, targeted advertising, or to further train the models-often without users being fully aware or having explicitly granted consent.

Despite some claims about anonymisation, emotional data is considered uniquely identifiable. Many users are unaware that their most personal interactions could be stored indefinitely and used for purposes well beyond the initial conversation.

In essence, users are contributing some of their most private moments to systems that can monetise and repurpose this data.

Platforms like Replika, for instance, capture not just text but also media such as photos and videos, as well as details about sexuality, beliefs, and health.

Although such companies may claim not to use this data for advertising, their licensing terms allow for broad internal usage, modification, and storage. Similarly, Character.ai collects extensive user data, including IP addresses, browsing activity, and device information, which may be shared with advertisers.

Gaps in Regulation

While global data protection laws such as the GDPR, CCPA, and India's DPDPA offer a framework for consent and privacy, they are often ill-equipped to handle the nuances of AI companions. Emotional nuance, inferred mental states, and conversational metadata tend to fall outside the clearly defined boundaries of current legislation.

There's also a widespread lack of transparency about whether user data is being used to improve models, develop psychological profiles, or drive personalised recommendations. Clearer user disclosures and easy-to-use tools for data deletion remain sorely lacking.

Trust and Risk

The potential reputational and legal fallout for companies in this sector is considerable. If users feel misled or discover that their data has been mishandled or commercialised without adequate transparency, trust can deteriorate rapidly-particularly when platforms serve emotionally vulnerable individuals.

Current legislation also struggles with the challenge of tracing how AI systems process data. The opaque nature of these systems complicates issues of consent and minimisation. Mismanagement of such sensitive data could invite both public backlash and legal consequences.

In fact, the US case Garcia v. Character Technologies has begun to raise legal questions about whether AI companions should be treated as products under existing liability laws.

A preliminary ruling from a California court has opened up the possibility of holding both platform providers and model developers responsible for any harm caused by AI-generated content.

India's Measured Approach

India is seeing steady uptake in AI companions, particularly in areas like wellness and entertainment. While users are increasingly engaging with AI-driven tools, cultural attitudes around emotional expression in digital formats are still developing. As a result, trust remains a major barrier.

Companies hoping to succeed in India will need to demonstrate not only privacy awareness but also cultural and psychological sensitivity.

According to Indian law, any organisation offering AI companions in the country becomes a "Data Fiduciary". This means it is legally obligated to safeguard user data, ensure its accuracy, implement proper security measures, honour user rights, and report breaches both to authorities and those affected.

The Dual Edge of Empathy

AI companions now do more than talk-they remember, simulate affection, and offer a form of companionship.

Yet, these seemingly empathetic exchanges are also powering product development and model refinement.

There is concern that such synthetic empathy may result in users forming emotional dependencies, potentially leading to long-term social isolation.

In the end, while these systems can offer emotional relief in the short term, they are fundamentally built to learn from and monetise those very emotions. Control over the data lies with the platforms-not the users.