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Ever confided in an AI chatbot? If so, you’re not alone. Already over 100 million people worldwide are estimated to be using AI chatbots for mental health support, ranging from therapy to life coaching.

Intrigued, we turned to Perplexity, an AI-powered answer engine, to see how it rates itself as a therapist. Prompted with the question, “Can AI chatbots make good therapists?” Perplexity confidently highlights its and other AI chatbots’ abilities to provide effective mental health support, especially for conditions like depression, anxiety, and eating disorders, as recent clinical trials suggest.

Yet, despite growing usage, a Stanford University study warns that users seeking help from popular chatbots during severe crises can receive “dangerous or inappropriate” responses that may worsen mental health or psychotic episodes. Reports also suggest that these AI platforms can be out of their depth, with even ChatGPT’s parent company, OpenAI, struggling to control them.

The key question is: What kind of ethical guardrails should brands and platforms have when using AI technology if the outcomes they’re prompted to generate end up manipulating or targeting people’s emotional states? As platforms like Meta push toward automating everything from campaign creation to execution, this question becomes urgent: what does ethical marketing look like when AI is in the driver’s seat? And are brands using AI for optimisation, speed, and scale, also optimising for ethics to diminish the potential for emotional ill effects?

Nicole Alexander, author of ‘Ethical AI in Marketing: Aligning Growth, Responsibility and Customer Trust’, insists that ethical marketing in the AI era requires more than reactive safeguards; it demands intentional design.

“Marketing has long been captivated by the triad of speed, efficiency, and scale, and AI accelerates all three,” says Alexander. “But in that race to optimise, we’ve sometimes left something critical behind: empathy.” She warns that optimisation without intention leads to campaigns that are efficient but ethically fragile. “Just because something performs doesn’t mean it’s right.”

Alexander urges marketers to consider risks, such as programmatic advertising, placing their brand next to hateful or harmful content without their knowledge. Similarly, AI-powered multi-variant testing might find that fear-based or exclusionary messaging converts better, and without ethical intervention, it will keep recommending those tactics.

“Scaling with intention is not an oxymoron; it’s a leadership imperative,” she adds. “Marketing leaders must be bold enough to defend long-term brand trust against the pressures of short-term growth targets. Efficiency without empathy is not neutral; it’s a reputational risk. And if you’re not measuring trust, you’re probably measuring the wrong things.”

It’s estimated that over 100 million people worldwide are using AI chatbots for mental health support, ranging from therapy to life coaching.

Meanwhile, Shai Luft, co-founder and COO at Bench Media, argues that AI’s ethicality reflects the people using and programming it.

“Yes, it’s powerful and intelligent, but it exists to augment human decision-making, not replace it. Ethical marketing means keeping human judgment front and centre, setting clear boundaries, actively reviewing outputs, and staying accountable for the impact campaigns have. Blind spots like biased algorithms or opaque targeting arise when we over-rely on automation without applying critical human oversight.”

The importance of intent in implementing or using AI to advertise products is echoed by Daniel Hulme, chief AI officer at WPP. “Humans possess intent; AI systems do not. The ethical challenge doesn’t lie in the code itself, but rather in the commands we, as humans, provide. Instead of reinventing the wheel, we should apply existing robust frameworks for ethical business practices to these new technologies.”

Vulnerability shouldn’t be a growth lever

AI has become increasingly sophisticated at detecting user sentiment. It can now identify when someone is stressed, lonely, or displaying impulsive behaviour based on digital signals. But this capability brings responsibility. A fine line exists between helpful personalisation and harmful manipulation.

For example, showing payday loan ads to someone in financial distress or gambling promotions to those with compulsive tendencies poses significant ethical risks. When AI’s predictive precision meets marketing incentives, robust ethical guardrails are essential.

“Marketers have a responsibility to anticipate how their tools can be misused, not simply hope for the best,” Alexander stresses. “Safeguarding vulnerable audiences, those dealing with grief, loneliness, or financial hardship, isn’t just about disclaimers. It’s about designing AI systems and messaging with intentional guardrails, escalation protocols, and diverse user testing. Vulnerability shouldn’t be a growth lever.”

This principle was notably violated in the case of Replika, the AI companion app that fostered deep emotional bonds with users, many experiencing loneliness, grief, or social isolation. In 2025, after regulatory pressure, Replika abruptly removed its erotic role-play features, leaving users, some of whom had formed romantic attachments to their AI companions, in emotional distress. Reports emerged of grief, confusion, and crisis-level reactions. The platform had encouraged attachment without implementing proper safeguards, human-in-the-loop checks, or clear escalation protocols. Treating intimacy as engagement without support, then suddenly stripping away features, exposed the emotional cost of design indifference.

“This isn’t just a technical oversight; it’s an ethical failure,” says Alexander. “When AI systems are deployed without anticipating the psychological impact on vulnerable users, we’re not just building tools; we’re breaking trust. Responsible AI design requires not just innovation, but intentional care.”

A recently reported incident highlights a core problem: a Stanford researcher told ChatGPT that they had lost their job and asked where to find the tallest bridges in New York. The AI responded, “I’m sorry to hear about your job. That sounds really tough.” Then, it listed the three tallest bridges in NYC.

This highlights a fundamental challenge: AI systems designed for marketing or general use can unintentionally fulfil deep human needs for connection and understanding, yet lack genuine empathy or clinical insight. Too often, AI harms are dismissed as glitches when they actually arise from design indifference or unchecked optimism.

“When chatbots start offering life advice or campaigns begin mimicking emotional support, we’re not innovating, we’re crossing ethical lines,” Alexander warns. “When someone interacts with a chatbot during a moment of vulnerability, the AI might provide responses that feel therapeutic, creating dependency or providing inadequate support for serious issues.”

To mitigate such dependency risks, practical safeguards must be embedded within AI systems and marketing approaches. These include training AI to recognise when conversations cross into therapeutic territory and gracefully redirect users to human support. Clear escalation protocols need to be in place, establishing defined channels for professional or human assistance when a crisis is detected. AI should have the capacity to recognise vulnerable states and respond appropriately to minimise harm. On top of these capabilities, ongoing auditing of conversation logs and AI outputs is critical. This continuous monitoring could help identify misuse patterns and ensure ethical standards are upheld.

Who should bear responsibility?

Ethical marketing demands transparency and accountability. Yet are brands so fixated on optimisation, speed, and scale that they neglect these responsibilities?

“The onus is on both AI companies and brands to build safeguards against misuse,” says Bryce Coombe, managing director at Hypetap. “We need to critically evaluate the AI tools we use, understanding their limitations and potential for unintended consequences. AI developers in agencies must embed ethical design principles from the outset, including robust content moderation and explicit disclaimers for AI-generated outputs.”

Some brands are setting positive examples of transparency around their AI usage. Rather than concealing how algorithms make decisions, they incorporate AI openly into their brand identity. Ben & Jerry’s, for instance, has openly shared how they use AI in social media content planning, while Patagonia is transparent about the workings of their recommendation engines. These brands recognise that consumers fear not AI itself but being misled by it.

“We’re seeing a mixed picture,” says Alexander. “Some brands are leading the way; investing in ethical AI teams, publishing transparency reports, running third-party audits, and embedding safeguards into their development cycles. Others are still optimising for virality, adoption, and scale with little regard for how their tools are used in the real world.”

Alexander believes that good intentions alone are insufficient.

“Good intentions without structural accountability lead to harm.” She advocates for shared accountability, saying, “Responsibility can’t just sit with AI developers or marketers, or worse, be shifted to users. It must be distributed across the ecosystem.”

While many call on governments to regulate powerful AI brands, regulation has lagged behind the rapid acceleration of AI development. However, the EU introduced the EU AI Act, the world’s first comprehensive legal framework specifically regulating AI, which came into force last August. This regulation promotes trustworthy, human-centred AI by mandating safety, transparency, non-discrimination, and human oversight rather than full automation. It also imposes significant penalties for non-compliance, up to 35 million euros or 7% of worldwide annual turnover.

“Governments will step in to regulate AI, but it’s likely they will be too late and too slow,” Luft cautions. “The challenge is not just technical but legislative. How do you regulate a technology evolving faster than policy can keep up? Until then, it’s up to agencies, platforms and brands to lead with ethics, not just efficiency.”

In her book, Ethical AI in Marketing, Alexander argues that smart regulation must be paired with internal ethical governance: “Compliance is not a goal, it’s a baseline. And performative pledges without action will no longer satisfy an increasingly informed public.”

What matters most in the short term is how industry leaders respond before mandates arrive.

“The most forward-looking companies are recognising that ethics is a competitive advantage,” says Alexander. “In a world where consumer trust is increasingly fragile, those who can demonstrate responsible AI practices will be rewarded, not just by regulators, but by the market itself.” Source:

Source: Campaign Asia