What is the impact of AI on Total Factor Productivity and intangible capital?
Short Answer
AI amplifies Total Factor Productivity by enabling firms to extract more output from the same inputs, with the productivity gains increasingly attributable to intangible capital — data, algorithms, and organisational knowledge — rather than physic...
Full Explanation
Total Factor Productivity (TFP) measures the portion of economic output not explained by the quantity of inputs (labour and capital). Historically, TFP growth has been attributed to technological progress and innovation — the Solow residual. AI is now a primary driver of TFP gains, but its effects flow predominantly through intangible capital channels. When a company deploys AI to automate customer service, optimise supply chains, or personalise marketing, the productivity gains are embodied in software, data assets, and organisational processes — all intangible. Research by Corrado, Hulten, and Sichel (CHS) has shown that intangible investment now exceeds tangible investment in most advanced economies, and AI is accelerating this shift. For individual firms, AI-driven TFP improvements compound over time: better data leads to better models, which generate more data, creating a virtuous cycle of intangible asset accumulation. Companies that measure and manage their intangible capital systematically — tracking AI's contribution to each asset category — gain a clearer picture of where productivity gains originate. This visibility is essential for investment decisions, valuation, and communicating value to investors who increasingly look beyond tangible asset metrics.
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Further Reading
AI Integration Costs: The Hidden Expenses of AI Adoption
AI licensing fees represent only 20-30% of total AI adoption costs. The remaining 70-80% — data preparation, integration engineering, change management, and ongoing maintenance — are the hidden expenses that derail AI budgets and timelines.
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