Conclusion First: Outsourcing Accounting Costs Will Soon Be Unnecessary

For small and medium-sized enterprises in rural areas, back office costs can be a significant burden.

Monthly advisory fees for accountants and tax advisors range from 30,000 to 50,000 yen, bookkeeping services cost 20,000 to 30,000 yen per month, and annual settlement fees range from 150,000 to 300,000 yen. Hiring a part-time accountant incurs personnel costs of 2 to 3 million yen a year. Additionally, outsourcing data analysis and reporting can cost tens of thousands of yen per project.

When totaled, these costs exceed 3 million yen annually. For a company with annual sales of 100 million yen, this means that 3 to 5% of profits are disappearing into back office expenses.

This structure is currently beginning to break down.

AI bookkeeping platforms like Tabby, invoice processing AI, and BI automation tools can potentially reduce back office operational costs to below 50,000 yen a month when combined.

You might wonder, “Is there really such a good deal?” Let’s take a closer look.

What Tabby Disrupts — The Sacred Realm of “Monthly Bookkeeping”

Tabby is an AI platform that automatically generates ledgers in real-time. By connecting bank accounts, credit cards, and invoice data, entries are automatically created, and profit and loss can be visualized in real-time.

Traditionally, this work was done by bookkeeping service providers or in-house accounting personnel.

The going rate for bookkeeping services is 20,000 to 50,000 yen per month, totaling 240,000 to 600,000 yen annually. If you hire a part-time accountant in-house, it would cost 1.5 to 2.5 million yen a year. This can be replaced by a subscription to a tool like Tabby for just a few thousand to tens of thousands of yen per month.

What’s important here is that it’s not just about reducing costs.

Traditional bookkeeping was fundamentally based on a “monthly” cycle. Receipts were gathered at the end of the month, entries were made the following month, and it would take 2 to 3 weeks to see the numbers. This meant that business owners were always making decisions based on “past numbers.”

With Tabby’s real-time bookkeeping, today’s sales, today’s expenses, and today’s profit and loss are visible. This is not just about “cost reduction”; it’s about “changing the speed of decision-making.”

Imagine a restaurant with monthly sales of 5 million yen. One that only knows its profits at the end of the month versus one that can see profits daily. Which one can make more accurate purchasing decisions? The answer is clear.

What Invoice AI Kills — The Time Thief of “Data Entry”

Next, let’s discuss invoice processing.

The biggest time sink for accounting personnel in small and medium-sized enterprises is actually “data entry.” Receiving invoices, verifying their contents, and manually entering them into accounting software. For a company processing 100 invoices a month, this task alone can take 20 to 30 hours. For a part-time worker earning 1,200 yen per hour, that’s about 350,000 yen a year spent on invoice data entry.

Currently, several tools have emerged that use OCR and AI to automatically read invoices and generate entries. Domestic services like sweeep, invox, and Bill One are increasing the options available.

The accuracy is 95 to 99%. This means that only 1 to 5 invoices out of 100 need to be checked by a human. The 30 hours of work per month can be reduced to just 1 to 2 hours of checking.

The annual personnel cost of 350,000 yen can be transformed into an annual tool cost of just 50,000 yen.

Moreover, input errors drastically decrease. “I misentered the invoice amount by one digit, and the settlement was off” — this is a common issue in small business accounting, but AI can reduce such mistakes to nearly zero.

What BI Automation Changes — The Misconception That “Analysis is for Large Corporations”

Now we reach the core of the discussion.

Once bookkeeping and invoice processing are automated, data will accumulate automatically. Sales data, expense data, client data, seasonal fluctuation data. The numbers that were previously dormant in accounting software will be stored in an analyzable state.

The problem has been that small and medium-sized enterprises lack individuals who can “analyze” this data.

BI tools (like Tableau and Power BI) have existed, but using them required data engineers or analysts. Outsourcing could cost 500,000 to 2 million yen per project, which was out of reach for small businesses.

This is where LLM (Large Language Model) based BI automation comes into play.

Recent research has highlighted approaches like BI-Agent, which allow users to ask natural language questions such as, “What caused the profit margin to drop compared to last month?” or “Which product categories are seeing sales growth?” and automatically execute data extraction, transformation, analysis, and visualization.

In traditional BI processes, 60 to 80% of the time was spent on data preprocessing. By automating this preprocessing with LLMs, the time and cost associated with analysis can be dramatically reduced.

This signifies the collapse of the structure that says, “Data analysis is a privilege of large corporations.”

Even a construction company with monthly sales of 3 million yen will be able to ask AI, “Which construction projects have the highest profit margins?” or “Which subcontractors offer the best cost performance?” and receive answers in seconds.

Timeline — Realistic Steps Until “3 Million Yen” Disappears

Instead of abstract future predictions, let’s outline what needs to be done starting today.

Months 1-2 (Implementation Phase): Automate Bookkeeping and Invoice Processing

• Connect an AI bookkeeping function like Tabby to cloud accounting (such as freee or Money Forward)
• Implement invoice AI (like sweeep or invox) and establish a flow for scanning paper invoices and automatic entries
• Cost reductions at this stage: Bookkeeping service fees of 20,000 to 50,000 yen per month + 50% reduction in part-time accounting labor.

Months 3-4 (Data Accumulation Phase): An Analytical Foundation Forms Automatically

• Once two months of data accumulates, monthly comparisons become possible
• The reporting function of cloud accounting automatically visualizes trends in sales, expenses, and profits
• Cost reductions at this stage: Outsourcing fees for monthly report creation of 10,000 to 30,000 yen.

Months 5-6 (Analysis Phase): Start Asking AI “Why?”

• Implement LLM-based BI functions (like ChatGPT integrated with spreadsheets or BI-Agent tools)
• “What caused the profit margin to drop by 2% compared to last month?” → AI breaks down expense items and provides answers
• Cost reductions at this stage: Elimination of annual outsourcing fees for data analysis of 500,000 to 2 million yen.

Month 7 Onwards (Optimization Phase): Automating Forecasting and Decision-Making

• LLM generates sales forecasts and cash flow projections from historical data
• Answers to questions like “Will cash flow be okay next month?” or “Should we take on this project?” are provided numerically
• Consultations with accountants can be limited to “annual settlements and tax filings” only

The landing point six months from now: Annual back office costs drop from 3 million yen to 500,000 to 600,000 yen. The difference of 2.4 million yen becomes pure profit.

So, What Should Be Done?

Just three things need to be done.

1. Stop using paper. Make all invoices and receipts digital. This is the entry point for automation. From January 2024, the electronic storage law for electronic transaction data will be fully mandated. There is no longer any reason not to do this.

2. Implement cloud accounting and invoice AI. This will cost around a few thousand to 10,000 yen per month. Compared to the personnel costs of a part-time accountant, this is a negligible amount. Just try it for one month.

3. Review contracts with accountants. After delegating bookkeeping and monthly reports to AI, ask accountants only for “tax judgments” and “settlements.” You should be able to negotiate advisory fees to less than half.

What I want to clarify here is that this does not mean that accountants will become unnecessary. Tax judgments, tax-saving strategies, and responses to tax audits — these remain the domain of experts. What becomes unnecessary are the tasks of “bookkeeping,” “data entry,” “aggregation,” and “report creation,” not the judgments.

On the contrary, accountants freed from these tasks can focus on higher-level advisory roles. For small and medium-sized enterprises, the money previously spent on accountants for monthly bookkeeping can be redirected to “annual strategic tax consultations.” This is beneficial for both parties.

Why Local SMEs Can Ride This Wave

Large corporations face delays due to existing core systems, internal approval processes, and coordination with IT departments — changing these takes time.

In a company with 10 employees, if the president says, “We will use this starting next month,” that’s the end of it. The speed of decision-making directly translates into competitive advantage.

A cost reduction of 2.4 million yen may be a rounding error for large corporations, but for a small business with annual sales of 50 million yen, it can significantly improve profit margins by nearly 5%.

When the cost of technology decreases, the greatest beneficiaries are those who could not afford those costs before.

The automation of back office functions is no longer a “future story.” The tools are ready. It all comes down to whether to act or not.