The Rise of AI Trading Firms: Why the Export Agency Fee Market is Restructuring
Last month at a lifestyle international trade show held at Tokyo Big Sight, while introducing South Korean companies' approaches to the Japanese market at our booth, an overseas sales manager from a mid-sized consumer goods manufacturer in the Kansai region asked me a rather earnest question: "Lately, when I go to Don Quijote or Loft, it's nothing but Korean cosmetics..."
In 2026, leading frontier AI labs simultaneously stepped away from being purely "companies that sell software." They chose implementation and services instead. This shift is by no means irrelevant to the traditional roles of Japanese trading firms (Sogo Shosha).
1. First, Three Major Events in the AI Industry
To start our discussion, let’s set aside our own product for a moment. First, let’s look at three facts that unfolded in the first half of 2026. Primary sources have been published for each.
① OpenAI Launched a Separate "Deployment" Entity
In May 2026, OpenAI established The OpenAI Deployment Company (DeployCo). Rather than simply selling model APIs, this business entity embeds "Forward Deployed Engineers" (FDEs) within client companies to redesign their business processes from the ground up. With an initial investment exceeding $4 billion, its backers include TPG, Goldman Sachs, SoftBank, and top consulting firms like McKinsey, Bain, and Capgemini. Simultaneously, OpenAI acquired Tomoro, a UK-based AI deployment consultancy, securing approximately 150 FDEs from day one.
- Primary Source: OpenAI launches the OpenAI Deployment Company
- Business Description: The OpenAI Deployment Company
② Anthropic Partnered with PE Firms to Create a Deployment-Only Joint Venture
A few days prior, Anthropic announced "Ode with Anthropic," a $1.5 billion joint venture with Blackstone, Hellman & Friedman, and Goldman Sachs. Building on the acquired Fractional AI, around 100 engineers work directly inside client organizations to overhaul core business operations. Reports indicate that the idea originated with Blackstone, which realized that neither major consulting firms nor boutique agencies could fill the critical execution gap when implementing AI across its portfolio companies.
- Primary Source: TechCrunch: Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models
- See also: CNBC
③ Sierra Priced "Outcomes" Instead of "Seats"
A parallel shift is happening in billing models. Sierra, led by Bret Taylor, adopted a performance-based pricing model that bills per successfully resolved customer issue rather than per seat or per message. Escalated issues are generally excluded from billing, and what constitutes a "success" is defined prior to signing the contract. Third-party estimates place this at roughly $1.50 per resolution, a billing structure that has helped Sierra double its ARR in a single year.
- Primary Source: Sierra: Outcome-based pricing for AI Agents
2. The Common Thread Linking These Three Facts
Though these look like separate headlines, they share the exact same underlying structure.
AI companies have begun charging for "execution" rather than licensing fees.
Instead of just delivering software and walking away, they embed people and systems directly into customer workflows and charge for outcomes. This is not a new invention. In fact, it is the exact same monetization model that trading companies have used for over a century.
A trading company's commission (margin) is not a charge for manufacturing costs. It is compensation for "finding the counterparty," "backing credit," and "handling tedious operations." This is precisely the conclusion the AI industry reached in 2026: selling execution is far easier to justify under a client's budget than selling software.
In short, what we are witnessing is "AI becoming a trading firm." If so, the inverse question naturally arises: to what extent will traditional trading functions be replaced by AI?
3. Deconstructing the Functions of Sogo Shosha (Trading Firms)
The export support functions of a Sogo Shosha can be broadly categorized into the following four layers:
| Layer | Function | Core Value Driver |
|---|---|---|
| A. Search & Discovery | Identifying foreign buyers, assessing market viability | Information asymmetry |
| B. Outreach & Engagement | Initial contact, multi-language support, relationship building | Human networks and language skills |
| C. Credit & Finance | Credit enhancement, L/C, forex, financing | Balance sheet and institutional credit |
| D. Operations & Logistics | Customs clearance, shipping, documentation, regulatory compliance | Licenses and physical operations |
Among these, Layers A and B are areas where generative AI has dramatically driven down marginal costs. Finding tens of thousands of potential buyers by country, executing hyper-personalized multi-language outreach in six languages, and classifying responses to gauge buyer intent—what was once a labor-intensive, human-hours cost trap in 2023 has fully transitioned into the domain of software by 2026.
On the other hand, Layers C and D remain unaffected. Someone must still shoulder the credit risk on their balance sheet, and customs clearance remains a licensed profession. What AI has commoditized is the pre-decision analytical phase, not the assumption of actual liability.
This is the most critical point of this article: trading companies will not disappear. Instead, only the specific layers within trading companies that can no longer justify their price tag will shift.
4. What Exactly Are Export Agency Fees Currently Paying For?
When a small-to-mid-sized manufacturer establishes an export channel, the expenses generally break down as follows.
First, let's look at the standard rates for domestic sales outsourcing services in Japan.
| Expense Item | Typical Price Range | Nature of Cost |
|---|---|---|
| Sales Agency (Fixed-rate) | 500,000 – 600,000 JPY / month per representative | Fixed cost based on labor |
| Telemarketing-focused (Fixed-rate) | 200,000 – 300,000 JPY / month | Same as above |
| Telemarketing-focused (Pay-per-performance) | 15,000 – 30,000 JPY / appointment | Cost per action |
| End-to-end (Inside & Field Sales) | 500,000 – 1,500,000 JPY / month, or 10–30% of contract value | Mixed |
Source: PRONI Imitsu "Average Cost and Fee Structure for Sales Agency Services", cocorobi "Sales Agency Fee Benchmarks [2026 Edition]"
For international projects, local labor and travel expenses are tacked on. Furthermore, pricing is heavily dictated by the scarcity of agencies operating in target markets. For example, because fewer providers cover the Middle East or Africa compared to Asia, rates naturally spike due to scarcity.
When mapping out what you are actually purchasing under each export strategy, the breakdown is as follows:
| Method | Cost Structure | Ownership of Customer Contact |
|---|---|---|
| Overseas Sales Agency | Monthly fixed fee + Performance bonus | Retained by the seller |
| Local Distributor | Sales margin | Shifted to the distributor |
| Trading Company (Sogo Shosha) | Buy-out spread | Most distanced from the seller |
Source: Link Global "What is Overseas Sales Outsourcing?"
Though the pricing models differ, these three options buy the exact same thing: paying someone else to handle "Search & Discovery" and "Outreach & Engagement."
The crucial element here is the budget pool used for retainers and performance bonuses. On corporate balance sheets, these are filed under "sales promotion expenses" or "professional fees," not "software licenses." The price points differ by orders of magnitude. A SaaS budget of a few hundred dollars a month and an agency budget of thousands of dollars a month operate on completely separate approval tracks.
And yet, what this larger budget pool is actually buying lies entirely within Layers A and B—the very domains where AI has already crushed marginal costs to near zero.
5. RINDA's Position: The Managed AI Trading Firm
This structural reality is why we do not refer to RINDA as an "AI sales tool" but rather call it a Managed AI Trading Firm.
With just a single website URL, RINDA autonomously runs the following sequence:
- Discovers potential buyers in target countries (Layer A)
- Designs and executes localized, multi-language outreach customized to each company's context (Layer B)
- Classifies incoming responses, handing off only high-intent leads to human reps
Until now, these steps required either dedicated international sales reps or full-service trading agencies.
On the flip side, we steer clear of Layers C and D. Existing players are infinitely stronger at managing credit, customs clearance, and physical logistics. Instead of competing there, our design philosophy is to lower the cost of Layers A and B to the price of machine cycles. This leaves companies with ample budget to spend on the specialized services of Layers C and D.
Let's look at the actual numbers
Because calling a service "cheap" without sharing hard data is disingenuous, here is our operational track record.
Operational Performance (As of April 2026, Cumulative)
| Metric | Actual Figure |
|---|---|
| Cumulative Emails Sent | 130,975 |
| Total Replies Received | 2,738 |
| Qualified Meetings | Over 600 |
| Paid Customers | 42 companies (As of July 2026) |
| Paid Churn Rate | 10.2% |
| Campaign Repeat Rate | 82% |
Pricing (Actual ARPU)
| Plan | Monthly Fee | Intended Audience |
|---|---|---|
| Basic | 350,000 KRW (approx. $260) | First-time exporters |
| Partners | 1,500,000 KRW (approx. $1,100) | Multi-country, multi-category |
| Enterprise | ~400M KRW / year (approx. $300k) | Government agencies, export support organizations |
| Performance Fee | 5% of deal value | Optional add-on to the above (currently active with 4 companies) |
Annual Cost Comparison
| Channel | Annual Cost (Est.) | Deliverables |
|---|---|---|
| Hiring 1 Full-Time Int'l Sales Rep | 50M KRW+ (~$37,000+) | Non-scalable personal effort. Requires months to ramp up. |
| Japanese Sales Agency (Fixed-rate, 1 rep) | 6.0M – 7.2M JPY (~$40k – $48k) | Dedicated work hours. |
| Premium Matching Agency (Korean Export Voucher) | 20M KRW (~$15,000) / one-off | Lead list + verification + meeting setups. No ongoing operations. |
| RINDA Basic | 4.2M KRW (~$3,100) | Continuous, year-round discovery, outreach, and response sorting. |
Calculations based on an exchange rate of roughly 1 JPY ≈ 9.3 KRW, and converted to USD equivalents.
Let's clarify the definitions of these metrics first.
The "2,738 replies" mentioned above includes out-of-office replies and automated bounce-backs. After auditing 6,076 rows of our raw data, we found that meaningful human replies accounted for about 27% of the total. The only metric that truly matters in this article is the "Over 600 Qualified Meetings"; total reply count should never be treated as a primary performance indicator.
It's a known industry issue that "response rates" are compared without a standardized definition—a pitfall we ourselves fell into initially. That is why we define our metrics transparently as follows:
- Sent (1 unit): An individual, successfully delivered email (excluding bounces).
- Reply (1 unit): Any response received, including auto-replies (not used as a success metric).
- Qualified Meeting (1 unit): An actual business meeting scheduled and held upon mutual agreement.
The true value of this comparison is not just about the absolute cost. It is about using a uniform metric—"cost per outcome"—to finally compare AI and human sales channels side-by-side.
Note the charging mechanism. Traditional Japanese sales agencies command 10% to 30% of contract values on performance, and trading company commissions scale proportionally with transaction volume. RINDA's success fee is just 5% of the finalized deal. We are operating on the same "fee-for-outcomes" model, yet our percentage is a whole order of magnitude lower. This is not because we are underselling ourselves; it is because the marginal costs of buyer discovery and initial outreach have physically bottomed out.
In procurement meetings, the question changes from "Do we really need this software?" to "Is this fee rate reasonable?" The latter is a much easier approval to secure because it leverages a budget category that companies are already accustomed to paying.
6. Let's Be Clear: This is Reallocation, Not Replacement
Lastly, let me make one thing absolutely clear.
This article is not an argument for bypassing trading companies or customs brokers. Quite the contrary.
Among the functions traditionally held by Sogo Shosha, search and initial outreach commanded high premiums because their profitability relied on information asymmetry. Now that this asymmetry has shrunk, continuing to charge high premiums for these steps is unsustainable for both buyers and sellers.
Conversely, functions like credit, financing, and logistics operations will not lose value; they will actually become scarcer and more valuable. As automation dramatically scales up the volume of qualified business meetings, demand for specialized operations that can execute those deals will skyrocket.
This is why we do not view trading companies, freight forwarders, or customs brokers as competitors. If RINDA generates a high volume of upstream business opportunities, and established logistics players execute the downstream trade, this division of labor increases the pie for everyone. Indeed, our most successful client engagements are with companies that already possess in-house trade compliance and operational expertise.
AI trading firms do not replace traditional trading companies. They simply take over the specific service layers whose costs have become the hardest to justify.
The subsequent negotiations, credit backing, customs clearances, and the final handshake will always remain human endeavors.