arbiter
JournalsPricingAccount

Data Localization as Tax Nexus: Server PEs for AI Providers in Asia

Mark Bowler-Smith & Thao Le

Asia-Pacific Tax Bulletin2026https://doi.org/10.59403/38mj6yharticle
ABDC C
Weight
0.50

What the paper says

Mandatory data localization in Asia can compel foreign artificial intelligence (AI) providers to place or control infrastructure in a given country, raising the question of whether this creates a server permanent establishment (PE) under article 5 of the OECD and UN Models. Drawing on a doctrinal study of Vietnam, Indonesia, Myanmar, Cambodia and Lao PDR, this article shows how localization and presence requirements can satisfy the fixed place and “at disposal” tests in the case that providers deploy dedicated inference environments that they control, even without personnel on site. It proposes an operational “control and co-location” test to distinguish compliant hosting from PE-relevant architectures. It then outlines a profit attribution approach under the Authorized OECD Approach, adapting DEMPE analysis to algorithmic functions: routine returns for local hosting and orchestration, residual profits for offshore model development and data curation. Finally, it identifies double taxation risks and recommends targeted safe harbours and stronger dispute resolution mechanisms.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.59403/38mj6yh

Or copy a formatted citation

@article{mark2026,
  title        = {{Data Localization as Tax Nexus: Server PEs for AI Providers in Asia}},
  author       = {Mark Bowler-Smith & Thao Le},
  journal      = {Asia-Pacific Tax Bulletin},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.59403/38mj6yh},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Data Localization as Tax Nexus: Server PEs for AI Providers in Asia

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.