Data centers have always been a major component of tech CAPEX, but the scale of AI-specific facilities is transforming them into one of the most widely discussed capital-allocation stories of the past several decades.

Projects tied to OpenAI, Anthropic, Meta, Microsoft, Oracle, and Amazon do not necessarily raise new accounting questions. Rather, the projects increase the materiality of familiar issues — such as consolidation and lease accounting, disclosure of construction-in-progress balances and disaggregation by PPE category, and presentation of CAPEX-related accounts payable. The potential materiality of AI-related construction projects to the lead organizations’ balance sheets magnifies insufficient and inconsistent disclosure and, in some cases, suggests the need for more specific accounting guidance.

We examined how AI-related projects are structured and financed, and why their accounting and disclosure should be evaluated in conjunction with the chosen project structure.

Key themes:

• Deal structure matters. Some companies appear willing to keep more of the financial impact of the construction on their own balance sheets, while others rely more heavily on joint ventures, special-purpose vehicles, and sale-leaseback arrangements that obscure the full impact of the projects.
• Accounts payable are rising across the AI-related data center construction industry, but not all increases are created equal. Across several major tech companies, total accounts payable as well as payables tied to property, plant, and equipment have risen sharply, suggesting that some companies may be relying on supplier financing. In our view, it is important to differentiate between ordinary cash management activity and financing-like arrangements embedded in the financing structure of some of the construction projects.
• Disclosure remains inconsistent. Companies do not all present CAPEX-related activity the same way, making comparisons more difficult for investors.
• Concentration is a material risk. If AI demand weakens or construction timelines slip, the economic pressure may not fall evenly across sponsors, developers, lenders, vendors, tenants, and investors.

In our view, the broad increase in days payables outstanding, or DPO, across the group of firms focused on AI-related construction projects suggests that large-scale AI and data center construction — including EPC contracts, long-lead GPU procurement, and phased buildouts — may be significantly influencing payable timing.

Differences in smoothness versus choppiness likely reflect variations in construction contract structures (fixed schedule vs. milestone-based), the cadence of PPE purchases, and whether companies are expanding capacity through steady multi-year programs or more episodic project launches.

As discussed above, however, DPO trends alone do not fully capture the mechanics of the cash flow presentation and construction-in-progress (CIP) balances, including the timing of “placed in service” decisions which drive depreciation expense. Additionally, large portions of capital investment may be financed through leases, supplier financing embedded in accounts payable, joint ventures, and third-party-funded construction, making near-term cash flow appear stronger than the true economic burden. At the same time, CIP balances, timing of asset placement, and classification within the statement of cash flows can materially affect comparability and limit the usefulness of traditional cash flow metrics when applied to multi-year, externally financed infrastructure buildouts.

This is an abridged version of the analysis. The full Deep Quarry series of posts — available to paid Deep Quarry subscribers — examines structure, financing, and accounting guidance for the AI-related deals (Part 1), as well as construction-in-progress accounting and disclosure and cash flow implications (Part 2). 

For questions and data inquiries please contact olga@deepquarry.com.

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