Learning-oriented employees gain most from AI, enhancing workplace innovation

Artificial intelligence is transforming not just how organizations operate but also how employees think and behave at work. As AI becomes deeply embedded in workplaces, it is reshaping employee confidence and willingness to take risks, according to a new study that provides fresh insights into the psychological impacts of AI on workers.

The research, titled "Trust the Machine or Trust Yourself: How AI Usage Reshapes Employee Self-Efficacy and Willingness to Take Risks" and published in Behavioral Sciences, examines how AI usage interacts with employee self-efficacy and learning goal orientation, the authors reveal that AI influences much more than task performance, it alters risk-taking behavior, a factor critical for innovation and organizational growth.

How does AI usage influence employee risk-taking?

The study explores the relationship between AI usage and employees’ willingness to take risks, a behavior often linked to creativity, innovation, and competitive advantage. Using data collected from 442 employees across industries with high AI adoption, such as manufacturing, IT, and finance, the researchers found that AI usage significantly increases employees’ risk-taking tendencies.

This effect is primarily explained by the concept of self-efficacy, an employee’s belief in their own ability to succeed in challenging situations. The research shows that AI tools provide workers with enhanced analytical capabilities, faster problem-solving, and greater decision accuracy, all of which build confidence. This increase in self-efficacy makes employees more comfortable stepping out of their comfort zones to take calculated risks that may drive innovation.

Notably, the study highlights that risk-taking here does not refer to reckless behavior. Instead, it refers to strategic decisions where employees evaluate potential outcomes and take action that could yield substantial benefits for their organizations. AI reduces uncertainty in these situations, giving employees the confidence to pursue opportunities that they might have previously avoided.

What role does self-efficacy play in this process?

The authors identify self-efficacy as the mediator between AI usage and risk-taking. When employees use AI effectively, they perceive themselves as more capable, competent, and equipped to handle complex problems. This confidence empowers them to make bold yet informed decisions.

Self-efficacy plays a pivotal role in shaping how employees interact with AI. Those who feel empowered by technology are more likely to embrace it, using it to enhance their capabilities rather than fearing it as a replacement for their skills. The study underscores that organizations must pay close attention to how AI tools are introduced and supported. Without proper training and integration, AI can cause anxiety and resistance rather than empowerment.

The research also notes that self-efficacy impacts not only decision-making but also employee engagement and job satisfaction. Workers who believe in their abilities are more motivated, take initiative, and contribute to innovative solutions. Thus, AI’s capacity to boost self-efficacy has far-reaching implications for workforce performance and organizational success.

Why does learning goal orientation matter?

Beyond self-efficacy, the study finds that learning goal orientation, the extent to which employees are motivated to develop their skills and master new challenges, significantly influences the relationship between AI and risk-taking. Employees with a high learning goal orientation view AI as an opportunity to enhance their capabilities. They actively engage with the technology, experiment with its features, and use it as a tool for continuous improvement.

For these employees, AI amplifies the positive cycle: they use the technology to learn, which builds their self-efficacy, which in turn increases their willingness to take risks. On the other hand, employees with a low learning goal orientation may see AI as a threat or burden, limiting its positive effects on their behavior.

The findings suggest that organizations must foster a culture of learning to fully harness the benefits of AI adoption. Training programs, mentorship opportunities, and a supportive environment encourage employees to develop a growth mindset. When employees feel safe to experiment, fail, and learn, AI becomes a catalyst for innovation rather than a source of fear.