arXiv:2606.18288v1 Announce Type: cross Abstract: This volume develops a knowledge theory of capital for economies in which productive capacity increasingly resides in software, data, models, routines, expertise, platforms, organizations, commons, and public epistemic infrastructure. Beginning from Adam Smith's theory of labour, stock, specialization, and market extent, it asks what changes when knowledge becomes stock-like, mobile across forms, scalable, governable, recombinable, and imperfectly visible in accounting. The book introduces knowledge-bearing stock as the central object and analy
The publication reflects growing academic and industry recognition of knowledge and intangible assets as increasingly dominant forms of capital in modern economies.
A re-conceptualization of capital to include knowledge assets is crucial for understanding economic value creation, policy design, and competitive advantage in the AI era.
This theoretical framework shifts the focus from traditional physical capital to software, data, and expertise as core economic drivers, necessitating new methods of valuation and governance.
- · AI/Software companies
- · Knowledge-intensive industries
- · Countries with strong intellectual property frameworks
- · Highly specialized experts
- · Industries reliant solely on physical capital
- · Economies with low investment in intangible assets
- · Traditional accounting firms slow to adapt
- · Labor in easily automatable roles
This theory provides an updated lens for economic analysis, investment strategies, and national economic policies.
It could lead to new metrics for national wealth and corporate valuation, emphasizing intangible assets over traditional balance sheet items.
The integration of knowledge as capital might reshape global trade, potentially leading to 'data wars' or competition for AI expertise and models.
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Read at arXiv cs.AI