The Numbers That Don't Appear on the Quote
"How much should we budget for AI adoption?" Last week, the CEO of a mid-sized manufacturer asked me that, coffee cup half empty. Three quotes sat on the table between us. The lowest: 38 million KRW. The highest: 240 million KRW. Same requirements document, same automation scope.
It took me thirty minutes to explain the six-fold gap. Only then did he quietly say, "I've been reading nothing but quotes this whole time." That one sentence is why I'm starting this series.
Rethinking AI Adoption Cost: Start with Scale
The most common misconception about AI adoption cost in 2026 is assuming the question "how much?" is even valid on its own. Real budgets swing by a factor of ten or more depending on scale and purpose.
Pulling industry data together, the picture looks roughly like this. A PoC (proof of concept) scoped to a single internal task — document summarization, a chatbot for one department — starts at 2 to 8 million KRW. Push that into real production deployment and you're looking at 10 to 50 million KRW. Company-wide adoption typically runs 50 million to 200 million KRW or more. Overseas numbers line up: for US SMEs, five-year total investment is reported in the USD 200K to 500K range.
Honestly, these numbers are reference points, not answers. The real variable driving that six-fold spread isn't scale — it's the state of your data.
Sticker Price vs. Total Cost
Three line items rarely show up on the initial quote.
First, data cleaning cost. When your internal documents are scattered across PDFs, Excel sheets, and messenger logs, shaping them into a form the AI can actually read can add tens of millions of KRW on its own. This is the single most common place budgets blow up when moving from PoC to production.
Second, operations and maintenance. GPU, API calls, vector DB, retraining — combined, these typically run 20-40% of initial development cost as a recurring annual expense. You need to think of this as "something that has to be retrained a year later," not "build it once and you're done." I'll cover this in Episode 4.
Third, integration cost. How many existing systems you have to connect to — ERP, groupware, inventory — can decide more than half of development cost. What looks like a one-line "ERP integration" in the requirements doc can turn into who-knows-how-many person-months once you actually open it up.
Why the 2026 Budget Looks Different
A recent survey found that 79.3% of Korean companies increased their generative AI budget this year. Nearly half of those grew by more than 20% year over year. Korea's Ministry of SMEs and Startups alone allocated 799.2 billion KRW, with the total national AI budget structured at 9.9 trillion KRW. Translation: more compute vouchers, adoption consulting, and other support programs are on the way.
At the same time, there's a countercurrent. Major LLM API prices were revised upward in 2026, and token usage commonly balloons to 2-3x initial estimates at rollout. Which means the "start with an API, it's cheap" logic flips once you scale up. I'll break down where that break-even point sits in Episode 3.
Getting the Sign-Off
What a mid-sized CEO ultimately needs on the approval sheet isn't "how much" — it's "how much, when, and why". Three questions to close out this episode:
- How much will you spend in the first four weeks? — That's the PoC budget. The goal is validation, not completion. Next episode.
- How much goes out annually to run it? — 20-40% of adoption cost. If that number isn't on the approval sheet, your third-year budget review is going to wobble.
- When does it start paying back? — I'll cover how to calculate ROI as a metric rather than a gut feeling in Episode 5.
Just placing those three numbers next to the quotes cuts about half of the six-fold gap into something you can actually see.
What's Next
Next episode: what you're actually buying during those four weeks of PoC. Mistake a PoC for an ROI validation and the budget doubles. I'll lay out where the objective of validation should sit and what deliverables you should be receiving — from the perspective of the person signing off on the budget.
If you're staring at a quote right now, our 5years+ free consultation starts by examining the state of your internal data. Checking that data before you receive the quote is the fastest way to shrink that six-fold spread.