Before You Apply for AI Funding, Decide These Three Things

The most interesting AI news in Korea this month wasn't a model release — it was where the money is going. The Ministry of SMEs and Startups said it will fund AI adoption for 175 small service companies with up to 100 million won per project, and a natural-language "AI helper" that answers small business owners' questions about policy, local market data and legal issues launches in September. Add the newly created support program for innovative small businesses adopting AI, and the number of publicly funded on-ramps aimed at very small teams has clearly grown.

Wherever you are, the pattern repeats: a grant, voucher or credit program appears, and the first question a team asks is "what should we apply for?" That's backwards. Funding doesn't create your project — it accelerates a project you already decided to do.

What does a public AI funding program actually mean for a small team?

Treat a grant as a way to pull a decided project three months forward, not as a reason to start one. If you invent a project to fit the application form, the work stops the day the program ends. Programs differ in structure, so match the type to your situation first.

• Adoption subsidies cover the cost of bolting AI onto an existing workflow — best when you already have a process that works.
• Staged programs fund a first phase (build a working model), review it, then release business funding and mentoring for a second phase. You need something you can demo, not describe.
• Consortium programs, like Korea's AI voucher scheme, require you to apply together with a registered supplier. Choosing the right partner from a fixed pool is half the work.
• Training-linked programs make coursework part of eligibility. Leaving that to the last week is how applications fall apart.

What should you settle before you apply?

One problem, one number, one owner. Without those three, any funded project ends as a thick consulting deck. Do this before you open the application form.

1. Log four weeks of repetitive work. An online pet supply store, for example, can tag every chat inquiry as shipping, stock, returns or other, and count minutes spent.
2. Write the problem in one sentence. Not "support is hard," but "the founder answers shipping and stock questions every evening."
3. Define success as a number you can verify, such as first response under five minutes, or fewer than one in five answers needing a human rewrite.
4. Build a minimum version without funding. A bot that answers your 30 most common questions is enough. What fails here will also fail with a grant behind it.
5. Write the application from that evidence. Reviewers respond to a working screen and four weeks of logs far more than to a plan.

How do you make sure something survives after the program ends?

The real risk isn't rejection — it's the running cost and ownership left behind when the project closes. Build costs may be covered, but monthly API usage and maintenance are yours. Confirm these in writing before signing with any vendor.

• Do you own the source code, design files and data?
• Are the AI API keys and cloud accounts opened under your company's name?
• What is the estimated monthly running cost after the program — and at double the traffic?
• Is handover documentation, including screen recordings, part of the deliverable?
• When a model is deprecated or prices change, who fixes it and at what rate?

So the task this season isn't reading every call for applications carefully. It's turning your own problem into one sentence. A team with a sharp problem gains three months if it wins funding, and still holds a working minimum version if it doesn't. A team that applies first and thinks later ends up with a report. Start with one thing this week: list the three tasks you repeated most over the past four weeks.