Intelligent systems—incorporating computational tools, learning algorithms, and statistical models—can generate knowledge to empower employees in how they conduct their work and increase their job performance. How can organizations realize this potential? Our in-depth study of transformation of work with intelligent systems in a technology maintenance service company provides managerial insights to this question. Although knowledge from intelligent systems can empower employees, employees will need to adapt how they work with intelligent systems to improve their job performance. Interestingly, they can leverage the empowerment to adapt in two ways: maximize benefits, where they use the system to its full potential in conducting work, and minimize disturbances, where they reduce role conflict with the system in conducting work. Although inexperienced employees leverage the empowerment to use the system to its full potential, experienced employees leverage the empowerment to minimize role conflict with the system. How empowered employees realize job performance gains requires understanding how employees channel their empowerment: maximize benefits through use of the system or minimize disturbances through role conflict with the system. Differentiating how inexperienced and experienced employees channel empowerment to increase job performance will enable managers to effectively manage the transformation of work for these two groups.

Online Health Consultation Communities (OHCCs) have emerged as vital platforms connecting patients with physicians for online consultations. However, finding the right match between patients and physicians can be tricky due to physicians’ changing capacity to consult on the OHCC. Our study delves into how signals provided by OHCCs on physicians’ professional status and behaviors can help make these matches successful, especially when considering their capacity fluctuations. We differentiate between two types of signals pertaining to physicians–owned, pertaining to their professional status, and earned, pertaining to their OHCC activity and patient reviews of the physician. Employing a Hidden Markov Model to analyze data from a large OHCC on physicians’ voluntary online consultations with patients, we find the role of the signals in efficient matching to be contingent on the capacity state of the physician. Physicians’ professional status is particularly important when they have less time available, and showing active participation in the community can make the status even more impactful. Conversely, when physicians have more availability, patient feedback becomes crucial, even diminish the importance of professional status. These insights suggest that OHCCs should tailor how information on physicians’ professional status and patient feedback are presented depending on physicians’ availability as this can help patients to make better choices. By being active in the OHCC and earning favorable patient feedback, physicians with more availability can improve their attractiveness to patients, even offsetting concerns that can stem from the lack of seniority of the physician. The findings underscore the need for OHCCs to develop signaling and matching mechanisms that consider the capacity of physicians, thereby fostering efficient and satisfactory patient-physician consultations.