Problem
Research questions and friction points this paper is trying to address.
Artificial Intelligence
Business Model
Exposure
Resilience
Assessment Framework
AI Exposure and AI Resilience: A Two-Dimensional Assessment Framework for Software and Software-Based Business Model
🤖 AI Summary
本文提出AI暴露度和韧性双维度评估框架，用以解决AI对软件及基于软件的商业模式影响评估问题。
📝 Abstract
Artificial intelligence is changing both software production and the economics of software-based business models. Classical technology due diligence mainly examines technical properties such as architecture, scalability, and technical debt. These criteria do not fully capture how AI can affect a company's value proposition, competitive position, margins, or access to customers. This paper develops Artificial Intelligence Exposure and Resilience (AI-ER) as a two-dimensional assessment framework. AI exposure describes the pressure for change that AI creates for a business model. AI resilience describes the company's ability to absorb that pressure, adapt to changed conditions, and use AI in an economically viable way. Metrics for both dimensions are derived from current AI capabilities, their deployment conditions, and relevant research on business models and organizational adaptability. The model keeps exposure and resilience separate and adds an explicit assessment of evidence quality and confidence. It can be applied first with public information and later refined with internal evidence. The result is a traceable company profile that supports comparison without concealing uncertainty in the underlying evidence. The paper also specifies an initial score logic and a procedure for empirical validation.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Artificial Intelligence Exposure
AI Resilience
Two-Dimensional Assessment Framework
Business Model
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2024-01-26arXiv.orgCitations: 5
