Paper Type
Complete
Paper Number
1275
Description
The advancement of AI holds significant potential for the professional service sectors, yet more than half of AI initiatives have underdelivered. To demystify the translation of AI potential into tangible firm-level outcomes, we undertook a longitudinal case study of AI adoption and utilisation within a leading Australian professional service firm. Adopting affordance actualisation theory, we identified affordances that emerged and were actualised by individuals within the firm, leading to immediate outcomes at the individual level. Six generative mechanisms—mechanical accuracy, mechanical efficiency, scope expansion, data insights, task priority, and conformance enforcement—were abstracted to articulate how these affordances yield three pivotal organisational outcomes. Our findings contribute to the literature by illuminating how affordances were actualised through the interplay between AI features and individual actions upon facilitating conditions, and how individual outcomes were aggregated into firm-level successes. The findings are insightful for professional service firms seeking to effectively leverage AI.
Recommended Citation
Yang, Jiaqi; Marrone, Mauricio; and Amrollahi, Alireza, "Actualising AI Affordances: Insights from a Professional Service Firm’s Journey" (2024). PACIS 2024 Proceedings. 7.
https://aisel.aisnet.org/pacis2024/track01_aibussoc/track01_aibussoc/7
Actualising AI Affordances: Insights from a Professional Service Firm’s Journey
The advancement of AI holds significant potential for the professional service sectors, yet more than half of AI initiatives have underdelivered. To demystify the translation of AI potential into tangible firm-level outcomes, we undertook a longitudinal case study of AI adoption and utilisation within a leading Australian professional service firm. Adopting affordance actualisation theory, we identified affordances that emerged and were actualised by individuals within the firm, leading to immediate outcomes at the individual level. Six generative mechanisms—mechanical accuracy, mechanical efficiency, scope expansion, data insights, task priority, and conformance enforcement—were abstracted to articulate how these affordances yield three pivotal organisational outcomes. Our findings contribute to the literature by illuminating how affordances were actualised through the interplay between AI features and individual actions upon facilitating conditions, and how individual outcomes were aggregated into firm-level successes. The findings are insightful for professional service firms seeking to effectively leverage AI.
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