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The AI Investment Gap: Rethinking Cost Recognition for Technology Infrastructure
Paperback
AccountingEconomicsInvesting & Finance
ISBN13: 9786180065695
Publisher: Panagiotis I. Chronopoulos, PhD
Published: Jun 8 2026
Pages: 130
Weight: 0.35
Height: 0.28 Width: 5.50 Depth: 8.50
Language: English
The argument of this book is that the gap between AI investment and AI adoption manifests, in the first instance, in the accounting - and that accounting, far from being a neutral record of economic reality, actively shapes how the transition unfolds.
The economy is entering a period of regime change - a structural transformation in the relationship between investment, productivity, and prices. The hundreds of billions of dollars flowing into AI infrastructure are not speculative excess but the foundation of a new productive capacity, one that may in relatively short order generate efficiency gains across virtually every sector. Companies will produce more with fewer inputs. Costs will decline, and with them prices, even as the economy grows.The implication for monetary policy is significant. If AI constitutes a significant disinflationary force, central banks could reduce interest rates without igniting inflation. The supply side would be expanding rapidly enough to accommodate demand without price pressure. The old trade-offs would no longer apply.
This is a bet on technological transformation delivering macroeconomic salvation, and the bet is not implausible. Artificial intelligence has demonstrated remarkable capabilities. Tasks that previously required expensive human expertise - legal research, medical diagnosis, software development, financial analysis - are increasingly performed by AI systems at a fraction of the cost. Deployed at scale, the productivity implications are genuinely substantial.
Yet the bet requires more than capability. It requires that capability translate into economic reality within a particular timeframe - that the infrastructure investments pay off before they become burdens, and that the economy absorb the transition without the disruptions that accompanied previous technological revolutions. It is this last requirement that warrants examination. Not whether AI can transform productivity; it almost certainly can. But whether the transition itself can be managed.
The infrastructure is being built at one pace, and the capacity to use it is developing at another. These paces are not aligned, and the gap between them must manifest somewhere in the economic system.Also in
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