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cloud.google.com·7h ago
AI Research
arXiv CS.AI·Sep 12·5 min read
AI Exposure and AI Resilience: A Two-Dimensional Assessment Framework for Software and Software-Based Business Model
TL;DR
A new framework, AI Exposure and Resilience (AI-ER), assesses how artificial intelligence impacts software business models by measuring a company's pressure to adapt and its ability to do so. This two-dimensional model provides a structured way to evaluate AI's influence on business value and competitive positioning.
✦ Why It Matters
Evaluate your company's AI exposure and resilience to strategically adapt your business model today.
Key Takeaways
- Assess your business model's AI exposure to identify necessary changes.
- Measure AI resilience to understand your adaptation capabilities.
- Utilize public information for initial assessments of AI impact.
- Implement the proposed scoring logic for empirical validation.
Full Summary
Artificial intelligence is transforming software development and the economics of software-based business models, necessitating a new assessment approach. The AI Exposure and Resilience (AI-ER) framework distinguishes between AI exposure, which reflects the pressure for change that AI imposes on a business model, and AI resilience, which indicates a company's capacity to adapt and leverage AI effectively.
Metrics for both dimensions are derived from existing AI capabilities and relevant research on business models. The framework allows for an initial assessment using public information, which can be refined with internal data, resulting in a traceable company profile.
This profile supports comparisons while transparently addressing the quality and confidence of the underlying evidence. An initial scoring logic and empirical validation procedure are also proposed to enhance the framework's applicability.