“We rolled out generative AI, but is anyone on the floor actually using it?” This is a concern that is quietly spreading among many Japanese-affiliated companies based in Thailand. Names like ChatGPT and Claude are now known to everyone, and management issues the call to “put AI to work here as well.” Yet once the tool is licensed and handed to the field, only a small handful of people end up genuinely using it in their work. Subscriptions pile up while the investment fails to translate into results. Plenty of managers will recognize that situation.

Practical Generative AI Training (AI Adoption Training) from TOMAS TECH is a service designed precisely to break through that “adopted but unused” barrier. It is a three-hour intensive hands-on course for Japanese-affiliated companies operating in Thailand, with a single goal: enabling participants to start using the generative AI tool Claude in their real work from the very next day. Below we introduce a training program that stays with the field — a program only an IT integrator that knows factory and logistics operations could design.

What is Practical Generative AI Training?

Practical Generative AI Training is a hands-on training service for Japanese-affiliated companies operating in Thailand. It is structured as a three-hour intensive course with the goal of enabling participants to start using the generative AI tool Claude in their actual work from the next day. The curriculum covers everything from the basics of generative AI to operational efficiency, document creation and data analysis, giving participants a systematic grounding in skills they can genuinely apply on the job.

There is no shortage of “AI seminars” and “AI courses” out there. Most of them, however, tend to stay in lecture mode, discussing general topics such as how generative AI works, its history, and its impact on society. Background knowledge certainly matters, but even if the content makes sense while you are listening, you return to your desk the next day and fall back into the same manual routine. That way, neither the time nor the cost invested in the training is ever recovered. Practical Generative AI Training starts from a clean break with this kind of “knowledge-only” training.

What this course insists on above all is a single point: that participants can use what they learn in their own work from the next day. Every participant works with generative AI hands-on, using their own responsibilities as the subject matter — writing daily reports, summarizing documents, translating between Japanese and Thai, drafting emails, aggregating Excel data, and other concrete tasks they repeat every day. Within a short three hours, participants move beyond simply knowing to actually being able to do. That is the essence of Practical Generative AI Training.

Why we use Claude

The generative AI used in this course is Claude. Claude is strong at reading and summarizing long documents, producing natural text in multiple languages including Japanese and Thai, and organizing and analyzing tabular data — capabilities that align closely with routine office work. It delivers practical value on the tasks that arise daily at Japanese-affiliated companies in Thailand, such as reading forms, drafting reports, organizing meeting minutes and translating.

The quality of what generative AI produces also depends heavily on how you instruct it — in other words, on the prompt. The aim of this course is not to memorise the operation of one particular tool called Claude, but to build the mindset needed to convey a business problem to generative AI correctly and draw out the deliverable you want. Once that foundation is in place, the thinking carries over even when the tool is updated or when you move on to a different generative AI.

Do any of these challenges sound familiar?

We hear a wide range of comments every day from managers and executives at Japanese-affiliated companies doing business in Thailand. Among them, the following concerns about using generative AI come up especially often. If even one of them applies to you, there is a good chance this course can help.

Challenge 1: We want to adopt AI, but we do not know whether it will really work for our operations

You understand the potential of generative AI, but you cannot be confident that it will genuinely help with this specific task at your own company. There feels like a gap between the flashy examples you see in the news or in demos and your own unglamorous daily work. This is an extremely common concern. Generative AI is not an all-purpose magic wand, but there are many situations where it delivers reliably once you correctly identify where to apply it. The problem is that those application points are hard for the people doing the work to see. Because this course runs its exercises on your company’s actual operational data, participants come to understand first-hand where AI fits into their own work and how it helps.

Challenge 2: We have nobody in-house who can teach local staff how to use AI

A typical setup in Thailand is a handful of Japanese expatriates supported by a large number of Thai staff. To turn generative AI into genuine operational efficiency, the local staff who handle the day-to-day work need to become capable users themselves. Yet it is rare for a company to have someone in-house who can teach Thai staff the practical use of generative AI in Thai. Handing over Japanese-language materials does not get the message across fully, while external Thai-language seminars have only a weak connection to actual work. This course resolves that bottleneck — the absence of anyone to teach — directly, through instructors who work in both Japanese and Thai.

Challenge 3: Routine work such as forms, reports and translation is eating up our staff’s time

Compiling daily reports, producing weekly and monthly reports, translating documents for submission to the Japanese head office, handling email with business partners — each of these routine tasks may be small on its own, but together they steadily consume the time of your staff. Hours that ought to go to higher-value work such as improvement activities, customer response and shop-floor management disappear into repetitive clerical work. Repetitive routine work is exactly what generative AI excels at. Through hands-on exercises, this course teaches the concrete steps for handing that work over to AI.

TOMAS TECH developed this service as an IT integrator that knows factory and logistics operations, in order to address these challenges head-on. It is not armchair theory: it is a grounded training program built on what actually happens at Japanese-affiliated manufacturing and logistics sites in Thailand.

Service overview

Here is an item-by-item summary of Practical Generative AI Training. Many elements can be adjusted flexibly to suit your circumstances, so please start by reviewing the standard structure.

• Service name: Practical Generative AI Training (AI Adoption Training)
• Format: Three-hour intensive hands-on training (available on-site or online)
• Intended for: Japanese-affiliated companies in Thailand (primarily manufacturing and logistics; all industries supported)
• Tools used: Claude (document creation, translation, analysis, automation of routine work) / Notion (knowledge management)
• Languages of delivery: Japanese / Thai (selectable to suit the participants)
• Deliverables: A prompt collection and cheat sheet ready for use at work, plus a certificate of completion

About the format — on-site and online

The training can be delivered either on-site (at your premises) or online. For on-site delivery, the instructor visits your meeting room or similar space and runs the exercises in the same room as the participants. The advantages are that participants can call out immediately when they get stuck on a step, and that it is easy to share discoveries with one another. Online delivery, on the other hand, is convenient when staff are spread across multiple locations or when your site is in an industrial estate far from Bangkok. Whichever format you choose, the hands-on core of the course remains the same.

Tools used — Claude and Notion

The generative AI tool Claude is at the center of the course, but we also cover the use of the knowledge management tool Notion. By positioning Notion as the container for organizing and sharing the prompts and outputs created with generative AI along with in-house know-how, we bridge the gap between one person becoming able to use AI and the whole organization adopting it. The intention is to have participants think from the training stage onwards not only about personal skill development but about accumulating knowledge as a company asset.

Three features of this course

Among the many generative AI courses available, the following three points are what distinguish TOMAS TECH’s Practical Generative AI Training. It is because all three come together that the training does not simply end when the session does, but stays with the field.

Feature 1: Focused on real operational use

This course is not a lecture. We receive your actual data — forms, daily reports and the like — in advance and customize the exercise materials around it. Our basic approach is to keep instruction to a minimum and center the session on hands-on practice.

Using real data is the decisive difference from a typical AI seminar. Practising on generic sample data leaves you stuck the moment you return to your own work and wonder, “Wait — how does this apply to our forms?” By using your daily report format, your report template and the data you normally handle as the teaching material from the outset, the procedures learned in the exercises can be reproduced as they are in the next day’s work. In effect, we remove the “translation loss” that tends to arise between learning and real work at the material-preparation stage.

Naturally, we handle the actual data entrusted to us with the utmost care. It is used for no purpose other than the training, and we discuss and agree on confidential information management arrangements in advance, so you can entrust it to us with confidence.

Feature 2: Available in both Japanese and Thai

This course is available in both Japanese and Thai. The language of delivery can be selected to suit the participants, so the training can be run in Japanese for Japanese expatriates and in Thai for local staff.

Why does this matter? To make efficiency gains from generative AI truly stick, the local staff who handle the work every day need to become capable users themselves. But training delivered only in Japanese does not reach Thai staff fully. Training through an interpreter is also a poor fit for a hands-on course: subtle nuances drop out and the rhythm of questions and answers is lost.

It is precisely because the message reaches local staff in their native language that the training stays with the field. Learning directly in Thai, asking questions in Thai, and building your own prompts in Thai — whether or not participants have that experience makes an enormous difference to how well the training takes hold afterwards. This is where the understanding of both languages and both business cultures that TOMAS TECH has built up as an IT integrator rooted in Thailand comes into its own.

Feature 3: Usable from the next day

The overriding goal of this course is to get participants to a state where they can use AI from the next day. During the session, every participant completes a prompt for their own work and takes it away with them. From the day after the training, they can put that prompt to work in practice.

A “prompt for your own work” might be, for example, an instruction that automatically summarizes the daily report along a fixed set of items, or one that polishes a Japanese report into natural business Japanese for submission to head office. These are not generic templates but ready-to-use instructions tuned for that person and that task.

When the training ends, each participant is left with a concrete tool and the knowledge that “when I do this task tomorrow, I can use this.” Not abstract knowledge, but a real object that will help them tomorrow. That is what “usable from the next day” means. Because participants can try it out in real work while the energy of the session is still fresh, what they have learned is far more likely to settle into a habit.

Sample curriculum

How exactly are those three hours spent? Here we introduce the standard flow of the curriculum along with an indication of how the time is allocated. In practice the content is adjusted to your challenges and the level of the participants, so please treat this as one example. The course as a whole is designed to move through three stages: grasp the fundamentals, apply them to real work, and make them your own.

1. Generative AI fundamentals (approx. 30 minutes)

We begin with a minimal amount of instruction on what generative AI is, and on what Claude can and cannot do well. Difficult technical discussion is left out; we narrow the content to the essentials needed to understand AI as a tool for work. What generative AI is good at, what it is weak at, and how to handle information carefully when using it are all shared at this stage. We move through this quickly and proceed straight to the hands-on phase.

2. Hands-on: operational efficiency (approx. 40 minutes)

Participants experience the basics of handing routine daily work over to generative AI. Tasks that come up constantly in office work — drafting emails, preparing replies to inquiries, summarizing long documents, organizing meeting minutes — are actually processed with Claude. At this stage participants get a tangible sense that “a task that used to take 15 minutes can be cut down this far with a single instruction.”

3. Hands-on: document creation (approx. 30 minutes)

Participants learn how to use generative AI to speed up the creation of reports, proposals, internal notices and other documents. They experience an approach that reduces the burden of writing from scratch and divides the work with AI, from building the outline through to the final draft. Because document creation is covered in both Japanese and Thai, the skills are useful for materials aimed at head office and at the local organization alike.

4. Hands-on: data analysis (approx. 30 minutes)

Participants learn techniques for organizing and analyzing tabular data with generative AI. Aggregating figures, identifying trends and drawing insights out of data are all carried out using Claude. Participants experience how they can hold a dialogue with their data using nothing but instructions in Japanese or Thai, with no specializt analytics tools or programming knowledge required. If we can use data you normally handle — daily reports, performance figures and so on — as the subject matter, the exercise becomes even more practical.

5. Prompt workshop — completing a prompt for your own work (approx. 50 minutes)

This prompt workshop is the climax of the course. Drawing on the thinking acquired up to this point, each participant actually builds a prompt they can use in their own work every day. The instructor works alongside each participant on the specifics of their job, offering advice such as “phrasing the instruction this way will improve accuracy” or “adding this sentence will produce output in the format you want,” refining the prompt until it reaches a genuinely usable level. Having gone through this session, participants finish the course holding the “tool they can use from the next day” mentioned at the outset.

That is the standard flow, but the time allocation and the themes covered are rearranged flexibly according to your requirements. Requests such as “please focus on translation work” or “we would like more time on data analysis” are very welcome.

Mechanizms for making it stick in the field

There is no point in training that generates enthusiasm on the day and then fades away. Value is created only when people keep using what they learned in their real work from the next day onwards. Practical Generative AI Training builds in concrete mechanizms to embed the learning in the field.

Creating a prompt for your own work

As described above, participants complete a prompt dedicated to their own work during the session. This is not merely a practice output but a working tool that can be used as-is from the next day. Because there is no longer any need to think through “what should I ask for and how” from scratch each time, participants can start using generative AI after the training without hesitation. Removing that friction at the point of getting started is the first step towards making the practice stick.

Prompt collection and cheat sheet

As deliverables, we provide a prompt collection and a cheat sheet ready for use at work. The prompt collection contains the participant’s own prompt created during the training plus a set of examples that can be applied to similar tasks. The cheat sheet is a quick-reference sheet covering the basic patterns for using generative AI and the tips that make it work well. It gives participants something to return to when time has passed and they find themselves wondering “how did that technique go again,” supporting their ability to act even once the details have faded from memory.

Certificate of completion

Participants who complete the course are issued with a certificate of completion. Giving the achievement a tangible form raises the participant’s own motivation and also makes visible who within the company is capable of using generative AI. Clarifying who has acquired AI skills creates a point of contact for internal questions and becomes a starting point from which adoption spreads.

Post-training support

This course does not end when the session does. Rather than treating the training day as the finish line, we maintain a structure that continues to support adoption in the field after the course. Making use of generative AI is not something that spreads automatically once learned; it takes root gradually, through trial and error in real work.

Follow-up training (online)

Once people start actually using AI at work after the course, new questions and requests inevitably arise. In follow-up training (online), participants bring those real post-course issues to the table and we work through them. By answering the questions that only emerge once you have tried something in practice, we lift the level of usage another step. It is time set aside so that learning does not stop at learning, and so that we can get over the hurdles of practice together.

Annual support

For companies that want to keep advancing their use of generative AI, we offer annual support. This is a structure for accompanying you over the long haul — responding to questions that come up in daily work, discussing new ideas for applying AI, and so on. The world of generative AI changes quickly, with new features and new ways of working appearing one after another. We can stay with you long-term as the partner who keeps bringing that change into your operations.

Adoption support for company-wide rollout

From the stage where individuals can use AI to the stage where its use spreads across the whole organization: our adoption support service is what carries you through that transition. Moving from “only some people use it” to “it is standard practice across the company” requires work that is different from individual training — establishing internal rules, building a platform for sharing knowledge, designing additional training. TOMAS TECH supports lasting adoption in the field on an ongoing basis, up to and including an adoption support service for rolling AI out internally. Starting from the training as an entry point, we help you grow your use of generative AI into results at the organizational level.

Value specific to Japanese-affiliated companies in Thailand

Practical Generative AI Training is not a generic AI course. It is a service optimized for the particular environment of a Japanese-affiliated company operating in Thailand. It offers distinctive value that TOMAS TECH can provide precisely because we have been deeply involved with manufacturing and logistics operations in Thailand.

Local staff can take the leading role

In most cases it is local staff who actually keep operations running at Japanese-affiliated companies in Thailand. For efficiency gains from generative AI to succeed in any real sense, those local staff must become capable users in their own right. Because this course can be delivered in Thai, local staff can be developed not as people to be taught but as the leading players in adoption. Even when Japanese expatriates move on, the AI skills remain locally and accumulate as organizational capability.

Multilingual work itself becomes lighter with AI

Japanese with the head office in Japan, Thai for local operations, and English too depending on the business partner — Japanese-affiliated companies in Thailand work across several languages every day. Translation and producing documents in multiple languages place a heavy burden on the field. Multilingual work is exactly where generative AI excels. Because this course covers concrete ways to use AI to streamline translation and document creation across Japanese and Thai, it lightens the very burden that a multilingual environment imposes on Japanese-affiliated companies in Thailand.

Instructors who know manufacturing and logistics operations

TOMAS TECH is an IT integrator that knows factory and logistics operations. Through production management systems and shop-floor productivity solutions, we have engaged with manufacturing and logistics sites in Thailand day in and day out. That is why we understand in concrete terms what forms are used on the floor, what reporting work exists, and where manual waste is hiding. This grounding in real operations lets us make specific proposals — “this particular task at your company will become easier in this way” — rather than abstract claims about what AI can do. A perspective rooted in the field, which an ordinary IT training company does not have, is what underpins the value of this course.

How pricing works

The price of the training varies according to the number of participants and the delivery format (on-site or online). Whether it is an intensive session for a small group or a course covering a larger number of staff together changes both the optimal structure and the cost.

In addition, because this course customizes its exercise materials around your actual data, the advance preparation differs from company to company. For that reason, rather than presenting a single fixed price, we listen to your situation and requirements first and then provide an individual quotation. We welcome inquiries of any kind — “we would like to try it with a few people first,” “we want to introduce it in one department only,” “we would like to run it across multiple sites,” and so on.

For detailed pricing, please feel free to contact your sales representative. We will propose an adoption plan that works comfortably for your company.

Frequently asked questions (FAQ)

Q1. Can employees who have never used generative AI take the course?

Yes, absolutely. The course starts from the fundamentals of generative AI and is centred on hands-on practice, so even complete beginners build understanding step by step. No specializt knowledge or programming skills are required whatsoever. Anyone who can give instructions in Japanese or Thai can take part. In fact, for people who are about to start using AI, this is the ideal first step.

Q2. Can the course be taken by Thai staff only?

Yes. The course can be delivered in Thai, and we also run sessions for local staff only. Learning in one’s native language means the content gets across in depth, and take-up after the course is higher as a result. It is also possible to run a Japanese-language course for Japanese expatriates and a Thai-language course for local staff as separate sessions.

Q3. Can people really become able to use AI at work in three hours?

The course is designed with “usable from the next day” as its goal. By keeping instruction to a minimum and centring the session on hands-on practice, and by having every participant complete and take away a prompt for their own work, results that connect directly to real work can be achieved even in as little as three hours. Because we concentrate on mastering one thing participants can definitely use in their own job, rather than covering a broad sweep of material, a practical level is reachable in a short time.

Q4. Is there anything we need to prepare in advance?

To make the training more effective, it is ideal if you can provide actual operational data such as daily reports, forms and report formats. Customizing the exercise materials around these means the exercises translate directly into real work. We handle the data with the utmost care and use it for no purpose other than the training. If providing data is difficult, the course can still be delivered using generic material, so please get in touch and we will discuss it.

Q5. Can we get the same results online?

Yes. The essence of the course — hands-on practice, usable from the next day — is unchanged in the online format. Where staff are spread across multiple locations or your site is in a distant industrial estate, online delivery is in fact more convenient. The instructor checks each participant’s work via screen sharing as the session proceeds, so the hands-on experience is every bit as good as on-site. Please choose whichever format best suits your circumstances.

Q6. We are worried about whether we will be able to use it well after the training. Is there any support?

Please rest assured. This course does not end when the session does. We support lasting adoption in the field on an ongoing basis, through post-course follow-up training (online), annual support, and an adoption support service for company-wide rollout. We also respond continuously to the questions and issues that surface once you have actually started using AI, so you can go ahead with confidence even if you are still at the “not sure we can master it” stage.

Q7. What is the minimum number of participants?

We accept small groups. We propose the optimal structure for the number of participants and the delivery format, so we can accommodate both “we would like to try it with a few people first” and “we would like a whole department to take it together.” Let us know the numbers and your preferences and we will suggest a plan that suits your company.

Q8. Can companies outside manufacturing and logistics take the course?

Yes. While the course is centred on manufacturing and logistics, it supports all industries. Needs such as streamlining routine work, creating documents, translating and analyzing data exist regardless of sector, so companies in any industry can benefit. We customize the exercises to your operations, so please feel free to get in touch whatever your industry.

Summary / Contact us

Used correctly, generative AI is a powerful tool that reliably lightens the load on the field and redirects staff time towards more valuable work. But there is a wide gap between adopting it and mastering it. Crossing that gap in one go, in a three-hour intensive hands-on course — that is Practical Generative AI Training (AI Adoption Training).

Content focused on real operational use and centred on hands-on practice; delivery in both Japanese and Thai; and a goal designed around taking away a prompt you can use from the next day. On top of that, a structure that continues to support adoption in the field, from post-course follow-up through to adoption support for company-wide rollout. All of this is value that only an IT integrator who knows manufacturing and logistics operations in Thailand can provide.

“We want to adopt AI, but we do not know whether it will really work in the field.” “We have nobody who can teach our local staff.” “Routine work is eating up our staff’s time.” If even one of these rings true, please get in touch. Inquiries at the stage of “could AI do anything about this task?” are very welcome. We will listen carefully to your challenges and propose the best approach for your company.

Please send your inquiry via this form: https://tomastc.com/en/contact/