The "settlement" of AI investment has begun — cost discipline and withdrawal design in an era where investments yield no results.
This document explains the cost discipline and withdrawal design to resolve the gap between investment and outcomes in AI investments. Currently, many AI initiatives are abandoned before they go live, making the gap between investment and outcomes visible. What is questioned during this settlement period is not the pursuit of new models, but the judgment of which to continue and which to stop. This document clarifies the causes of the gap between investment and outcomes and presents three designs to overcome this issue. 【Contents】 ■ Causes of the gap between investment and outcomes (going live without designing a cost structure, experiments without a definition of success) ■ Three designs to overcome the gap (establishing GO/NO-GO criteria based on numbers, cost control through structure, focusing on a few use cases) ■ Support provided by our company (creating GO/NO-GO criteria, optimizing cost structures, delineating between withdrawal and continuation, etc.) *For more details, please download the PDF or feel free to contact us.
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Decision-making based on target values for deal conversion rates in the digital marketing domain, cost reduction through routing according to the complexity of requests, and measurement of quality and on-site changes using the adoption rate of AI-generated products and user satisfaction. *For more details, please download the PDF or feel free to contact us.*
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