Successful integration of new technology heavily relies on emotions, and with 80% of companies admitting to not fully harnessing its potential, managers need guidance on managing these aspects, according to researchers.
The successful integration of new technology largely depends on emotional factors, and as 80% of companies report not optimizing its benefits, managers must learn how to navigate these emotional dynamics, according to Aalto University researchers.
Recent studies indicate that artificial intelligence (AI) can improve decision-making, drive innovation, and help leaders enhance employee productivity. Despite significant investments from many large companies, studies indicate they are not reaping the anticipated rewards, with 80% of organizations reporting a failure to take advantage of the new technology.
Assistant Professor Natalia Vuori from Aalto University states, “Employees frequently struggle to adopt new AI tools successfully, yet the reasons behind this are not clear.” She suggests that previous analyses often attribute these issues to the limitations of the technologies themselves or to users’ cognitive assessments of AI performance.
“Our findings emphasize that success hinges less on the technology’s capabilities and more on the emotional and behavioral responses employees have towards AI—and how leaders can effectively manage these responses,” explains Vuori.
Her research team monitored a consulting firm with 600 employees for over a year while the company sought to develop and implement a new AI tool designed to gather employees’ digital activities and outline their skills and competencies, ultimately creating a capabilities map for the organization. This map was intended to optimize the selection process for consulting projects, with the entire initiative seen as a pilot for AI software they wished to offer clients.
After nearly two years, the firm abandoned the initiative along with the product. What went wrong?
It was discovered that while some employees recognized the tool’s functionality and value, they felt uneasy about AI tracking their calendar events, internal communications, and daily interactions. Consequently, many opted to stop sharing information entirely or began manipulating their inputs to skew results in their favor, leading to inaccuracies in the AI’s outputs and creating a damaging cycle where users lost trust in its effectiveness.
“Leaders could not comprehend why AI usage was declining. Even with significant efforts to promote the tools and clarify how data was used, their actions did not yield results,” remarks Vuori, who suggests this situation illustrates a common trend in AI adoption, as well as tech integration more broadly.
The research team is now exploring the use of Microsoft’s popular Copilot AI software, which so far shows analogous results.
What should leaders prioritize?
Researchers identified four distinct groups based on individuals’ reactions to the new technology, categorizing them into cognitive trust—belief in the technology’s performance—and emotional trust—feelings towards the system. The groups include: full trust, full distrust, uncomfortable trust, and blind trust.
Individuals in the first group expressed high levels of both cognitive and emotional trust, while those in the second group exhibited low trust across the board. Uncomfortable trust reflects high cognitive trust but low emotional trust, and the opposite defines blind trust.
As emotional trust decreases, individuals limit, withdraw, or manipulate their digital activities, highlighting that this trend exists even among those with cognitive trust in the technology.
These insights provide organizations with the opportunity to develop more effective strategies for AI implementation.
“The adoption of AI is not merely a technological challenge but a leadership one. Success is contingent upon understanding trust dynamics and addressing emotions, as well as making employees excited about leveraging and experimenting with AI,” asserts Vuori. “Without a human-centered approach and strategies tailored to each group’s needs, even the most advanced AI will fall short of realizing its potential.”
The findings of this research were published in the Journal of Management Studies on January 22:
