Top 10 AI Prompts and Use Cases and in the Government Industry in Thailand

Thailand's government is at a policy inflection point where practical AI prompts and grounded use cases move from theory to urgent practice: the consolidated Draft Principles being circulated would create a tiered, EU‑style risk regime that lets sectoral regulators list Prohibited‑risk and High‑risk AI (including bans on subliminal manipulation, social scoring and real‑time biometric ID in public spaces), while NAIS and a new national data strategy back the push for sandboxes and safer innovation; that mix makes it critical for civil servants to map inventories, classify use cases by risk, and craft prompts that keep humans in‑control and explainable to citizens who, under the drafts, must receive clear notice, an explanation, and a chance to contest AI decisions.

For hands‑on skills that translate to everyday public service work, consider practical training like the AI Essentials for Work bootcamp to learn prompt writing, risk-aware workflows, and prompt-based automation that respects Thailand's evolving rules and citizens' rights (Thailand draft AI law analysis, AI Essentials for Work bootcamp syllabus).

“in‑control”

Program	Length	Early bird cost	Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work bootcamp syllabus

Selection favoured prompts and use‑cases that map cleanly to Thailand's emerging governance landscape - a risk‑based filter echoes the Draft Principles' two headline categories (Prohibited‑risk and High‑risk) and the push to classify public‑sector workflows before deployment (Thailand draft AI law and EU-style risk framework analysis); it also prioritised ethical alignment with national strategies and sectoral guidance to ensure PDPA compliance and explainability (Thailand AI ethics guidance and PDPA regulatory overview).

Practicality was weighted heavily: candidates had to offer clear human‑in‑the‑loop controls, fit for regulatory sandboxes, and demonstrable benefits in priority domains such as health, agriculture and justice.

Social acceptance and trust were a second lens, informed by public sentiment about surveillance and fairness - recall the controversial use of AI police robots during Songkran - which steered choices toward transparent, contestable designs and upskilling pathways (Thailand AI public sentiment survey on surveillance and fairness).

Prompts were then written to mirror real workflows, include guardrails for data governance, and produce outputs that a civil servant can audit, contest, and explain to citizens.

The Digital Government Development Agency (DGA) is steering Thailand's move from legacy systems to an AI-ready, cloud-first public sector, and its newly published Cloud and Data Classification Guidelines force a practical reckoning: agencies must classify records as “official,” “protected,” or “highly protected,” keep sensitive data in domestic or sovereign clouds, and bake in encryption, access controls and PDPA compliance before any AI-driven citizen service goes live (Thailand DGA Cloud and Data Classification Guidelines (Hogan Lovells)).

That same governance backbone makes AI features - smarter search, personalised service nudges, predictive case routing - safer to pilot inside Thang Rath, the government superapp that already surged to 20 million downloads in 48 hours during a benefits rollout, showing how scale and fragility collide in real time (Thang Rath superapp growth and Thailand DGA cloud strategy (GovInsider)).

For civil servants automating e‑government workflows, the takeaway is simple: cloud-enabled AI can cut cost and boost access, but only if data classification, localization rules and PDPA-aligned guardrails are embedded into prompts, models and procurement from day one (Public-cloud expansion for scalable AI in Thailand government).

“Cooperation between agencies has become much smoother. This is because agencies now recognise the benefits of organisational development through the adoption of technology.”

Thailand's mobile champions AIS and True are already turning 5G into practical hospital tools that cut waiting times, free up beds and let specialists reach patients without long travel: Siriraj's 5G smart hospital - launched as the country's and ASEAN's first large 5G medical hub - has incubated 5G, cloud and AI apps from contactless delivery robots to AI‑assisted CT imaging, while TrueBusiness's collaboration with Intel is packaging seven 5G‑powered AI healthcare solutions (from telemedicine and pathology‑as‑a‑service to a Patient Management as a Service that builds a “digital patient twin” using ceiling sensors for heart rate, temperature and sleep data) to speed diagnosis and streamline hospital resource allocation across wards and ambulances (see the Siriraj 5G smart hospital project and TrueBusiness 5G‑powered AI healthcare solutions).

The concrete payoff is simple and memorable: real‑time edge AI and 5G let a clinician know a critical patient's status before the ambulance arrives, so triage and theatre allocation happen faster and with less guesswork.

“TrueBusiness is accelerating the development of innovative services while integrating AI to enhance organizational capabilities.”

Ricult stitches satellite intelligence, simple farmer UX and finance to turn smallholder uncertainty into actionable decisions for Thai fields: the free Ricult farmer app bundles daily–monthly weather forecasts, satellite RGB and NDVI imagery updated every five days, agronomic chat with experts and farm record‑keeping, while RicultX and Crop Scan give banks and mills field‑level visibility (Crop Scan reports 90%+ accuracy) so lenders can offer affordable credit and buyers can trace supply; the result is a pragmatic, scalable tool that helps farmers time sowing and harvests, spot drought early, and capture better market prices - outcomes credited with double‑digit income gains in published profiles of Ricult users and highlighted by the CEO's role advising Thailand's AI strategy (see the Ricult farmer app and Ricult profile in The ASEAN for details).

Metric	Value
Farmers using platform (reported)	587,833 users
Area analysed	5,000,000 acres
Satellite imagery cadence	Every 5 days (RGB & NDVI)
Crop Scan accuracy	90%+
Reported farmer profitability uplift	20–30% (published case estimates)

“Ricult has helped me predict weather more accurately. At this age, counting months for farming activities does not work anymore. I can use Ricult app to see weather data more quickly and anytime” - Jumrus Inpuek, Lopburi, Thailand

Khon Kaen's smart‑city push turns emergency response into a visible, measurable public good: university campuses now use twelve “smart emergency call points” that flash, stream real‑time audio and photo feeds to dispatchers and - crucially - shaved average EMS arrival from 9.14 minutes down to 6.01 minutes versus the traditional 1669 phone line, demonstrating how fixed IoT hotspots can speed help when seconds matter (Khon Kaen smart emergency call point study (Prehospital and Disaster Medicine)); at city scale, Khon Kaen couples that campus tech with smart ambulances, predictive “smart ICU” monitoring and a plan for a 24‑rai medical hub that lets clinicians monitor vitals en route and coordinate 26 ambulances in a single control room (Khon Kaen Smart City masterplan (Nation Thailand)).

The result is practical resilience: flashing call points, teleconference‑equipped ambulances and blockchain‑ready health records that aim to turn chaotic incidents into coordinated care - so a rider in crisis can be seen, triaged and routed before bystanders can finish dialing (Khon Kaen smart health solutions (Healthcare Weekly)).

Metric	Value
Smart emergency call points (KKU campus)	12 installed since 2017
Average EMS response (smart point)	6.01 minutes
Average EMS response (1669 phone)	9.14 minutes
Ambulances coordinated by Command Centre	26 ambulances
Annual emergency cases (Khon Kaen Hospital)	~120,000

“The alerts will be triggered from smart devices that the patient owns, and the smart ambulance service will be dispatched.”

For Thailand's policy teams, the Asian Development Bank's work shows that AI plus satellite imagery can turn sparse survey snapshots into actionably granular poverty maps - capable of flagging tiny, high‑need pockets (the Indonesia pilot used 2.4 km × 2.4 km grids) so local programmes and cash transfers reach the neighbourhoods that standard statistics miss; ADB's 2025 summary explains how daytime Sentinel‑2 and VIIRS nightlights fed into convolutional neural nets and tree‑based models to surface infrastructure, vegetation and urban patterns as proxies for wealth (ADB: How AI and Satellites are Transforming Poverty Analysis), while an earlier ADB study demonstrated viable ConvNet approaches for the Philippines and Thailand and highlighted the need for local calibration and complementary data (mobile records, surveys) to avoid transfer errors (ADB: Using Machine Learning on Satellite Images to Map Poverty).

The operational takeaway for civil servants: invest in calibrated models, combine remote sensing with local ground truth, and use high‑resolution maps to target interventions rather than rely on province‑level averages.

Country	Year	ConvNet Accuracy
Thailand	2013	0.85785
Thailand	2015	0.85219
Philippines	2012	0.94150
Philippines	2015	0.93500

Thailand's highest courts are a natural fit for careful automation: peer-reviewed work from Thai universities shows that NLP and deep learning can “read” judgments, identify decision components and even predict outcomes by comparing case facts to legal provisions - examples include a bi‑directional GRU with attention that imitates legal interpretation and Mahidol studies on extracting decision components from Supreme Court text (GRU prediction model for Thai Supreme Court decisions, Utilising AI/NLP to predict Supreme Court decisions); those approaches can surface the few sentences that really drove a ruling, turning long case files into pinpointed review items for judges and clerks.

Any pilot must also respect Thailand's emerging compliance regime - the draft AI law explicitly empowers regulators to issue administrative orders to AI providers - so explainability, data provenance and PDPA alignment are non‑negotiable (draft AI law empowering regulators).

Practically, digital case management tools promise real efficiency gains - but only with staff training to manage exceptions and bias, and with transparent outputs that a judge can contest and audit before a decision is final.

Pattani's experience and the NBTC's August 18, 2025 liveness‑detection mandate make Thailand's SIM‑registration shift a high‑stakes test of security versus rights: regulators now require real‑time facial liveness checks for all new prepaid and postpaid registrations and for SIM swaps, with operators expected to support verification via apps, service centres and authorised dealers while complying with the Personal Data Protection Act (PDPA) (NBTC liveness-detection mandate for SIM registration in Thailand).

That same toolbox - face scans, “two‑shot” ID systems and mass re‑registration - has already been used in Pattani's Deep South, where mandatory biometric programs, temporary service suspensions for unregistered numbers and a history of intrusive practices (the GT200 scandal is a haunting reference point) have fuelled deep public distrust and ethnic profiling concerns (Patani two‑shot identification and surveillance in Thailand's Deep South).

Legal and ethical analyses warn the obvious trade‑offs: fraud reduction and traceability versus irreversible privacy harms, exclusion of vulnerable groups, and function‑creep unless strong PDPA‑aligned safeguards, independent oversight, clear consent processes and secure, purpose‑limited storage are enforced (Legal and ethical analysis of biometric SIM registration).

The practical takeaway for civil servants: technology can close fraud loopholes, but without transparent governance and redress it risks turning public‑safety tools into a panoptic liability.

“The NBTC prioritises consumer protection and aims to enhance trust in telecommunications services.”

The Thailand AI Research Institute - built from a depa–VISAI partnership and often framed as “AI for Everyone” - is shaping a practical talent pipeline by marrying ready‑made models, hands‑on training and cloud delivery so SMEs and public agencies can adopt AI without deep in‑house expertise; VISAI's AI Cloud Platform offers up to nine off‑the‑shelf models and paid AI training while DEPA-backed programs and industry alliances (AIT, Microsoft, SCB 10X) supply curricula, certificates and regional upskilling to narrow a stark gap: roughly 100,000 AI/IT roles are needed each year against an estimated supply of 25,000.

This blended approach - research institute R&D, accessible cloud models, and public‑private reskilling - turns abstract workforce plans into deployable tools, letting departments pilot accountable automation with local support and lower onboarding cost (Thailand AI Research Institute (VISAI + DEPA) partnership announcement, VISAI AI Cloud Platform overview and paid AI training, Digital Manpower Development alliance: AIT, Microsoft, SCB 10X and DEPA AI talent initiative).

Metric	Value
AI/IT workers needed (per year)	~100,000
Available AI/IT supply (per year)	~25,000
VISAI cloud models (initial)	Up to 9 models

“Many people have taken advantage of this technology. Not only big business organisations, but all entrepreneurs can tap AI to develop their knowledge and take their business forward.”

NECTEC (part of NSTDA) is the natural backbone for government efforts to digitize records, govern datasets and meet PDPA obligations because its labs combine Thai‑language AI, national data infrastructure and certification capacity: the Data Science and Analytics Research Group builds national data infrastructure for big‑data analytics, the Artificial Intelligence Research Group focuses on language, speech and image processing useful for document digitization, the NSTDA Supercomputer Center (ThaiSC) supplies the heavy compute, and the Digital Technology Evaluation and Certification Institute (DTEC) provides a route to product-level assurance - together they let agencies move from brittle paper workflows to audited, privacy‑aware pipelines while keeping PDPA compliance and explainability front‑of‑mind (see NECTEC research units and target industries and the Pathumma LLM announcement on Thailand‑centric language, vision and audio models).

The practical win is straightforward: when Thai‑tuned models, certified tools and national HPC are combined with clear data‑classification rules, civil servants can automate triage, redact PII, and generate searchable summaries that are auditable and contestable - transforming compliance from a blocker into an operational capability.

NECTEC Unit	Relevant role for government AI
Data Science and Analytics Research Group (DSARG)	National data infrastructure & analytics
Artificial Intelligence Research Group (AINRG)	Thai language, speech & image processing for digitization
NSTDA Supercomputer Center (ThaiSC)	High‑performance compute for model training
Digital Technology Evaluation and Certification Institute (DTEC)	Product evaluation & certification for compliance
Assistive Technology & Medical Devices (A‑MED)	Health data integration and accessible tech

For the Port Authority and Ministry of Transport, pragmatic AI means pairing IIoT sensors with asset‑centric platforms so bridges, ports and tunnels shift from calendar‑based checks to condition‑aware upkeep: industrial‑grade systems like NOV Max Maintenance asset tracking and predictive maintenance platform give real‑time asset visibility, QR/NFC/RFID tracking, auto‑triggered work orders from sensor thresholds, and mobile apps that let crews update jobs even offline; combined with the productivity gains of predictive maintenance described by Artesis predictive maintenance and asset management insights - early fault detection, fewer unplanned outages and smarter spare‑parts planning - this approach cuts downtime and lowers lifecycle costs.

Scale and data access are easier when agencies use cloud‑first rollouts to host analytics and integrations, so predictive alerts can feed central command rooms and mobile technicians alike (public‑cloud expansion for scalable AI in government).

The practical win: condition‑based monitoring that automatically schedules a maintenance task and arms the field team with the exact parts and checklist they need, turning surprise breakdowns into planned, auditable operations.

Practical next steps for Thai civil servants and beginners are straightforward: start small, govern early, and train quickly - run focused pilots inside PDPA‑compliant sandboxes, pair each use case with clear data‑classification and MLOps checks from the outset, and measure citizen‑facing gains (Pennsylvania's pilot, for example, reported up to eight hours saved per employee per week).

Use proven playbooks: adopt the GSA's AI Guide for Government to structure IPTs, IATs and central AI resources for procurement and lifecycle governance (GSA AI Guide for Government), mirror DHS's approach to safe pilots and AI corps staffing for technical review and threat‑testing (DHS fact sheet on AI pilots and AI corps staffing), and invest in human capital so teams can audit outputs, manage exceptions and avoid exclusionary outcomes.

For beginners, a pragmatic training path - like a 15‑week course that teaches prompt writing, prompt‑based automation and workplace use cases - turns policy into action and builds the practical skills needed to run accountable pilots (AI Essentials for Work syllabus - Nucamp); the real test is not theory but a tiny, well‑measured pilot that proves both value and explainability to citizens.

Program	Length	Early bird cost	Syllabus
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work syllabus - Nucamp

“You don't get good at using AI by reading about it - you get good at it by doing.”