Organizations looking to accelerate artificial intelligence adoption may need to focus less on technology and more on human behavior. Research highlighted by workplace culture firm Workhuman suggests that recognition—specifically acknowledging experimentation, collaboration, and learning—can help organizations build employees into “AI power users” who help integrate AI into everyday work.

Many organizations approach AI implementation primarily as a technology rollout: selecting tools, launching training sessions, and creating internal guidance for employees. But the research suggests the largest barriers to AI adoption are often behavioral rather than technical. Employees may hesitate to experiment with AI tools if they are unsure what success looks like or fear making mistakes publicly.

According to the analysis, successful AI adoption depends on reinforcing behaviors that encourage experimentation, iteration, and knowledge sharing across teams.

Workplace recognition can reinforce AI adoption behaviors

Recognition can help organizations reinforce the behaviors needed for effective AI adoption. According to a Workhuman study, employees who received recognition in the previous week were significantly more likely to understand their organization’s strategic initiatives—rising from 50 percent to 86 percent. Alignment with those initiatives also increased from 36 percent to 80 percent.

The research suggests employees tend to repeat behaviors that receive visible appreciation or reinforcement. In the context of AI adoption, recognizing experimentation and learning may encourage employees to continue exploring new tools and workflows.

Rather than recognizing only polished outcomes, the analysis recommends acknowledging the behaviors that support long-term capability. Examples include testing multiple approaches, documenting lessons learned, and identifying when human oversight is required.

Psychological safety supports experimentation

Another factor influencing AI adoption is psychological safety. Employees must feel comfortable experimenting, asking questions, and sharing incomplete ideas in order to build new technical capabilities.

According to the research, employees who received recognition in the previous month reported psychological safety scores that were 21 percent higher than those who had not received recognition. Employees who had recently thanked colleagues also showed a 15 percent increase in psychological safety.

Higher psychological safety was also associated with stronger organizational alignment. Teams with higher safety levels were more likely to understand organizational values and strategic goals, including AI adoption initiatives.

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Peer learning helps build AI power users

The analysis suggests peer recognition can help organizations develop AI power users—employees who experiment with tools, share what they learn, and help colleagues improve their own use of AI.

Recognizing employees who coach others, share prompt strategies, or create reusable workflows can help transform individual experimentation into team-wide capability. These behaviors help translate AI technology into practical improvements in everyday work.

The report also notes that traditional adoption metrics, such as logins or usage statistics, may not fully capture whether AI adoption is spreading across teams. Recognition patterns, however, can reveal which behaviors employees value and where AI experimentation is gaining traction.

Implications for laboratory leaders

For laboratory managers, the findings highlight the human side of technology adoption. Laboratories are increasingly exploring artificial intelligence for applications such as data analysis, literature review, workflow optimization, and quality management. Integrating these tools into daily scientific work often requires as much cultural change as technical capability.

Encouraging experimentation, recognizing learning efforts, and creating space for peer-to-peer knowledge sharing can help laboratory teams build confidence with new technologies. In environments where precision and compliance are critical, leaders who reinforce thoughtful experimentation and responsible AI use may help staff adopt new tools more effectively while maintaining scientific rigor.

As laboratories evaluate the role of artificial intelligence in research and operations, the research suggests that successful AI adoption may depend less on the tools themselves and more on how leaders encourage curiosity, collaboration, and continuous learning within their teams.

This article was created with the assistance of Generative AI and has undergone editorial review before publishing.