Conclusion First: “Relying on a Single AI is Now Just a Risk”

Microsoft CEO Satya Nadella made it clear. “Companies that depend on a single AI may not survive.”

This is a warning to large corporations. Companies that have spent billions of yen contracting with specific AI vendors and have deeply integrated them into their internal systems are now finding themselves unable to move.

Interestingly, small businesses are largely unaffected by this issue. Since they haven’t made significant investments from the start, switching AIs or using multiple options is easy for them.

ChatGPT Plus for 2,000 yen a month. Claude Pro for 3,000 yen a month. Free-to-use Gemini. The state of small businesses using multiple AIs in small increments due to “lack of budget” has, in effect, turned into a multi-AI strategy.

While large corporations are trying to spend hundreds of millions of yen to promote “multi-vendor strategies,” small businesses are achieving this for under 10,000 yen a month. This reversal is the essence of what is happening now.

Why Did Large Corporations Fall into “Single Vendor Dependency”?

So, why did large corporations fall into the trap of relying on a single AI? The reason is simple.

The underlying thought is that “if we don’t unify, we can’t manage.”

Large corporations have thousands or tens of thousands of employees. If everyone starts using different AIs, security management and cost management become impossible. Therefore, they adopt policies like “the company standard is OpenAI’s GPT-4” or “we will unify under Azure OpenAI Service.” This decision was rational.

The problem is that this “rational decision” has begun to act as a constraint.

From the second half of 2024, the landscape of the AI industry has changed dramatically. China’s DeepSeek has started offering GPT-4-class performance at a low cost. Anthropic’s Claude is increasingly outperforming GPT in coding and long text analysis. Google’s Gemini has carved out its own territory with an unprecedented context length of one million tokens. Moonshot AI’s Kimi K2 has been released as open-source, with API costs a fraction of GPT-4’s.

In other words, the “strongest AI” is no longer fixed. We have entered an era where the optimal AI varies by task.

In such a context, what happens to large corporations that have integrated their entire systems with a single AI? Even if they want to switch, the costs of integration with existing systems, internal prompt assets, and redoing security reviews are so enormous that they cannot move. This is vendor lock-in in its purest form.

According to a survey, the transition costs for large corporations switching AI vendors can reach 30-50% of the initial implementation costs. If they spent 100 million yen to implement it, switching would cost 30 to 50 million yen.

This is the true nature of the “single vendor dependency risk.”

Why Small Businesses Were “Right from the Start”

So, what about small businesses?

To be clear, small businesses adopting a multi-AI strategy is not because it is “strategically correct.” It just happened because they lack budget.

However, this has turned out to be the right approach.

Take a look at how the local small businesses we support are using AI:

• Summarizing meeting minutes and drafting emails → ChatGPT (2,000 yen/month)
• Checking contracts and analyzing long texts → Claude (3,000 yen/month)
• Aggregating internal data and linking spreadsheets → Gemini (free to 2,900 yen/month)
• Image generation (for social media posts) → Canva’s built-in AI or Midjourney (about 1,500 yen/month)

Totaling under 10,000 yen a month. Even a company with five employees can operate effectively.

Moreover, the biggest advantage of this setup is “the ability to switch at any time.”

If they feel ChatGPT’s performance has declined, they can switch to Claude. When a new model comes out, they can try it for a week and make a judgment. If they are using it via API, they only need to change the endpoint URL and API key. The switching cost is almost zero.

While large corporations are trying to spend tens of millions of yen to achieve “multi-vendor strategies,” small businesses are doing it unconsciously for under 10,000 yen a month.

Whether they recognize this structural reversal will be a decisive factor moving forward.

“Agility” Has Become a Strategic Advantage

What is important here is to reinterpret “we became this way because we lack budget” as “that’s why we are strong.”

The speed of AI evolution is extraordinary. The strongest model from six months ago can drop to second or third place in terms of cost-performance today. In a market that changes at this speed, slowness can be fatal.

Large corporations take six months to select a single AI. By the time they get approvals, conduct security reviews, and roll it out company-wide, the next model has already been released.

Small businesses can implement a new AI the day after the CEO says, “This looks good; let’s try it starting tomorrow.” If it doesn’t work, they can stop using it the following week. This speed of decision-making is the greatest weapon in the AI era.

Furthermore, employees in small businesses using multiple AIs naturally develop higher AI literacy. They can make on-the-ground judgments like, “Claude is suited for this task” or “Gemini is more accurate for number aggregation.”

Employees in large corporations who are told, “the company standard is GPT-4” continue to use it without even knowing its strengths and weaknesses. It is clear who is truly mastering AI.

So, What Should Be Done Specifically?

For small businesses to consciously adopt a multi-AI strategy, they only need to focus on three things.

1. First, Get Hands-On Experience with Three AIs for Free to 3,000 Yen a Month

ChatGPT, Claude, Gemini. Ensure everyone has access to these three. Free plans are fine. The starting point is to experience the “differences.”

2. Record “Which AI Worked Best” by Task

You don’t need to do anything complicated. Simply record “task details,” “AI used,” and “satisfaction level (◎○△)” in a Google Spreadsheet. After a month, you will start to see the optimal usage for your company.

3. Try New Models Every Three Months

The AI industry changes in three months. Make it a habit to try a new, trending model for just one week every quarter. If it doesn’t fit, you can revert back. The cost is almost negligible.

By simply implementing these three steps, small businesses can acquire the “AI utilization foundation” that large corporations are trying to build for hundreds of millions of yen, for under 10,000 yen a month.

How Long Will This Reversal Structure Last?

To be honest, this advantage will not last forever.

Large corporations are beginning to adopt AI gateways and routing technologies (systems that automatically allocate the optimal AI model based on task content). Once this matures, large corporations will also be able to efficiently use multiple AIs.

That’s why now is the time to seize the opportunity.

At this very moment, while large corporations are struggling with multi-AI strategies, small businesses can leverage their agility to maximize the benefits of AI. Whether they seize this 2-3 year window will significantly change the future for local small businesses.

There’s no need to spend 3 million yen on AI consulting. All it takes is 10,000 yen a month and a CEO’s simple statement of “let’s try using it first.”

This is one of the few structural opportunities for small businesses to compete with large corporations in the AI era. This is an opportunity that should not be missed.