5 ways leaders should prioritize mental health

As companies adopt AI, the conversation is shifting from the promise of productivity to concerns about AI’s impact on wellbeing.

Business leaders can’t ignore the warning signs. The mental health crisis isn’t new, but AI is changing how we must address it. More than 1 billion people experience mental health conditions. Burnout is rising. And more people are turning to AI for support without the expertise of trained therapists. What starts as “empathy on demand” could accelerate loneliness. What’s more, Stanford research found that “these tools could introduce biases and failures that could result in dangerous consequences.”

With the right leadership, AI can usher in a human renaissance: simplifying complex challenges, freeing up capacity, and sparking creativity. But optimism alone isn’t a strategy. That’s why responsible AI adoption is a business imperative, especially for companies building the technology. That work is not easy, but it’s necessary.

UNCLEAR EXPECTATIONS

We’ve seen what happens when powerful platforms are built without the right guardrails: Algorithms can fuel outrage, deepen disconnection, and undermine trust. If we deploy AI without grounding it in values, ethics, and governance—designing the future without prioritizing wellbeing—we risk losing the trust and energy of the very people who would lead the renaissance.

I’ve seen this dynamic up close. In conversations with business and HR leaders, and through my work on the board of Project Healthy Minds, the signals are clear: People are struggling with unclear expectations around AI use, job insecurity, loneliness, uncertainty, and exhaustion.

In a recent conversation with  Phil Schermer, founder and CEO of Project Health Minds, he told me, “There’s a reason why professional sports teams and hedge funds alike are investing in mental health programs for their teams that enable them to operate at the highest level. Companies that invest in improving the mental health of their workforce see higher levels of productivity, innovation, and retention of high performers.”

5 WAYS TO BUILD AN AI-FIRST WORKPLACE THAT PROTECTS WELLBEING

Wellbeing should be at the core of the AI enablement strategy. Here are five ways to incorporate it.

1. Set clear expectations

Employees need to understand how to work with AI and that their leaders have their back. That means prioritizing governance and encouraging experimentation within safe, ethical guardrails. Good governance builds trust, and trust is the foundation of any successful transformation.

Investing in learning and growth sends a powerful message to employees: You belong in the future we’re building if you’re willing to adapt. We prioritize skill building through ServiceNow University so every employee feels confident working with AI day-to-day.

In a conversation with Open Machine CEO and AI advisor Allie K. Miller, she told me that we need to redefine success in jobs by an employee’s output, value, and quality as they work with AI agents. This means looking at things like business impact and creativity, not just processes or tasks completed.

2. Model healthy AI behavior

AI implementation is a cultural shift. If we want employees to trust the technology, they need to see leaders and managers do the same.

That modeling starts with curiosity. Employees don’t need to be AI experts from day one, but they need to show a willingness to learn. Set norms around when, why, and how often teams engage with AI tools. Ask questions, share experiments, and celebrate use cases where AI saved time or sparked creativity. AI shouldn’t be an “opt in” for teams—it should be part of how we work, learn, and grow. When leaders use AI thoughtfully, employees are more likely to follow suit.

3. Pulse-check employee sentiment consistently

To design meaningful wellbeing programs, leaders must ground analysis in data, continuously improve, and build for scale. That starts by surveying employees to track sentiment, trust, and AI-related fatigue in real time.

Then comes the harder part: acting on the data to show employees they’re seen and supported. Leaders should ask:

• Are we tailoring wellbeing strategies to the unique needs of teams, regions, and roles?
• Are we embedding empathy into our platforms, workflows, and automated tasks?
• Are our AI tools safe, unbiased, and aligned to our values?
• Are we making mental health a routine part of manager check-ins?

According to Schermer, “The organizations making the biggest strides are the ones treating wellbeing data like commercial data: measured frequently, acted on quickly, and tied directly to outcomes.”

4. Focus on connection, keeping people at the center 

AI should not replace professional mental healthcare or real-world connections. We must resist the urge to “scale empathy” through bots alone. The unique human ability to notice distress, empathize, and escalate is largely irreplaceable. That’s why leaders should advocate for human-first escalation ladders and align their policies to the World Health Organization’s guidance on AI for health. Some researchers are exploring “traffic light” systems to flag when AI tools for mental health might cross ethical or personal boundaries.

AI adoption is a human shift, so people leaders need to take responsibility for AI transformation. That’s why my chief people officer role at ServiceNow evolved to include chief AI enablement officer. Today’s leadership imperatives include reducing the stigma around mental health, building confidence in AI systems, creating space for open human connection, and encouraging dialogue about digital anxiety, loneliness, or job insecurity.

5. Champion cross-sector collaboration

We need collaboration across industries and leadership roles—from tech to healthcare, from HR professionals to policymakers—to create systems of care alongside AI. The most effective strategies come from collective action.

That’s why leaders should partner with coalitions to scale access to care, expand AI literacy, and advocate for mental health in the workforce. These partnerships can help us shape a better future for our people.

THE BOTTOM LINE: AI MUST BE BUILT TO WORK FOR PEOPLE

The future of work should be defined by trust, transparency, and humanity. This is our moment to lead with empathy, design with purpose, and build AI that works for people, not just productivity.

Jacqui Canney is chief people and AI enablement officer at ServiceNow.