When AI meets EQ: the next frontier of digital health

Artificial intelligence (AI) or when machine learning techniques or algorithms are used to manage tasks or processes more efficiently, has quickly become the backbone of digital health — from nutrition coaching and stress management to chronic condition care. Eighty-five percent of healthcare leaders report exploring or implementing AI, in part to improve personalization and scalability. For employers, that's transformative: helping more people, more often, at a lower cost. 

But predicting what someone needs is only half the battle. As efficient as AI is, it wasn't designed to completely replace human connection and emotional intelligence (EQ), the ability to recognize and understand emotions of yourself and others. Organizations that use AI to strengthen engagement — not automate it — will be the ones that truly improve workforce health.

With so many capabilities, AI is bound to improve engagement for some users. But even the best data needs interpretation. Context is always key. AI might be able to flag a week of inactivity, but it can't tell if it's due to stress, travel or exhaustion. That's where people step in — to connect, triage or adjust the plan.

Then there's always the risk of AI hallucination or when AI presents false information as facts. OpenAI recently found that its newest models (o3 and o4-mini) hallucinated 30% to 50% of the time. And it's not just an OpenAI issue: A wide range of chatbots have also been known to invent data, with research finding a wide range of hallucination rates across many systems. With the health and wellbeing of individuals on the line, the risk of leaning entirely on AI and automation will be too high for many employers. And it's why getting that balance right will be key to providing the best care for the most amount of people possible.

For years, there's been a swinging pendulum toward automation in the field of wellness — with chatbots, self-guided programs and algorithms that could deliver personalized, scalable care. This has, in many ways, made healthcare more accessible. But tools and automation alone won't drive the day-to-day emotional connection and trust that keeps people engaged. A strategy that falls short on the human element puts three buckets of people at risk of disengagement:

1. Those who need a bit of human support every-so-often to make sense of all the information and tools given. Some people need accountability, human check-in and the relationship that says, "Hey, I see you. You're doing great. Keep going."
2. Those without the health literacy or digital literacy to make sense of all the information and tools they receive. Instead of feeling supported by automated tools, it's overwhelming.
3. Those who are maxed out — emotionally or mentally. It's not that they don't want help; they just don't have the bandwidth to figure out a new program. For them, AI can feel bombarding and create an even bigger obstacle.

And here's another thing: when it comes down to it, people want to feel seen. Research has shown that people are more likely to stick to healthcare guidelines or treatment when they feel understood and supported. Empathy isn't a nice-to-have, it's the foundation for emotional intelligence required to drive adherence, participation and ultimately health outcomes.

Why this matters for employers right now

Employers are navigating one of the most complex benefit environments in decades. Employer health-care costs are predicted to rise 6.5% this year, partially driven by chronic disease, obesity and the rising use of GLP-1 medications. At the same time, 70% of HR leaders say mental and emotional well-being are top priorities for their organizations. Now, more than ever, employers are looking for ways such as AI to provide support in a scalable and cost-efficient manner.

Programs that feel personal drive participation. Programs that build trust drive results. And both ultimately deliver the sustained outcomes employers need to contain costs and improve employee well-being. As benefit leaders explore new digital and AI-enabled tools, the question isn't how much technology to use — it's how to use it in partnership with human involvement to keep people connected, motivated and cared for.

AI vs. human care isn't an either/or — it's a balance. In practice, that looks like:

• Balanced care with escalation path built in. If AI is the first touch and someone needs more help, the system routes or escalates to a real coach or clinician who can personalize next steps.
• Personalization that feels personal. Data informs timing, tone and topic, but human expertise sifts through the nuance and guides content — turning automated prompts into emotionally intelligent guidance that fits real life.
• Accessibility through smart design. AI chat, SMS, email, group coaching and telephonic outreach work together. While automated tools manage quick questions or reminders, human coaches step in when the need is complex or emotional.
• Automation with human oversight. Every interaction — automated or not — can be monitored through human review, A/B testing and feedback loops.

The future of digital health lies in using AI to extend our reach and capacity to help people and not replace human insight, but amplify it. The next generation of digital health will be defined by the partnership between AI and EQ, combining data-driven precision with the humanity that guides it.