Project summary

I am seeking USD 30,000 for a six-month continuation of my research on firms entering publicly funded AI research in South Korea. The question is whether expanded participation opens a route for new enterprises and different founder backgrounds, or mainly brings established organisations into newly labelled programmes. The minimum is USD 18,000 for a four-month validation stage.

The project will connect dated professional histories to research-funding participation. It will distinguish founders from later CEOs, founding dates from first appearance in the funding records, and employment at a large firm from an internship or a collaboration. The resulting evidence can help innovation researchers and programme designers examine who gains access to publicly supported AI work.

What already exists

The current research has an organisation register with 4,335 records. A 29 September 2026 checkpoint records lookup histories for 363 organisation keys, not 363 fully verified founder biographies. Its latest 100-key batch identified 12 company candidates with evidence supporting founder relationships and 15 associated people. These counts are progress records, not population estimates. Unresolved identities and missing education or employment dates remain visible.

My earlier published research examines government support for emerging and mature ICT sectors and diversity in subsidised collaboration. The new work addresses the people and entry histories behind programme participation. The existing register is the starting point for the completion and validation stage described below.

The funded next stage

I will maintain a dated completion log and select 400 additional or unresolved company records under a stratified rule spanning entry period, company type and available AI-related project evidence. Assistants will record the source and date for each professional claim. We will attempt all 400 audits; verified biographies are an outcome, not a promised count. A second reader will independently check at least 80 company records. The minimum stage will attempt 200 audits and 40 independent checks.

Coding will separate degree completion from enrolment, professional employment from internships, and pre-founding from later experience. Missing biographies will not be coded as no degree or no prior job. Potentially duplicate company identities will remain unresolved until the available evidence supports a merge. The initial 50 records will test the time budget and coding definitions before the remaining work proceeds.

I will examine first observed programme entry and subsequent participation against documented founder experience, reporting observability and sample-weighting sensitivity. Where histories support it, the analysis will distinguish entry after corporate employment, academic research and earlier entrepreneurship. The study cannot infer that AI caused people to leave large employers, or estimate graduates' propensity to found firms without the relevant denominator.

Investment rounds, exits and novelty are possible extensions. They enter the funded analysis only if identity, dates, coverage and permitted use are adequate. The core deliverable does not depend on obtaining a commercial investment database. If linkage is too weak, the report will document where the claims fail and present valid programme-entry results.

Deliverables and schedule

Month one fixes scope, sampling and a 50-record pilot; months two to four cover evidence collection and checks; month five covers analysis; month six completes a working paper, an aggregate policy brief and an executable codebook and reproducibility package. Progress reports follow the pilot and main audit. The four-month minimum produces the smaller audit and a focused paper.

Public outputs will include aggregate results, definitions, code and permitted source references. Personal career dossiers and restricted data will not be promised as a public download. Named policymakers or organisations have not agreed to use the findings.

Research progress during fundraising

This research is already underway and may progress while fundraising continues. The hours and costs below are proposed budgets, not a record of work already performed. Before receiving funds, I will update the completion log and identify any work on this specified stage performed during fundraising. I request that documented research time and direct costs from this stage be eligible for support, including work before disbursement where Manifund explicitly approves it in writing. Earlier completed work is background to this request. I will not charge the same time or expense to another grant. If the stage finishes before funding is available, I will seek approval for retrospective support or revise or close the request; I will not present completed work as still outstanding.

Budget

The full USD 30,000 budget is USD 15,000 for 200 hours of my time at USD 75; USD 6,000 for 240 assistant hours at USD 25; USD 2,000 for 40 independent-review hours at USD 50; USD 1,500 for data retrieval and computing; USD 500 for documentation and release; and USD 5,000 for prospective submission and publication costs.

The USD 18,000 minimum is USD 9,000 for 120 hours of my time, USD 3,000 for 120 assistant hours, USD 1,000 for 20 independent-review hours, USD 500 for data, USD 500 for release and USD 4,000 for publication costs. These are proposed task-based allowances; personnel have not yet been hired.

Publication costs are prospective reserves, not journal quotations or a promise of acceptance. I will check institutional coverage and waivers, document actual charges, and seek approval to reallocate or return unused funds. The public working paper and permitted research materials will be released even if journal review continues beyond the project. Compensation figures are gross project costs.

Risks and useful outcomes

The main risk is uneven coverage of professional histories. If sources do not support a biography or a company link, that case will remain unresolved. The output will report the attempted sample, verified subset and limits of any comparisons. Investment and exit analyses will be omitted if their coverage is inadequate.

Researcher and other support

I am Hana Kim, a contract research professor at KAIST's School of Business and Technology Management in South Korea. I hold a PhD in Technology Management, Economics and Policy and a master's degree in medicine from Seoul National University. I will lead the funded work from Korea. Assistants and independent reviewers will be paid from the grant and recruited once support is secured.

This proposal is separate from the AI-checking evaluation submitted to Emergent Ventures and published on Manifund. Existing shared resources will be recorded once, and I will agree a workable schedule before accepting simultaneous awards. Publication costs apply only to this project's outputs. Any coauthored source materials will be used with the appropriate permissions and attribution.

I am not currently receiving a separate research grant for the work proposed here. I participate in an institution-administered research institute project supported by the National Research Foundation of Korea (NRF). That participation is not presented here as a personal grant award. I will check the allocation of research time and expenses so that any costs covered by the institutional project are not also charged to this grant.

Academic profile: Hana Kim at KAIST BTM