Organizations across sectors are accelerating digital change, and McLean and Company’s HR Trends 2026 report shows that AI adoption is outpacing employees' ability to absorb it. Although the report is not specific to laboratory environments, several themes—rapid implementation, low maturity, and growing pressure on workforce capacity—are directly relevant to AI transformation in labs. As AI strategy for laboratories becomes more important for planning and operations, the report’s findings highlight broader trends that scientific workplaces may need to consider.

AI adoption expands faster than readiness practices

The report notes that 68 percent of organizations are already implementing AI, while only 14 percent have a formal AI strategy. This pattern suggests that AI tools are entering daily workflows before governance, training, or skill development are fully established. For laboratory leaders evaluating automation, digital scheduling systems, data-driven decision tools, or analytics platforms, these findings illustrate the importance of establishing structured approaches rather than reacting to market pressure or vendor-driven timelines.

AI transformation in labs cannot rely solely on tool deployment. It requires clear expectations, defined responsibilities, and support for employees integrating new technologies into existing workloads. The broader organizational challenges described in the report mirror similar pressures in research and clinical environments that adopt AI-enabled solutions.

The HR and IT partnership is central to sustainable AI adoption

One of the report’s key themes is that the strength of the HR and IT partnership significantly influences the success of AI initiatives. While IT teams focus on system design and implementation, HR teams lead training, communication, and change navigation. When these functions work independently, organizations struggle to support employees through transitions.

For laboratory leaders, this insight emphasizes that AI transformation in labs often depends on the same alignment. Scientific teams need accessible training, transparent communication about changing workflows, and clear definitions of how AI tools affect roles and expectations. These conditions depend on cross-functional support rather than isolated technical implementation.

Workforce strain is a limiting factor

The report identifies change fatigue as a growing challenge. Employees and leaders are managing continuous transformation in addition to their core responsibilities. As AI implementation accelerates, the cognitive load increases, especially when adoption occurs without strategic sequencing or adequate resourcing.

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This trend has implications for any workplace—laboratories included—that relies on consistent performance, specialized skills, and controlled processes. As organizations introduce AI, employees’ capacity to learn and adapt becomes a determining factor in the success of digital initiatives.

Implications for laboratory managers

Although the HR Trends 2026 report does not focus on scientific environments, its themes highlight considerations for labs navigating emerging AI tools. Laboratory managers may benefit from:

• Developing a formal AI strategy for laboratories before implementation
• Aligning with HR and IT to support training and communication
• Sequencing technology adoption to prevent change overload
• Clarifying responsibilities and job impacts early in the process
• Monitoring employee feedback to improve adoption readiness

The report suggests that AI transformation in labs is most effective when organizations balance technological ambition with the human capacity required to sustain change. As AI becomes more embedded across industries, these insights offer a useful lens for laboratory leaders preparing for the next phase of digital evolution.

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