The successful implementation of an enterprise system requires training and end users in the new systems and procedures. There has been no research reporting a relationship between Domain Expertise (DE) and the successful implementation of an enterprise system. This study sought to begin filling this knowledge gap by exploring the relationship between DE, technical proficiency, training outcomes, and perceived training effectiveness for a new enterprise system, specifically a Case Management System (CMS) in a small and medium enterprise (SME). The research examines different subjects of technical expertise including skills, abilities, and knowledge to increase professional acceptance in the high domain of expertise field. In order to understand the complex nature of expertise and the significant impact, an exploratory approach is undertaken. Purposive sampling was utilized to select the 88 respondents to participate in the research, in which the role of domain expertise and technical expertise is explored. Based upon analysis, research showed the relevance of domain expertise and technical expertise in the deployment of successful case management systems. The results contributed to literature by showing that how training influences soft skills such as tacit knowledge on organizational culture and potential clients, deliver best solutions to the project management. Meanwhile, the outcomes provided significant traits on perceived training effectiveness, which drive increase in knowledge, practical implication, and quality of project delivered, presentation skills, communication and problem-solving abilities. The study also contributed to the literature in terms of defining how technical and domain expertise not only effect the outcomes of case management systems but also develop greater coordination for dealing the intricacies, project difficulties, and task-related complexities.

The increasing utilization of generative artificial intelligence (AI) in organizations isenhancing productivity and decision-making processes of knowledge workers. However, alimited number of studies have focused on both communicative and organizationalimplications of how knowledge workers’ utilization of generative AI tools is affecting domainexpertise and knowledge sharing within organizations. In collaboration with the Swedishtelecommunications company Ericsson, this study embraces an interdisciplinary approach andimplements a qualitative research strategy based on data from 18 in-depth interviews withknowledge workers employed at a global ICT company. The findings highlight two keydimensions; firstly, knowledge workers perceived that by utilizing generative AI it couldaugment their expertise – both transcending domain boundaries and enhancing specializeddomain expertise. At the same time, they perceived work roles to become moresocio-technical in the future. Secondly, generative AI can facilitate knowledge sharingbetween domains by taking on the role of a mediator when communicating expertise acrossdomains. However, the facilitative knowledge sharing effects of generative AI might bedampened by potential silo effects when turning to generative AI instead of colleagues. Thishighlights the need for clear organizational objectives around generative AI usage and theimportance of collaborative knowledge sharing activities to create common understandings ofthe opportunities and limitations of generative AI tools / Den ökande användningen av generativ artificiell intelligens (AI) inom organisationerförbättrar produktiviteten och beslutsprocesser hos kunskapsarbetare. Däremot har ettbegränsat antal studier utförts som fokuserar på både kommunikativa och organisationellakonsekvenser av hur kunskapsarbetarnas användning av generativa AI verktyg påverkardomänexpertis och kunskapsdelning inom organisationer. I samarbete med det svenskatelekommunikationsföretaget Ericsson tillämpar denna studie ett tvärvetenskapligttillvägagångssätt och implementerar en kvalitativ forskningsansats baserat på data från 18djupintervjuer med kunskapsarbetare anställda på ett globalt ICT-företag. Resultatent visar påtvå huvuddimensioner; kunskapsarbetare uppfattade att de genom generativ AI kundeförstärka sin expertis genom att både överskrida domängränser och förbättra specialiseradexpertis. Samtidigt upplevde kunskapsarbetarna att arbetsroller kan komma att bli mersociotekniska i framtiden. Den andra dimensionen visar hur generativ AI kan faciliterakunskapsdelning som en medlare mellan olika domäner. Brist på tydlighet inomorganisationen gällande användningen av generativ AI i arbetsuppgifter och potentiellasilo-effekter kan däremot hindra verktygets kapaciteter för kunskapsdelning. Detta påvisarvikten av tydliga riktlinjer gällande användningen av generativ AI ochkunskapsdelningsaktiviteter för att skapa en gemensam förståelse av möjligheterna ochbegränsningarna med generativa AI verktyg.