Address the emotion behind AI resistance to keep adoption from lagging

Anika Gakovic is chief people and culture strategist at Phyusion, and advisor, Ragan’s Center for AI Strategy.

Treating AI resistance as a communication and training shortfall will not solve lagging technology adoption.

Resistance is emotional first. Employees are protecting their sense of identity and security, not undermining a rollout on purpose. Using motivation and language choices with intention can turn defensiveness into partnership.

A growing body of evidence shows that employees are concerned. Gallup found 18% of U.S. workers believe their job is likely to be eliminated within five years due to AI. That number rises to 23% at companies that have adopted it. Gallup also reported global employee engagement fell to 20% in 2025, its lowest level since 2020, pointing to a climate of workplace uncertainty. Pew Research found more than half of U.S. workers are worried about AI’s impact on jobs, and Boston Consulting Group found nearly half of workers at organizations undergoing AI-driven redesign report more worries about job security than those at less advanced companies.

A paper from Human Resource Management Review groups this resistance into three dimensions:

• Fear rooted in job and status threats.
• Inefficacy and self-doubt about using the tools well.
• Antipathy, or a values-based rejection of AI itself.

Applying the science of human behavior can help leaders navigate resistance. Here are three ways to lead employees through resistance to technology adoption:

Name the fear before it claims you

Leaders can fall into an enablement illusion by tracking adoption metrics while missing workforce sentiment. Employees with a positive outlook toward AI are reported as 3.4 times more likely to be productive, driven by role confidence and transparent communication.

Fear left unnamed moves into disengagement. Lead direct conversations about how AI changes specific responsibilities and workflows, naming what stays the same before what evolves in human judgment and expertise. Doing this early earns the trust that carries the rollout.

Build competence before asking for commitment

MIT Sloan Management Review columnist Ganes Kesari argued that leaders who weave AI incrementally into daily work outperform those who roll it out abruptly, because user comfort and trust ultimately determine whether adoption succeeds.

Competence and confidence build together: I have seen employees given room to experiment before being evaluated adopt technology faster than those trained and monitored immediately. Position learning as an opportunity for skill building and build in low-stakes practice before attaching performance expectations that raise the stakes.

Growth and exploration spark positive emotions and engage motivation.

Lead with compassionate honesty

A survey of human resources leaders found that 78% think workflows and roles will need to change to capture AI’s value. Success will require leaders to pair adoption with efforts to help employees feel safe raising concerns.

This is compassionate honesty: naming the truths and trade-offs about AI’s impact while making it clear that questions and feedback are welcome.

Employees take cues from how a leader responds when someone raises a concern. Build channels for employees to question AI workflows and flag issues without being labeled resistant.

For example, swap “Are you using AI correctly?” for “What is getting in the way?” Shifts in conversation reveal frictions early, giving leaders a chance to fix the root causes of lagging adoption.

The bottom line

AI resistance and hesitation are sources of useful data for those willing to listen. Communications leaders can treat that information to help choose their language with intention and keep humans at the center of AI change.