Short answer
An AI project has three costs: people to assess and build, usage fees for the AI model, and support after go-live. People are the largest, priced as person-days times a day rate; the Thai government benchmark for IT staff with 7 to 10 years of experience is roughly THB 6,048 to 7,573 per person-day, under the Public Debt Management Office's consultant-fee criteria (Ministry of Finance, March 2026 edition). Model fees scale with volume, so measure them on a pilot before budgeting a year. The lowest-risk route is an assessment of real work, then one measurable pilot, before any full investment.
Where the Money Goes in an AI Project
Most of the money pays for the people who make AI work on your processes: watching the work, connecting to company data, testing, and setting data rules. Model fees, which worry people most, are usually smaller, but they are the only cost that grows with volume every month.
When you read a quote, separate the three. If a vendor gives one number, ask for the person-days per phase and a monthly model-fee estimate at your volume.
| Cost | How it is priced | Reference point |
|---|---|---|
| People: assessment, build, training | Person-days × day rate | Thai government benchmark of about THB 6,048 (7 years) to 7,573 (10 years) per person-day, PDMO March 2026 |
| AI model usage | Per token sent and received | Varies several-fold between large and small models; see per-million-token prices in the model guide below |
| Support after go-live | Monthly, or a monthly block of hours | No public benchmark; scope it in the contract (fixes, model-version updates, periodic output checks) |
AI models and effort levels: how to choose without overpaying
Using the Government Benchmark to Read an AI Quote
The PDMO criteria set a base salary for IT staff with a bachelor's degree of THB 50,400 a month at 7 years and THB 63,110 at 10 years. Multiply by the 2.640 cost factor and divide by 22 working days, and you get about THB 6,048 and 7,573 per person-day.
It is not the private market rate: freelancers usually quote lower, specialists higher. But it gives every quote the same yardstick. Divide each quote back to a day rate; if one is unusually cheap, ask why the days are fewer. Often testing on real data or the data rules were left out.
Train the Team, Build a System, or Buy a Tool?
If a person uses the AI and checks every output, training the team is usually enough. If the task repeats hundreds of times, needs company data, or needs an audit trail, it should be a system. Getting this split right early is where most of the saving is.
- Train: drafting email and documents, summarising reports, research, anything a person reads before using.
- Build: sorting incoming documents, answering customers from your own knowledge base, extracting invoice data into accounting; high-volume work tied to existing systems.
- Buy: work every company does the same way, such as meeting transcripts and notes.
- Not yet: work that must be right every time with no one checking, or that a process change would fix.
The Four Stages an AI Project Should Follow
Each stage should end in a go or stop decision, not roll on automatically, so the large spend happens only after real results.
- Assess real work: measure time and error rates, pick the one to three tasks that pay most. You keep the assessment even if you stop here.
- Pilot: one task working on real company data, small scope, one user group, success measures agreed up front.
- Measure: compare against the baseline, including model fees at real volume. If it misses, stop or adjust; do not scale.
- Scale: more users and tasks, long-term support, team training and periodic output checks, because model versions change.
What You Should Get Back
Deliverables should let you carry on without depending on the same vendor forever. At SyncEdge, engineers work with AI assistants and own the result they hand over: the code, the tests and the documentation.
- An assessment: which tasks use AI and which do not, with reasons and numbers.
- Data rules: what may go to outside services, what may not, and how identifying data is removed first, in line with PDPA.
- Source code, prompts and configuration owned by your company, with model-provider accounts in your company name.
- A test set of real examples with correct answers, re-run whenever the model or system changes.
- A pilot report with before-and-after figures and monthly model fees at real volume.
Consultant, Freelancer, or an Off-the-Shelf AI Tool
None is always right. It depends on how similar your task is to everyone else's and how much company data it touches. For generic work such as meeting transcripts, a packaged tool beats a custom build.
| Option | Fits | Watch for |
|---|---|---|
| Off-the-shelf AI tool | Generic tasks; start today, pay monthly or per use | Your data sits with the provider; read its data terms; limited fit to your process |
| Freelancer | Small, well-defined, self-contained jobs | Continuity after handover, model-version updates, documentation |
| Consultant or firm | Work that needs assessment, touches company systems and data, spans departments or needs years of support | Higher price; pay by phase with a point where you can stop |
An off-the-shelf example: Scripta, AI meeting notes and transcripts
Checklist Before Hiring an AI Consultant
- Does the quote separate people, model fees and support?
- Are person-days given per phase, so you can derive a day rate?
- Does the pilot have agreed success measures and a stop point?
- Are model-provider accounts in your company name?
- Do source code, prompts, configuration and the test set come to you?
- Is there a written rule on which personal data may go to outside services?
- After go-live, who checks outputs, and who pays when the model version changes?
Frequently asked questions
How much does AI consulting cost in Thailand?
It depends on person-days more than anything. The public benchmark is the PDMO rate of about THB 6,048 to 7,573 per person-day for experienced IT staff; private rates vary around it. Add usage-based model fees measured on a pilot, and monthly support if you need it.
Can we just use ChatGPT or a general AI tool ourselves?
Yes, and many tasks should start there. Hiring helps when the work needs company data, runs at high volume, connects to existing systems, or needs customer-data rules the whole organisation follows.
How do we estimate monthly model fees?
Multiply monthly volume by the text size per task and the model's price per token. The reliable number comes from a pilot, which measures tokens per task on real work. Prices differ several-fold between model tiers, so simple tasks should not run on the most expensive one.
Is sending customer data to an AI service a PDPA breach?
Not automatically, but it needs a lawful basis, and the model provider acts as a data processor that needs an agreement in place. Remove identifying data before sending where you can, choose services that do not train on your data, and make it a rule for the whole team.