Advancing Artificial Intelligence Adoption and Decision-making with Extended Technology Acceptance Model

Abstract

Despite Kuala Lumpur’s push for AI integration, only 23% of businesses have adopted AI, lagging behind the global average of 37%, with 65% still relying on basic data tools and only 10% using advanced analytics. This study investigates the factors influencing AI adoption in Kuala Lumpur's IT sector, focusing on Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Perceived Organizational Support (POS). Using the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical foundations, this study extends these frameworks by incorporating POS to emphasize the critical role of organizational support in AI adoption. Data from a survey of 340 IT managers were analyzed us- ing PLS-SEM. The results demonstrate that both PEOU and POS significantly impact PU, which in turn influences AI adoption intentions. POS emerged as a vital factor, indicating that organizational support, such as training and resource provision, is key in making AI useful and encouraging its adoption. This research has practical implications for businesses and policymakers. Organizations should focus on improving organizational support mechanisms, particularly through targeted training programs and technical assistance to enhance AI adoption. Policymakers are encouraged to refine initiatives like Industry4WRD by strengthening infrastructure and providing sector-specific support. The study's novelty lies in its focus on emerging markets like Kuala Lumpur, addressing a gap in AI adoption research by exploring the organizational challenges specific to such regions.

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