"We can't make decisions without the president." "The leadership's thinking never reaches the front lines." A growing number of companies face challenges like these.

In a 2025 survey of 784 executives and HR professionals titled "Survey on the Realities and Challenges of Instilling Corporate Philosophy," conducted by Imajina Inc., it became clear that while awareness of the challenge of instilling corporate philosophy is high at many companies, they struggle with concrete ways to promote it. The most common measures for instilling philosophy were "posting it on the company website," "distributing brochures," and "putting up posters"—but these are all forms of "one-way communication," and there are limits to how well they help employees internalize the philosophy as their own.

Against this backdrop, the "CEO bot"—which trains AI on a leader's philosophy and decision-making criteria so that employees can consult them through dialogue—is drawing attention. In 2025, Sumitomo Mitsui Financial Group developed an AI modeled on its president, called "AI-CEO," and made it available to roughly 30,000 domestic employees of Sumitomo Mitsui Banking Corporation, which became a notable topic.

This article explains how a CEO bot works, where it can be used, the data needed to build one, how to roll it out, and the risks to watch for.

What Is a CEO Bot?

A CEO bot is a chatbot that trains generative AI on a leader's statements, ideas, and decision-making criteria, allowing employees to consult the leader's way of thinking through dialogue. It is also called an "AI president," "executive AI," or "CEO clone."

A common misconception is that a CEO bot is something that "makes management decisions on the president's behalf." It is not. It is strictly a system that returns "reference opinions" reflecting the leader's thought patterns and values. When an employee asks, "How would the president think about this matter?" they receive an answer based on past statements and management policy—that is the basic function.

The technical foundation of a CEO bot is a mechanism called RAG (Retrieval-Augmented Generation). You build a database from the leader's recorded statements, internal documents, management policy materials, and so on, and the AI generates answers to employees' questions while searching that database.

Why Are CEO Bots in Demand Now?

Three structural challenges lie behind the attention CEO bots are receiving.

The Management Philosophy Doesn't Reach the Front Lines

The 2025 White Paper on Small and Medium Enterprises in Japan shows that businesses that work to share their management philosophy and vision tend to perform better. Instilling philosophy is an important management theme, but conventional methods (reciting it at morning meetings, internal newsletters, posters) are one-way, and there are limits to how well they foster understanding tailored to each individual employee's situation.

A CEO bot lets employees ask questions specific to their own work and receive answers from the leader's perspective, turning "one-way communication" into "two-way dialogue."

Key-Person Dependency in Decision-Making

In small and medium-sized enterprises, important decisions tend to concentrate in a single leader. A state of "we don't know unless we ask the president" not only creates a decision-making bottleneck but also carries the risk that business stalls when the leader is absent. A CEO bot mitigates this key-person dependency by providing reference information for everyday decisions. For measures against key-person dependency itself, please also see How to Eliminate Key-Person Dependency.

Business Succession and the Severing of Philosophy

According to Japan's Small and Medium Enterprise Agency, while the rate of businesses without a successor is trending downward, the average age of business owners remains at a high level. In business succession, what is most easily lost is the background behind the previous leader's decisions—the "why did they decide that way." A CEO bot can be a means of accumulating a leader's decision-making criteria and values as a digital asset, making them referenceable across generations.

Five Ways to Use a CEO Bot

1. Responding to Everyday Questions from Employees

The most basic use is to provide feedback from the leader's perspective on everyday decisions such as "How should I handle this customer?" or "Is this direction for the new business proposal acceptable?" With Sumitomo Mitsui FG's AI-CEO, employees use it to polish proposals and to talk through their work (Source: DX-link official article).

2. Instilling the Management Philosophy

When a new graduate or mid-career hire wonders, "Why does our company do things this way?" they can ask the CEO bot and receive an answer grounded in the company's philosophy. Unlike one-way e-learning, it is a dialogue format that starts from the employee's own question, which makes it easier to deepen understanding.

3. New-Hire Onboarding

Employees who have just joined take time to grasp company rules and culture. When the CEO bot returns consistent answers to questions about organizational culture—such as "What does this company value?" or "What kind of behavior is rewarded?"—the quality and speed of onboarding improve.

4. Recruitment and Company Briefings

This is a system in which a CEO bot is made public for job seekers, and the AI answers questions about the company's philosophy and culture. By placing it on a recruitment site or LINE, you can give even job seekers who cannot attend company information sessions an opportunity to engage with the leader's way of thinking.

5. Recording the Philosophy for Business Succession

This use records a leader's thought patterns and decision-making criteria in AI while the current leader is still active. A system that lets a successor consult "how would the predecessor have decided?" prevents a break in philosophy and makes the generational handover smoother.

Three Types of Data Needed to Build a CEO Bot

The answer quality of a CEO bot depends heavily on the quality and quantity of the data it learns from. The necessary data is collected in three categories.

Statement Data

This is data that directly records the leader's own words. It includes in-house lectures and morning-meeting speeches, interview articles, social media and blog posts, and records of dialogues with employees. In developing Sumitomo Mitsui FG's AI-CEO, the president's statements inside and outside the company were transcribed, and interviews with executives and others about "the president's character" were also conducted (Source: DX-link official article). This data on "the persona as seen by those around them" is reported to have been important in adding a human touch to the AI's answers.

Document Data

These are official documents that reflect the leader's thinking. They include the management philosophy, vision, and code of conduct; medium-term management plans; messages to shareholders; management policy statements; and minutes of past decisions. In particular, records of statements made in management meetings vividly reveal the leader's decision-making process, so they greatly influence the quality of a CEO bot.

Behavioral Data

This is indirect data for inferring the leader's decision patterns. It includes the history of past decisions (what was approved and what was rejected), the background to changes in customer-response policy, and evaluation criteria used in hiring. It is important as data that supplements the "implicit decision-making criteria" that do not appear in statements or documents.

The more data you collect, the better, but as a minimal configuration, you can build a basic CEO bot with an interview of the leader (transcribed from two to three hours), documents on the management philosophy and vision, and internal messages from the past one to two years.

How to Roll Out a CEO Bot

Step 1: Define the Purpose and Scope of Use

First, clarify "for what purpose" and "for whom" the CEO bot will be used. Is the goal to instill philosophy internally, to brief candidates during recruitment, or to record knowledge for business succession? The data needed and the scope of disclosure change depending on the purpose.

Step 2: Collect and Organize the Data

Collect data along the three categories described above. In interviewing the leader, it is important not merely to record their statements but to dig into the background of "why they think that way." To extract decision-making criteria, it is effective to use specific cases and ask, "How would you decide in this situation? And why?"

Step 3: Build and Tune the AI

Incorporate the collected data into a RAG system and adjust the AI's answer quality. Especially important is reproducing the leader's "manner of speech" and "tone." In Sumitomo Mitsui FG's case, it is reported that reproducing the president's own way of speaking required trial and error in tuning the prompts and the RAG (Source: DX-link official article).

Step 4: Verify Quality

Have the leader and senior executives review the answers produced by the built CEO bot to verify "the president would/would not say this." It is also necessary to check whether the answers contain factually incorrect responses (hallucinations) and whether the bot gives inappropriate answers on sensitive topics.

Step 5: Operate and Improve

After releasing it internally, you need to monitor usage and update the data regularly. Because a leader's statements and policies change over time, add data every six months to a year to keep the answers fresh.

Limitations and Cautions of a CEO Bot

A CEO bot is a promising system, but it is not a cure-all. Before adopting one, you should understand the following risks.

It Is Not a Substitute for Final Decisions

A CEO bot's answers are strictly "reference opinions based on the leader's thought patterns." It is not appropriate to entrust legally binding decisions, personnel-related judgments, or judgments concerning major contracts to AI. As an operating rule, you need to make it clear that the CEO bot's answers are not grounds for final decisions.

The Risk of Hallucination

Generative AI carries the risk of "hallucination"—plausibly generating information that differs from fact. In the case of a CEO bot, it may output something the leader never actually said as "the president's view," which can become a source of misunderstanding or trouble. It is important to combine it with source citations and fact-checking mechanisms.

Dependence on Data Quality

The quality of a CEO bot is directly tied to the quality of the data it learns from. If there is little statement data from the leader, or if it is biased, the answers will likewise be biased. If you release it internally while the data is insufficient, the impression that "the CEO bot is useless" will take hold, and recovering from that afterward is difficult.

Companies It Suits and Companies It Doesn't

A CEO bot is especially effective at companies that meet the following conditions: the leader is motivated to put their philosophy and ideas into words; the headcount has grown and the leader has fewer opportunities to speak directly with every employee; and a business succession is approaching, making it necessary to record the leader's insights.

Conversely, it is not necessarily a good fit for companies where the leader is reluctant to put their philosophy and policies into writing.

Summary

A CEO bot is a system that reproduces a leader's philosophy, ideas, and decision-making criteria with AI, allowing employees to consult them through dialogue. It is gaining attention as a new approach to challenges that conventional methods struggled to solve—instilling philosophy, mitigating key-person dependency in decision-making, and recording knowledge for business succession.

When building one, it is important to collect high-quality data from three categories—the leader's statement data, document data, and behavioral data—and to raise quality in stages. At the same time, the conditions for success are recognizing that it is not a substitute for final decisions and that there is a risk of hallucination, and then using it under appropriate operating rules.

At Teraverse, we apply the technology for reproducing thought and personality with AI that we established through our joint research with Kyoto University on the Buddhist dialogue AI "BuddhaBot," and we provide development of conversational AI and personal AI that carries on a leader's philosophy. If you are interested in turning your management philosophy into AI, please feel free to contact us.