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Proposal pack · RO-LD11-04 v2

Do AI startups backed by a cloud giant end up running on that giant's cloud?

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Read this first. This is a research hypothesis drafted by Claude (SocioLens Project Lead), AI-drafted from the LD-11 debate on 12 October 2026, not a finding. Checked by Claude (SocioLens Project Lead) with AI research agents, by web search; not a person and not a domain expert; an independent AI reviewer with fresh context (not a person), 12 October 2026: every nearest-work citation checked against its source page; corrections applied. Every check so far was done by AI; no person or domain expert has checked it yet. The literature screen below was done by AI web search and can miss relevant work. Version v2, permanent address https://sociolens-web.pages.dev/opportunities/ro-ld11-04/v2/.

Not yet measured One PhD chapter or paper Low to medium cost No study found

Research question

Among AI startups that raised money from Amazon, Microsoft or Google (directly or through their venture arms), compared with similar startups funded by independent investors, how much more likely are they to build on the investing firm's cloud and models, and does that tie persist or loosen in later funding rounds?

Why it matters

FTC staff documented that, in three of the largest cloud–AI partnerships, the AI developers must spend a large share of the investment on the investor's cloud, and investor analysts describe hyperscaler investment as a way to lock in cloud commitments. Whether this pattern extends across the wider startup ecosystem, and whether it amounts to steering, is not measured. This is one concrete, observable route to the "AI-specific foreclosure" effect that current evidence cannot quantify.

The debate lists this among what we still do not know: a quantified AI-specific bundling/default foreclosure effect

Evidence that motivates it

  1. FTC staff found that major cloud–AI-developer partnerships included equity, revenue-sharing and varying consultation, control and exclusivity rights, while not establishing antitrust liability. (LD11-HQ-C11 v1.0)
    FTC staff found equity, revenue-sharing and varying exclusivity and control rights in major cloud–AI-developer partnerships, without establishing foreclosure; this study measures one downstream outcome across many smaller deals.
    Cites: FTC Office of Technology 6(b) staff report, Jan 2025
  2. The UK CMA found AWS and Microsoft hold significant market power in UK cloud and identified egress fees, interoperability barriers and Microsoft software licensing as constraints on switching and multi-cloud. (LD11-HQ-C08 v1.0)
    The CMA found switching constraints in cloud generally, but the claim explicitly does not license AI-specific foreclosure; that is the gap being measured.
    Cites: UK CMA Cloud Services Market Investigation, final decision…; CMA package of actions, 31 March 2026

Claims are shown as they read on the day this pack was built; claim pages keep every earlier version.

A possible design

Build a sample of AI startups founded 2019–2025 from a funding database (Crunchbase or PitchBook through a university licence, or the free Crunchbase tier plus press releases). Treated firms received equity from Amazon, Microsoft, Google or their venture arms; comparison firms are matched on founding year, sector, location, stage and round size. Measure each firm's cloud and model stack from three public traces: job postings (skill mentions such as AWS, Azure, GCP, Bedrock, Vertex, Azure OpenAI), public technical documentation and marketplace listings (for example appearing in a cloud provider's marketplace), and press releases announcing cloud partnerships. Estimate the difference in the probability of using the investor's cloud as primary platform, and use an event-study around the investment round to separate selection (firms already on that cloud) from post-investment shifts. Track multi-cloud adoption in later rounds.

Data needed

Funding records for a few thousand AI startups; job-posting data (public postings collected over time, or an academic licence to a postings dataset); cloud marketplace listings; a hand-coded validation sample.

Feasibility

One PhD chapter or paper. Low to medium: free if the university licenses a funding database and job-posting data; otherwise a few thousand US dollars for data access. Selection is the main threat (investors back firms already on their cloud); the event-study and pre-investment stack measures address this only partly. Cloud credit terms are rarely public, so the study measures stack outcomes, not contract terms, and cannot by itself establish illegality or foreclosure.

Has this been done?

The search found no study that does the core design (first-pass screen of 12 October 2026, checked again on 13 October 2026).

No study was found that systematically measures whether startups funded by cloud hyperscalers build on their investor's cloud compared with matched startups. The FTC staff report covers three large partnerships through compulsory orders; Widder and Kim map hyperscaler startup investments at scale from Crunchbase but report no measure of which cloud investees use, and forward search found no follow-up that does; regulatory attention in 2026 (a reported European Commission inquiry) concerns exclusive cloud contracts with frontier labs rather than portfolio-wide stack outcomes. Impink (2026) surveys AI startups about resource-sharing with large technology suppliers but names no investor and measures no cloud choice. A matched, ecosystem-wide measurement of the stack outcome remains open.

Literature check. No study was found that compares the cloud or model stack of hyperscaler-funded AI startups with matched independently funded startups. Forward search on Widder and Kim found only commentary; CVC literature (e.g. Ando et al., NBER w33993) studies generic technology adoption or innovation, not cloud choice; a possibly relevant SSRN paper by Impink on complementary technical assets in AI startups could not be opened at the time; it was later identified as HEC Paris Research Paper 1621, a survey that names no investor and measures no cloud choice. The European Commission's 2026 inquiry into exclusive hyperscaler-AI lab cloud deals (as reported) concerns contracts, not investee stack data. Checked by Claude (SocioLens Project Lead) with AI research agents, by web search; not a person and not a domain expert.

Where the search could not reach. Screened by web search on the date shown; Google Scholar, SSRN, paywalled journals and subscription databases (PitchBook, CB Insights research) were not reachable beyond public pages. Absence of a hit is not proof that the work does not exist. Literature check of 2026-10-13: Impink's paper was identified later (HEC Paris Research Paper 1621) and read at abstract level only. No access to Crunchbase or PitchBook. The European Commission inquiry was seen only through a secondary site. Corporate-venture journal search surfaced innovation-output studies only.

Before building a project on it, run your own search in a scholarly database such as Scopus, Web of Science, Google Scholar or SSRN.

Nearest work found

References

Sources behind the motivating claims:

BibTeX

The first entry cites this opportunity; then its nearest work; then the sources above. Nearest work and sources are recorded as reference strings, so each goes in whole as the title; add authors and year from the original before you cite it.

@misc{sociolens_ro_ld11_04_v2,
  author = {{SocioLens project}},
  title = {Do AI startups backed by a cloud giant end up running on that giant's cloud?},
  year = {2026},
  date = {2026-10-13},
  howpublished = {\url{https://sociolens-web.pages.dev/opportunities/ro-ld11-04/v2/}},
  note = {Research opportunity RO-LD11-04, version v2}
}

@misc{ro_ld11_04_nearest_1,
  title = {US Federal Trade Commission, "FTC Issues Staff Report on AI Partnerships \& Investments Study," press release and staff report (17 Jan 2025)},
  url = {https://ftc.gov/news-events/news/press-releases/2025/01/ftc-issues-staff-report-ai-partnerships-investments-study},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated; Judged from an abstract, summary or search listing only}
}

@misc{ro_ld11_04_nearest_2,
  title = {Gao, "Q3 2026 Fewer Deals, Bigger Bets: How Corporate Capital Is Concentrating US AI Venture Activity," PitchBook analyst note (21 Jul 2026)},
  url = {https://pitchbook.com/news/reports/q3-2026-fewer-deals-bigger-bets-how-corporate-capital-is-concentrating-us-ai-venture-activity},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

@misc{ro_ld11_04_nearest_3,
  title = {Lee, "How a 2016 Accounting Rule Fueled Big Tech's Investments in AI Startups," ProMarket (19 May 2026)},
  url = {https://www.promarket.org/2026/05/19/how-a-2016-accounting-rule-fueled-big-techs-investments-in-ai-startups/},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

@misc{ro_ld11_04_nearest_4,
  title = {Widder \& Kim, "How Big Cloud becomes Bigger: Scrutinizing Google, Microsoft, and Amazon's investments," SSRN working paper (Aug 2025), doi:10.2139/ssrn.5377426},
  url = {https://doi.org/10.2139/ssrn.5377426},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated; Judged from an abstract, summary or search listing only; Some details not confirmed}
}

@misc{ro_ld11_04_nearest_5,
  title = {Impink, "The Role of Complementary Technical Asset in Scaling: Evidence from AI Startups," HEC Paris Research Paper No. 1621 (1 April 2026); also SSRN 4977309},
  url = {https://ebslgwp.hhs.se/heccah/abs/heccah1621.htm},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated; Judged from an abstract, summary or search listing only}
}

@misc{ro_ld11_04_nearest_6,
  title = {Ando, Dinlersoz, Greenwood \& Piazzesi, "Technifying Ventures," NBER Working Paper 33993 (Jul 2025, rev. Mar 2026)},
  url = {https://www.nber.org/papers/w33993},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

@misc{ro_ld11_04_nearest_7,
  title = {AI and News, "European Commission's Investigation into AI Cloud Deals" (30 May 2026)},
  url = {https://www.aiandnews.com/blog/eu-antitrust-ai-clouds/},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated; Judged from an abstract, summary or search listing only}
}

@misc{src_ld11_ftc_6b_csp_ai_partnerships_2025,
  title = {FTC Office of Technology 6(b) staff report, Jan 2025},
  url = {https://www.ftc.gov/reports/ftc-staff-report-ai-partnerships-investments-6b-study},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

@misc{src_ld11_uk_cma_cloud_final_decision_2025,
  title = {UK CMA Cloud Services Market Investigation, final decision 31 Jul 2025},
  url = {https://www.gov.uk/cma-cases/cloud-services-market-investigation},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

@misc{src_ld11_uk_cma_cloud_actions_2026_03,
  title = {CMA package of actions, 31 March 2026},
  url = {https://www.gov.uk/government/news/cma-announces-package-of-actions-on-business-software-and-cloud-services},
  note = {Reference as recorded by SocioLens; authors, title and year are not separated}
}

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