Artificial intelligence is rewriting the economy’s production function. It is moving intangibles such as data, technology and ideas to the centre of production and transforming how production is organised. In the cover article of the latest issue of the Peking University Financial Review, Prof. Xiaolan Fu and Xiaomian Dai argue that this restructuring is precisely what makes pricing the decisive question. A new factor creates value only when it is combined with capital, and without credible, reusable price signals, factors struggle to flow, high-quality assets are hard to identify and capital finds it hard to come in. As the authors put it, ‘the central question of the AI-era economy is how to give the new factors a credible price’.

To enter the production function, a factor needs a price, yet the existing tools fall short. Cost, income and market-comparison approaches to valuation were born in an era of tangible assets, and ‘their failure is not only technical but also structural’. A mistaken view compounds the problem: that pricing standards are unnecessary because the market will decide, and the same technology may fetch a different price from every buyer. This sounds like faith in the market but confuses value with price. Value is the total utility an asset creates while price is the outcome of a particular transaction. Left to immature markets, prices follow the identity and bargaining power of buyers and sellers rather than the quality of the technology, and good assets are driven out by bad. ‘A market is itself a costly public good’, and opening up trade alone will not produce efficient prices. Inadequate methods and mistaken views together hold back the development of markets for technology and data.

The authors propose a solution that combines theory and tools. The utility theory of technology value (Fu et al., 2026, The World Economy) holds that the value of technology, and of data, is ultimately determined by the total utility it delivers to users and to society. Artificial intelligence now makes such valuation possible at scale for the first time, turning the valuation of intangibles from an art that relies on personal experience into a science that can be verified. With credible prices, finance can back the new factors through investment, lending, capital markets and insurance. Yet ‘the redistribution of pricing power has never been a purely technical matter’, so new tools must go hand in hand with institutional reform. Once these channels for prices are built, technology and data can flow into firms, industries and the financial system, and the restructuring of factors can truly become lasting momentum for productivity growth.

Read the full article (in Chinese).

Cite the article: Fu, X. and Dai, X. (2026) ‘Restructuring new factors of production and breaking the pricing deadlock in the AI era’ (in Chinese), Peking University Financial Review, 29, pp. 26–30.