AI Product Development & Innovation in Thailand

All training modules incorporate PDPA compliance frameworks, covering consent management, data minimisation, and breach notification obligations. With THB 21.5 million in fines already levied in 2025 — including against data processors — we ensure your team understands both controller and processor obligations when deploying AI systems that handle personal data.

Thai businesses can access multiple incentives: DEPA grants up to THB 200,000 for digital transformation, a 200% tax deduction on qualifying digital expenses for SMEs (effective June 2025 through December 2027), BOI corporate income tax exemptions up to 13 years for AI investments, and the new Qualified Refundable Tax Credit at 30-50% for advanced skills development.

We deliver using a hybrid English-Thai approach with high-energy, interactive workshops that match Thai learner preferences. Content respects hierarchical management structures and the kreng jai norm of maintaining group harmony, using consensus-building exercises rather than confrontational case studies.

The 2025 Draft Principles of Thailand's AI Law introduces risk-based classifications including 'Prohibited-risk' and 'High-risk' AI categories. Our training builds governance frameworks that anticipate these requirements, so your organisation is prepared when the law is formalized in 2026.

Traditional product analytics teaches you to use tools (Amplitude, Mixpanel) to track events and build dashboards. This AI-focused training teaches you to use AI to predict user behavior, automate insight discovery, and build intelligent product features. You'll learn behavioral segmentation (AI clustering), impact forecasting (AI prediction), and feedback synthesis (AI NLP) — capabilities beyond traditional event tracking.

Minimum: (1) Some form of event tracking (even basic GA4 or Mixpanel free tier), (2) User feedback channels (support tickets, NPS surveys, or reviews). Ideal: Product analytics platform (Amplitude, Heap, Mixpanel) with historical data. During Discovery, we'll assess your current setup and recommend quick-win improvements to maximize training value. Even basic event data enables powerful AI insights.

Yes! Module 4 is designed for non-AI-native products adding intelligent capabilities. You don't need a team of ML engineers. We'll show you how to: (1) Use pre-built AI APIs (OpenAI, Google AI) to add smart features quickly, (2) Build simple recommendation engines using collaborative filtering, (3) Partner with AI vendors for specialized capabilities. Goal: embed AI in your product to improve UX, not become an AI research company.

Critical concern addressed throughout the training. We teach AI feature validation: (1) Use AI analytics to identify high-frequency pain points first, (2) Prototype AI features using Wizard of Oz testing (manual behind the scenes), (3) Launch AI features to small user segments with opt-in/opt-out, (4) Measure adoption and satisfaction before full rollout. AI should solve real user problems, not be AI for AI's sake.

Highly relevant for both. B2B SaaS examples in the training: AI usage insights identifying expansion opportunities, AI onboarding optimization reducing time-to-value, AI feature adoption tracking for CSM prioritization, AI feedback analysis from customer calls and support tickets. Consumer product examples: AI personalization, recommendation engines, smart notifications. We customize content to your business model during Content Customisation.