How we connect—with customers, colleagues, and communities—depends on trust, predictability, and increasingly on AI. It’s bundled into our phones, our email, how we communicate, how we get answers, and how we get help. But here’s the critical shift: AI has to be more than efficient and accurate. AI and human connection demands that AI be empathetic—built to understand context and respond in ways that feel appropriate to the situation.
When I first wrote about AI and empathy several years ago, the use cases looked very different. Since then, large language models, generative AI, and conversational agents have validated many of the hypotheses behavioral science suggested: the way empathy is expressed by AI must be carefully designed.
Empathy Is a Design Principle, Not a Feature
In behavioral science, empathy has three forms.
Attentive Empathy
Actively listening and reflecting back what you’ve heard. For AI, that means accurately summarizing the user’s concern.
“Let me confirm—since the update, you’ve been unable to access your account.”
Affective Empathy
Acknowledging emotions in language, recognizing and validating how someone feels about their situation.
“That sounds frustrating—let’s fix it quickly.”
Cognitive Empathy
Taking the other person’s perspective to understand their situation and offer the most relevant, helpful solution.
“I get that you’re frustrated your shipment is late, so here’s exactly what we can do to fix it right now.”
AI needs to understand which empathy to deploy and when. For example, affective empathy delivered by AI can have the opposite effect in certain contexts. If a customer knows a system can’t actually feel emotions, overly sympathetic language can trigger reactance—a kind of psychological pushback.
Context Decides the Right Response
One of the most important truths in designing for AI and human connection is that empathy’s value changes with the situation.
- In high-pressure scenarios—like urgent travel rebooking—speed outweighs empathy. Studies show that inserting affective empathy into these moments can reduce satisfaction by more than 15%.1 Customers simply want the fastest path to resolution.
- In low-pressure contexts, empathy strengthens the perception of “social presence” and deepens connection.
This means the best AI must be able to assess context and modulate its empathy accordingly. It also means AI needs to know when to step aside to let humans take over.
When AI Leads and When Humans Step In
The evidence is clear: AI works best as an assistant, rather than a replacement of human expertise.
AI is better for routine, data-heavy, and privacy-sensitive tasks. One study showed people were 81.3% more likely to prefer interacting with a machine-like chatbot than a human for sensitive or possibly embarrassing products (e.g., personal care or medical supplies).2
Humans show more aptitude in high-stakes situations that are emotionally charged and morally complex. We trust other humans to navigate these moments because we expect them to feel empathy as part of their decision-making.
Behavioral biases shape the desire to speak to a human or not, too. When we receive good news—like a loan approval—we prefer it from a human because we attribute the outcome to our own merits. When we get bad news—like the rejection of an insurance claim—we’d rather hear it from AI, as we’re more likely to blame “the system” instead of ourselves.3
AI and human connection is evolving as the technology gets more sophisticated. As we become more accustomed to using AI in our daily lives, it’s also changing the way we work.
The Future of Work Is More Emotional
Paradoxically, as AI takes over simpler interactions, human roles become more emotionally intense. Contact center advisors, for instance, will have to handle a higher proportion of complex, empathy-heavy cases. This increases the emotional labor required, changes the skills we hire for, and demands new support systems to prevent burnout.
In behavioral science terms, this shifts many human advisors toward “deep acting” or “genuine acting”—truly feeling or effectively simulating empathy in sustained, high-stakes contexts. Both can be exhausting without proper training and resources.
Empathy Scales When AI and Human Connection Are Built-In
AI will never have lived experience, but it can be designed to respect and respond to yours. That’s where the magic of the AI and human connection happens—when technology understands context and delivers the right type of empathy.
In both life and business, empathy remains the ultimate competitive advantage. The AI systems that harness it—ethically and contextually—will be the ones people keep coming back to. To learn how to design AI that connects this deeply, download our e-book, “The Ultimate Guide to Empathetic AI.”
1 “Empathic Chatbots: A Double-Edged Sword in Customer Experiences,” Antoine Juquelier, Ingrid Poncin, Simon Hazée, Journal of Business Research, 2025.
2 “Avoiding embarrassment online: Response to and inferences about chatbots when purchases activate self-presentation concerns,” Jianna Jin, Jesse Walker, Rebecca Walker Reczek, Journal of Consumer Psychology, 2024.
3 “Chatbots better than humans for delivering bad news, study finds,” WXYZ Detroit, May 16, 2022.
Frequently Asked Questions (FAQs)
What is contextual empathy in AI design?
Contextual empathy means AI adjusts how it responds based on the situation. In high-pressure moments—like a flight rebooking—speed matters more than small talk. In calmer moments, empathy creates a sense of connection. The best AI knows when to dial empathy up, and when to step back.
How does AI affect customer satisfaction during high-pressure situations?
Research shows that adding “affective empathy” (e.g., scripted sympathy) into urgent situations can actually lower satisfaction by more than 15%. Customers under pressure want resolution fast.
When should AI take the lead over human advisors?
AI works best for repetitive, data-heavy, or privacy-sensitive tasks. For example, customers often prefer an AI chatbot over a human when buying personal care or medical supplies. Humans step in when the stakes are high, the emotions are complex, or the judgment calls carry moral weight.
How do human emotional skills become more vital with AI integration?
As AI handles routine tasks, humans are left with the hardest conversations—emotionally charged and empathy-heavy. That means advisors will need stronger emotional intelligence skills, and organizations must recognize the increased “emotional labor” required to keep people engaged and supported.
