Stop Asking “Why Don’t We Build Our Own AI ?” — Here’s the Real Answer

Why Indonesia Still Relies on Overseas AI Models — And Why That’s Not a Problem

The Real Reason Behind Indonesia’s AI Dependency

The question comes up often : “Why are we still using AI from overseas, especially for LLMs and automation engines, instead of fully local Indonesian AI ?”

It’s a valid question — and the answer reveals where Indonesia truly stands in the global AI race, and where our future advantage actually lies

At Futurescale, we work directly with enterprise clients, government stakeholders, and international partners across Southeast Asia and half of the world

From this vantage point, the picture is very clear :

Indonesia is not behind. Indonesia is in the correct strategic phase

Here’s why

1. Local AI Infrastructure Is Still Developing

Training a world-class LLM isn’t just about intelligence — it’s about infrastructure

To build an LLM at GPT-4 or Claude-level, you need :

• Massive GPU clusters (thousands of H100s)

• Billions of curated datasets

• Highly specialized ML research teams

• Continuous fine-tuning, safety alignment, and deployment pipelines

Indonesia currently does not yet have :

• A national-scale compute ecosystem

• Local cloud providers with sufficient GPU density

• Research institutions specializing in trillion-parameter model training

Without this foundation, building a top-tier model locally would be extremely expensive with slow return on investment

2. Global AI Labs Have a Multi-Billion Dollar Head Start

The world’s leading LLMs are backed by :

• USD 10–20 billion in R&D

• Over a decade of experimentation

• Thousands of AI scientists and safety engineers

• Mature, proven infrastructures that run at global scale

Competing with that overnight is not practical — nor necessary

Instead, Indonesia is smartly leveraging these global engines while focusing on what generates real business impact

3. Enterprise-Grade Requirements Are Extremely High

Large enterprises demand :

• 99.9% uptime

• ISO, SOC2, GDPR-level security

• Multilingual capabilities

• Reliable performance under millions of calls per day

• Fully tested auditability and compliance

• 
  

Overseas LLMs already meet these standards

Most local providers are still focused on application layer innovation, not foundational model reliability — and that’s where Indonesian AI can create the most immediate value

4. Indonesia’s Strength Is Practical Implementation, Not Building Mega Models

Across Southeast Asia, Indonesia leads in:

• Digital adoption speed

• Market size

• AI business use-case innovation

• Industry-specific automation

• Conversational AI deployment

• Voice AI and virtual human technology

Building a trillion-token LLM is expensive and doesn’t guarantee impact.But building AI agents, omnichannel automation, and enterprise workflows on top of global LLMs produces measurable results — fast

That’s where Indonesian companies excel

5. We’re in the “Build on Top” Phase — The Same Path Every Major Tech Nation Took

This is the same trajectory followed by :

• India (Infosys, TCS, Wipro)

• Singapore

• Early-stage China before Baidu and Alibaba built their own stacks

Phase 1: Use global LLMs →Phase 2: Localize models and flows →Phase 3: Build national AI capability

Indonesia is currently somewhere between Phase 1 and Phase 2 — and progressing fast

The Shift Is Already Beginning

Indonesia is now accelerating in :

• Local dataset development

• Local AI governance

• National compute initiatives

• Industry-specific fine-tuned models

• AI automation ecosystems for business

• Voice AI and virtual human platforms

• Agent orchestration frameworks

This is exactly where Futurescale positions itself: not as a model builder, but as an AI transformation enabler

The real value isn’t in owning the model — it’s in creating the ecosystem

So Why Do We Still Use Overseas LLMs ?

Because they are decades ahead in raw capability, and it allows Indonesia to focus on the highest-value layer : applying AI to real businesses, real industries, and real economic impact

Indonesia doesn’t need to recreate GPT-4 to win. Indonesia needs to deploy AI at scale, solve real problems, and build the ecosystem around it

That’s where the future is. That’s where Indonesia wins. And that’s exactly where Futurescale operates