What makes developing countries, especially Indonesia, always so far behind in terms of technology, especially AI applications?

Developing countries like Indonesia often lag in AI adoption due to a mix of structural, economic, and educational challenges.

Here are the key factors:

1. Limited Infrastructure & Investment

• AI requires strong digital infrastructure, such as reliable internet, cloud computing, and high-performance hardware, which are not yet fully developed across Indonesia.

• Investment in AI startups and research is lower compared to countries like the U.S. or China, limiting innovation.

  
  

2. Talent & Education Gap

• There is a shortage of skilled AI professionals. Universities still focus on traditional IT rather than cutting-edge AI applications.

• Brain drain: Talented engineers often move to developed countries for better opportunities.

  
  

3. Low Business & Government Adoption

• Many businesses still rely on traditional operations, and digital transformation is slow.

• Government policies on AI adoption and R&D funding are still developing, making it hard for startups to thrive.

  
  

4. Data & AI Regulation Challenges

• AI relies on high-quality data, but data collection, privacy laws, and standardization remain weak.

• Indonesia has strict data localization laws, which can limit access to global AI infrastructure.

  
  

5. Cost & ROI Concerns

• AI development and implementation are expensive, and many businesses don’t see immediate ROI, making them hesitant to invest.

• Local businesses prioritize automation for efficiency rather than advanced AI-driven innovation.

  
  

6. Cultural & Market Dynamics

• Many companies still prefer human interaction over automation.

• AI adoption is often seen as a threat to jobs rather than an opportunity for productivity.

  
  

Opportunities for Growth

Despite these challenges, Indonesia has huge potential due to its large population, rising digital economy, and government initiatives like "Making Indonesia 4.0."

The key is fostering local AI talent, attracting investments, and encouraging AI adoption in key sectors like finance, healthcare, and e-commerce.