Analysis of Financial Support Paths in the Implementation of Large-Scale AI Projects

Yimo Wang

doi:10.62051/ijgem.v10n8.05

Authors

Yimo Wang Faculty of Engineering School of Project Management, The University of Sydney, NSW 2006, Australia

DOI:

https://doi.org/10.62051/ijgem.v10n8.05

Keywords:

Artificial intelligence industry, Large-scale project implementation, Financial support, Financing structure, Investment-lending linkage

Abstract

Good Funds are needed to support the large-scale construction of artificial intelligence systems. It has not been determined whether the current financing system is suitable for the nature of these projects; they have strong asset specificity and a long pay-back period. The two types of this study are asset specificity and uncertainty. We will consider the operating modes of the four paths—equity capital, government-directed funds, bank credit and capital markets—and their relationships here. At present, the system of financial support has a hierarchical structure; early-stage venture capital leads, bank credit in the growth stage, and capital markets at the mature stage have all joined this structure. However, there are three kinds of disconnections among these paths: the early-stage projects lack funds; credit disbursement is not linked to equity investment; and the functional boundaries of policy funds and market-based funds are unclear. The traditional risk control system is based on tangible collateral and is therefore not suitable for the features of the AI industry, which has many intangible assets. This is the cause of the above problem. To promote the transition from segmented supply to full-cycle financial support, build an infrastructure for intangible asset evaluation, establish a risk-sharing mechanism for investment and lending linkage, and optimise the incentives of the long-term capital system.

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