AI Essentials for Executives and Managers: 5 Steps to Turn "Intimidating" into a Strategic Company Asset

What Exactly is AI? Comparing "Traditional AI" and "Generative AI" Using a Cooking Analogy

It can be hard to visualize what actually changes when someone mentions "AI adoption." Let's organize the basics first. Traditional AI and the recently trending Generative AI have completely different roles. If you implement them without understanding these differences, you may end up with disappointing results.

Traditional AI is an "Excellent Calculator"

Traditional AI excels at finding the correct answer from massive amounts of data. For example, predicting next month's sales based on past sales data, or judging "this is a defective product" by looking at images. In terms of cooking, it's like a"Cooking robot that perfectly follows a set recipe". It's not good at subtle adjustments to seasoning, but it excels at making the same taste in large quantities. In other words, it's"technology that derives the optimal answer to a question with a correct solution".

Generative AI is a "Creative Secretary"

On the other hand, Generative AI can create something from scratch. It generates text, images, code, etc. In terms of cooking, it's like a"Chef who thinks up and proposes new menus from leftover ingredients in the fridge". For questions without a correct answer, it drafts proposals like "How about this suggestion?" As mentioned in reference articles, Generative AI can be handled even without specialized knowledge, but it requires the ability to give clear instructions on "what to request." In other words, the difference is"AI that creates answers where there are no correct solutions".

The key point is that Traditional AI excels at "classification and prediction," while Generative AI excels at "creation and generation." It is important to use both according to their intended purposes.

Why Do Managers Need to Know About AI Now?

Don't you think "It's fine if the technical department handles it"? Actually, the most important thing is the manager's understanding. AI is a tool, and humans are the ones who master it. If managers don't understand it, the frontline will become confused.

Not Just Business Efficiency: The Quality of "Decision Making" Changes

Using AI doesn't just reduce time spent on document creation. For example, having AI analyze market research data might reveal trends humans would overlook. A manager's role is "decision-making." With AI presenting data and options as evidence,decision-making not relying solely on intuition or experiencebecomes possible. The three abilities mentioned in reference articles—"ability to formulate questions," "ability to evaluate," and "ability to make decisions"—are particularly important in the AI era.

Boosting Productivity Across the Entire Team

If subordinates cannot master AI, managers end up taking over those tasks. Conversely, if every team member can use AI as their "subordinate," overtime decreases, and time can be allocated to creative work. Even in Insource training cases, the concept of"making an AI agent your own dedicated subordinate"is spreading. Managers become "supervisors" deciding which AI tasks to delegate to whom. For future business professionals, mastering Generative AI to improve work speed and quality will become a prerequisite.

By Department! Specific Use Cases and Before/After

Instead of abstract talk, let's see how actual work changes. Having concrete images for each department is the key to successful implementation.

Sales Department: Improving Quality and Speed of Customer Response

Before:30 minutes to create meeting minutes after a negotiation. Struggling with email wording. Takes half a day to create proposals for each customer.

After:If voice data is passed to AI, meeting minutes are complete in 1 minute. Greeting messages tailored to the customer's industry are generated instantly. You can focus on building relationships with customers during the saved time. Since AI creates draft proposals, humans only need final checks and adjustments.

Marketing Department: Explosive Speed in Content Creation

Before:Takes 1 hour in meetings to brainstorm ideas for blog posts and SNS posts. Stuck due to struggles with copywriting.

After:If instructed "Give me 5 ideas for young people," suggestions appear instantly. Humans just select and modify them. Campaign turnover rates rise dramatically. It becomes possible to engage in a wide range of fields even with one person, making innovation easier to achieve.

Administrative Department: Automation of Routine Tasks

Before:Takes half a day to create monthly routine reports. Takes time to search internal regulations.

After:If data is passed to an AI agent, reports are created in the prescribed format. Alerts are issued for outliers, so only confirmation work is needed. If you ask the internal chatbot about regulations, answers are obtained immediately.

Risks and Countermeasures You Should Know

It's not all benefits. It is important to use it with the right knowledge. Avoiding use out of fear of risks is problematic, but using it without defense is dangerous.

Hallucination (Plausible Lies)

Generative AI sometimes tells lies that sound plausible when asked about things it doesn't know. This is called hallucination. In other words, it is a state of"confidently stating incorrect information". The countermeasure is simple. Important numbers and facts must always be verified (fact-checked) by humans. AI is merely a "draft creator," and the "ultimate responsible party" is human. Clarifying this boundary is important.

Information Security

Do not input confidential information as is. There is a risk that external secret data entered into public AI services will be used as learning data. As countermeasures,using enterprise plansandestablishing internal regulationsare essential. Training like Insource also supports creating such risk management rules. First, let's start by creating rules on "what can be entered."

The First Step of Implementation: Where to Start

Sudden company-wide implementation is dangerous. Small start is the golden rule. As mentioned in reference articles, choosing opportunities to learn gradually is important.

Step 1: Start with Personal Use

First, employees who are interested try free tools at a personal level. Start with low-risk tasks like email proofreading or idea generation. Programs that ensure mastery of basics through hands-on experience, such as Generative AI literacy training that improves through touching, are effective.

Step 2: Share Success Stories

Share success stories like "This reduced time by 1 hour" in internal chats. Spreading horizontally reduces resistance. It is important to cultivate practical skills to understand characteristics and risks with a Generative AI utilization plan and draw out results with appropriate delegation.

Step 3: Formal Training and Rule Establishment

Once utilization has progressed somewhat, conduct formal training and establish security rules. Choose programs that allow learning gradually from basics to practice, such as "Generative AI Literacy Training" as mentioned in reference articles. Plans that enhance not only Generative AI skills but also business skills together are recommended.

Frequently Asked Questions Q&A

Resolve doubts often held before implementation. Here we answer 5 particularly common questions.

Q. Which AI Tool Should I Use?

A. It depends on the purpose. For text creation, ChatGPT or Gemini are recommended; for Microsoft environments, Copilot is recommended. It is important to focus on one first. Try the free version first, then consider transitioning to an enterprise plan.

Q. Worried Employees Will Lose Jobs to AI?

A. Simple tasks decrease, but new jobs increase. The value of talent who can master AI rises. Rather than being taken away, view it as a change in role. If you leverage Generative AI, it is possible to transform business with just one person.

Q. Are Study Sessions Necessary?

A. Yes. Self-study leads to bias. Sharing correct knowledge through external training like reference articles or internal study sessions is the shortcut. It is best to choose things where you can select schedules that are easy to attend, such as training held daily.

Q. How Much Does It Cost?

A. There are many free tools, but paid plans are required for corporate use. The standard is around several thousand yen per person per month. However, considering the time reduction effect from business efficiency improvement, sufficient return on investment can be expected.

Q. Can Older Employees Use It?

A. Yes. Since Generative AI can be instructed in Japanese, programming knowledge is unnecessary. Courses like Basic AI Agent Training for Veterans, where you automate work with your own dedicated Generative AI, allow learning suited to levels.

So, What to Do Today?

No difficult preparation is needed. First, register for a free AI tool and try instructing"Write a draft of today's email". That feeling is the beginning of everything. There are many things you won't know until you touch it. Let's start small and accumulate success experiences.

Glossary

• Generative AI:Artificial intelligence that newly creates text, images, etc. Capable of handling questions without correct answers.
• LLM (Large Language Model):The brain part of Generative AI. Learns massive amounts of text data and handles language processing.
• Prompt:Instruction text to AI. Command. Accuracy increases the more specific the instruction.
• Hallucination:When AI generates content different from facts. Not lying, but requires caution.
• AI Agent:AI that autonomously executes instructed tasks. Can be used like your own dedicated subordinate.
• Machine Learning:A method to find trends and rules from massive data and utilize them for classification and prediction. Core technology of traditional AI.
• Deep Learning:A type of machine learning. Capable of complex processing. Used in image recognition, etc.
• Literacy:Ability to read and utilize information. AI literacy is the power to use AI correctly.
• DX:Digital Transformation. Transforming business and organizations with digital technology.
• Assessment:Evaluating current skills or situation. Utilization level can be measured with Generative AI Assessment.