Introduction
With the rapid evolution of generative AI, average-quality production and surface-level expression have quickly become commoditized.
The true source of value now lies in the ability to frame meaningful questions and to interpret cultural context.
Based in Thailand, we work with corporations, universities, and government organizations across a range of fields — from web production and brand development to exhibition design and business support.
What we observe in practice is clear: the ability to ask questions and design context — things AI cannot replace — is regaining central importance in creativity.
This article shares lessons from our Thailand-based projects, highlighting why human “resolution” matters more than ever.
How Generative AI Is Reshaping Creative Work
Table 1｜Shifts in Creative Work through Generative AI
| Area | Before | After (with AI) |
|---|---|---|
| Design implementation | Manual, experience-dependent | Automated, faster, reproducible |
| Problem discovery / Question framing | Driven by intuition and sensibility | Greater demand on human thinking |
| Value judgment in expression | Dependent on creator’s taste | Evaluated through user context |
Dividing Roles Between AI and Humans
Table 2｜Roles in AI-Enhanced Workflows
| Process | Responsible | Notes |
|---|---|---|
| Initial idea generation | Human + AI | AI provides a neutral draft |
| Concept design | Human | Reframed with cultural/ contextual insight |
| Implementation (design, copy) | AI or creative team | Speed and repeatability prioritized |
| Final editing & adjustments | Human | Fine-tuned for context and intent |
Table 3｜Where Human Involvement Is Critical (Average from Practice)
| Process | Human Importance |
|---|---|
| Idea generation | 70% |
| Context design | 90% |
| Design implementation | 40% |
| Final editing | 85% |
Practical Uses of Generative AI
For example, in cross-border e-commerce brand development in ASEAN, cultural and linguistic differences often make early alignment difficult.
By using AI outputs as a shared baseline, each local team was able to re-edit the content in line with their own context, leading to smoother discussions.
In multicultural projects, AI works best as a neutral, unbiased material provider, while humans focus on reconstructing meaning.
The Human Value of Designing Context
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Japanese manufacturer’s ASEAN expansion: AI drafts refined by local staff, aligned with customer reality.
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Seminars in Thailand: AI-generated drafts restructured by participants, deepening questions through contextual reinterpretation.
Our contextual editing workflow:
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Present AI outputs as initial materials.
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Participants reframe based on their own perspectives (cultural and social context).
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Share and critique (training in translation and reframing).
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Finalize for the audience (design intent and user experience).
AI as a Tool to “Return to Zero”
AI-generated outputs are often reconstructions of existing expressions.
Therefore, the future of creativity depends on what questions we ask, and where we find meaning.
AI should be treated as a tool for optimization, while humans must focus on high-resolution decision-making.
Five Practical Steps You Can Use Right Now
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Use AI drafts as a shared foundation.
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Make explicit whose context defines the evaluation.
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Focus human effort on question design and meaning editing.
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In multicultural projects, standardize the cycle: re-edit → critique.
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In the final stage, review for alignment with purpose and experience.
This column is based on the interplay of research and practice at our Thailand base, offering a field-level perspective on how generative AI can be applied in creative work.