AIORG-W020 Peer-reviewed research

Artificial Intelligence and Productivity: An Intangible Assets Approach

Oxford Review of Economic Policy grab018

peer reviewed economic article

Recorded claims
2
coded from the inspected source
Evidence classes
2
survey-or-synthesis, independent-empirical
Recorded limitations
3
stated, never hidden

From the wave-0 evidence ledger

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

The article treats software, databases, worker training, and business-process reorganization as complementary intangible investments needed to turn AI capability into productivity rather than as incidental rollout costs.

confidence: medium-high survey-or-synthesis

Scope: Broad AI/intangible-capital relationship, not a direct test of generative-AI adoption.

The empirical analysis found limited evidence of an AI productivity J-curve in the available data, preserving uncertainty about the timing and magnitude of returns even when complementary investments are conceptually important.

confidence: medium independent-empirical

Scope: Available historical AI and intangible-investment data; not current GenAI firm outcomes.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Broad AI and pre-current-GenAI data
  • Intangible categories are difficult to measure
  • Macro/industry patterns do not identify one firm's causal return

Source independence

Independent academic/macroeconomic analysis of AI and intangible assets.