Employees Prefer Human Connection in Learning and Development, Despite the Growing Acceptance of AI

In the dynamic world of workforce development, learning and development (L&D) plays a crucial role in shaping a skilled and adaptable workforce. Recently, there has been increasing interest in the use of artificial intelligence (AI) in L&D functions, offering the potential for automation and efficiency. However, a recent survey has revealed that employees still value human connection and prefer instructor-led training, highlighting the need to strike a balance between AI and human involvement in L&D initiatives.

Preference for Instructor-led Training

The survey conducted among employees indicated that a significant majority, 59%, preferred having an instructor, whether physically present or virtual, to direct their workforce development training. This preference reflects their desire for human interaction and personalized guidance in the learning process. Despite advancements in technology, employees attach great importance to the expert guidance and support provided by instructors.

Moreover, the survey findings emphasized the importance of human connection in L&D. Employees crave personal interaction and value the ability to ask questions, receive immediate feedback, and engage in discussions with their instructors and peers. This preference indicates that the traditional instructor-led training model retains its relevance and effectiveness in meeting employees’ needs.

Subject Matter Expert vs. AI Content Development

In addition to the preference for instructor-led training, the survey also highlighted a strong inclination towards content developed by subject matter experts (SMEs) rather than AI. An overwhelming majority – 87% of respondents – expressed a desire for L&D content to be developed by SMEs. This preference underscores employees’ belief in the expertise and experience of human professionals in delivering relevant and tailored content.

While there is growing interest in AI-based content development, only a mere 12% of respondents indicated a preference for AI-generated content. This finding suggests that employees value the nuances, insights, and practicality that human expertise brings to L&D content. They recognize the importance of subject-matter expertise in creating meaningful and engaging learning experiences.

Growing Acceptance of AI in L&D

Despite the emphasis on human connection, the survey findings also point to a shift in the attitudes of L&D professionals towards the use of AI. More and more professionals are warming up to the idea of incorporating AI into their functions, recognizing its potential for enhancing efficiency and productivity.

The survey revealed that 64% of respondents agreed that using AI for administrative tasks in L&D would increase efficiency. AI, as an automation tool, can streamline administrative processes, freeing up L&D professionals to focus their efforts on more value-added activities such as curriculum design, instructional design, and learner support. By eliminating repetitive tasks, AI has the potential to enhance the overall effectiveness and impact of L&D initiatives.

Balancing AI and Human Efforts in L&D

While employees may prefer instructor-led training and content developed by subject matter experts (SMEs), the survey results also showed that they do not oppose L&D practitioners improving their efforts through AI. This indicates a willingness to embrace the benefits of AI while maintaining the human touch.

Finding a balance between AI and human involvement is crucial for effective workforce development. AI can complement human efforts by providing data-driven insights, personalized recommendations, and adaptive learning experiences. By leveraging AI as a powerful tool, L&D professionals can enhance the efficiency and effectiveness of their initiatives, ultimately benefiting employees and organizations alike.

The survey’s findings align with the widespread adoption of AI across various workplace functions. Nearly one-third of workplaces are actively using AI, highlighting its increasing presence in driving efficiency and innovation. As AI becomes more integrated into organizations, it is essential for L&D professionals to understand its potential and harness its capabilities to support their training initiatives.

In the ever-evolving landscape of L&D, it is crucial to consider employee preferences and needs. The recent survey has shed light on the continued importance of human connection and personalized guidance in workforce development training. While AI offers tremendous potential for automation and efficiency, employees still value the expertise of instructors and subject matter experts.

The key lies in nurturing a balance between AI and human involvement in L&D initiatives. L&D professionals can leverage AI as an automation tool to optimize administrative tasks, allowing them to focus on higher-value activities such as curriculum design, instructional design, and learner support. By embracing AI while preserving the human touch, organizations can create a holistic and effective learning experience for their workforce.

In this era of technological advancements, it is crucial to recognize that the human element remains at the core of successful L&D initiatives. The ongoing dialogue between AI and human involvement in learning and development will drive the future of workforce training, enabling organizations to continuously upskill and empower their employees.

Explore more

How B2B Teams Use Video to Win Deals on Day One

The conventional wisdom that separates B2B video into either high-level brand awareness campaigns or granular product demonstrations is not just outdated, it is actively undermining sales pipelines. This limited perspective often forces marketing teams to choose between creating content that gets views but generates no qualified leads, or producing dry demos that capture interest but fail to build a memorable

Data Engineering Is the Unseen Force Powering AI

While generative AI applications capture the public imagination with their seemingly magical abilities, the silent, intricate work of data engineering remains the true catalyst behind this technological revolution, forming the invisible architecture upon which all intelligent systems are built. As organizations race to deploy AI at scale, the spotlight is shifting from the glamour of model creation to the foundational

Is Responsible AI an Engineering Challenge?

A multinational bank launches a new automated loan approval system, backed by a corporate AI ethics charter celebrated for its commitment to fairness and transparency, only to find itself months later facing regulatory scrutiny for discriminatory outcomes. The bank’s leadership is perplexed; the principles were sound, the intentions noble, and the governance committee active. This scenario, playing out in boardrooms

Trend Analysis: Declarative Data Pipelines

The relentless expansion of data has pushed traditional data engineering practices to a breaking point, forcing a fundamental reevaluation of how data workflows are designed, built, and maintained. The data engineering landscape is undergoing a seismic shift, moving away from the complex, manual coding of data workflows toward intelligent, outcome-oriented automation. This article analyzes the rise of declarative data pipelines,

Trend Analysis: Agentic E-Commerce

The familiar act of adding items to a digital shopping cart is quietly being rendered obsolete by a sophisticated new class of autonomous AI that promises to redefine the very nature of online transactions. From passive browsing to proactive purchasing, a new paradigm is emerging. This analysis explores Agentic E-Commerce, where AI agents act on our behalf, promising a future