AITF


A National Program

by Ministry of Communication and Digital Affair

"

The AI ​​Talent Factory is one of the flagship programs of the Ministry of Communication and Digital, which brings together digital talents in the AI ​​field to develop and implement AI in various fields.

Nezar Patria

Deputy Minister of Communication and Digital of the Republic of Indonesia

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About AITF

The Artificial Intelligence Talent Factory (AITF) is a national program for sustainable AI talent development from the Indonesian Ministry of Communication and Digital Affairs, through the Komdigi BPSDM Digital Talent Development Center. It aims to develop top AI talent through collaboration between the government, academia, and industry. The program focuses on real-life case studies that encourage participants to apply theory and develop AI-based solutions. The AITF serves as the government's primary strategy to strengthen AI sovereignty, develop AI innovation and ecosystems, and achieve a sovereign and dignified Indonesia in the global AI technology arena.

The AITF program is specifically designed for higher education institutions as strategic partners in building a strong and sustainable AI ecosystem within the academic environment. Through this collaboration, universities not only develop AI talent but also strengthen AI research and innovation capacity on campus. Universities interested in joining can register their institutions through the Artificial Intelligence and Data Science Collaboration Potential Mapping Survey form.

Tentang AITF

The Launch of the AITF Program: Komdigi x UB

Tentang AITF

BPSDM Komdigi dan JICA Officially Launch the “Next-Gen AI Talent Factory” Program Collaboration

Tentang AITF

Use Case Progress Presentations Become the Highlight of the AI Talent Factory Workshop

Tentang AITF

AITF 2026 Digital Talents Ready to Build a Sustainable AI Ecosystem in Indonesia

Tentang AITF

The Spirit of Collaboration Shapes the Development of AI Projects by AITF Participants

Tentang AITF

Project Analysis and Technical Learning Support the Development of AI Talent

Tentang AITF

AITF 2026 Becomes a Momentum to Strengthen a Globally Competitive National AI Ecosystem

Tentang AITF

Enhancing AI Competencies Drives the Emergence of Innovations from Indonesia’s Digital Talents

Tentang AITF

Collaboration and Discussion Become the Key to Developing AI Projects for AITF Participants

Tentang AITF

The Monev Dashboard demonstration at the AITF Komdigi x UGM Workshop 3 solidifies MVP readiness towa

Objectives of AITF

1

Building an Ecosystem

Building an ecosystem for sustainable AI talent development. This ecosystem serves as a catalyst for driving innovation in the AI ​​sector in Indonesia.

2

AI Talent Development

To develop AI talent who not only possess strong technical skills, but also have experience in the study and development of AI solutions, and are capable of applying AI technologies to solve real-world challenges across various sectors.

3

Generating Solutions

To produce practical solutions through AI research and innovation to address challenges in national priority programs as well as industry.

4

Experience & Contribution

Enhancing experience, fostering active participation, and expanding the digital talent portfolio through engagement in priority programs across government institutions and the private sector.

5

Quantity & Quality

Enhancing the quantity and quality of digital talent within the National Digital Talent Pool (DTP), managed by the Human Resources Development Agency (BPSDM) of the Ministry of Communication and Digital Affairs.

Implementation Framework

Kerangka AITF

🎓 Competencies Developed

Mastery of End-to-End AI Solution Development
Participants are equipped with comprehensive knowledge and skills covering the entire AI solution pipeline.

Practical Skills for Industry
Participants are trained through real-world case study experiences aligned with industry needs, enabling them to build applied AI product portfolios and develop the ability to critically understand business contexts and user requirements.

🎯 Target Participants

AITF participants are organized into collaborative teams consisting of active university students and a supervising lecturer (Technical Tutor) from the same institution. Students are preferably from fields related to Artificial Intelligence (AI), Data Science (DS), Informatics, Statistics, or Mathematics. Selection is based on technical competencies, foundational AI knowledge, and commitment to completing the proposed solution.

Each use case is derived from real-world challenges across various national priority sectors, ensuring that the resulting solutions are relevant, applicable, and implementable. Unlike conventional training programs, AITF emphasizes hands-on development based on real use cases to produce outstanding AI practitioners who are ready to enter the industry and emerge as future innovation leaders.

Team Structure and Roles of AITF Participants

Struktur

PMO (Project Management Office)

PMO (Project Management Officer) in charge of monitoring, coordinating, and ensuring program continuity, ensuring implementation adheres to the approved timeline, objectives, and the strategic direction set by Komdigi.

Students

Active third- or fourth-year undergraduate (Bachelor’s) students or Master’s students, preferably from fields related to Artificial Intelligence (AI), Data Science (DS), Informatics, Statistics, or Mathematics. Selection is based on technical competencies, foundational understanding of AI, and commitment to completing the proposed solution

Expert Tutor

Expert Tutors are appointed by the AITF program implementation team based on the specific needs of each use case. They consist of senior academics, professional researchers, or industry practitioners—both domestic and international—who provide advanced mentorship, strategic input, and technical validation of the use cases developed by the team.

Technical Tutor

Each lecturer serving as a Technical Tutor may mentor a maximum of five (5) students within one team. The lecturer, who comes from the same study program as the students, acts as a day-to-day technical mentor throughout the program implementation

AI Talent Journey

AI Talent Journey

AITF plays a strategic role in producing AI Practitioners and AI Specialists to possess skills relevant to industry needs and global competitiveness, through a real use case based approach.


AI Specialist:
Possesses deep knowledge at the research level, innovates, produces scientific publications, leads teams, and builds frameworks and methodologies that can serve as references for Artificial Intelligence development.


AI Practitioner:
Technical mastery of integrating AI into real solutions (end-to-end AI), capable of innovating, building and fine-tuning LLM/Generative AI Models, including creating Minimum Viable Products (MVP).


AI Developer:
Technical mastery at intermediate and advanced levels including training, evaluation, hyper-parameter tuning, deployment of Discriminative AI Models. As well as expertise in using existing Generative AI models to increase productivity.


AI Beginner:
Basic understanding of AI concepts, machine learning (ML), and deep learning (DL). At this stage, one masters the basics of mathematics, statistics, and Python programming for simple machine learning applications.

Program Benefits & Activities

AITF Program Activities

Core Process in Developing AI Practitioner Talent

Aktifitas Program AITF

Program Pembinaan

National & International Training Programs

Access to Coursera

Soft Skills Training

National (SKKNI) & International/Global Certification

Fasilitas Teknologi

GPU & Cloud Infrastructure Support

Access to the Latest LLM APIs

Pendampingan

Expert Tutors (Diaspora & Komdigi)

Expert Lecturers (Industry/Companies, Global Tech Firms, Overseas Universities)

Technical Tutors from Universities

Mentors from Key Stakeholders

Program Benefit

Benefits of AITF for Participants

 Registration through partner universities collaborating with the AITF Program and BPSDM Komdigi

Academic Benefits

  • Credit Conversion (Subject to University Policy)
  • Enhanced Technical & Analytical AI Competencies
  • Collaboration with Professional Lecturers & Tutors

Professional Benefits

  • Real-World Case Study Experience & Practical Implementation Solutions
  • Professional Network, Recommendations & Career Opportunities
  • Showcase & Publication of Solutions at National Forums

Personal Development Benefits

  • Team Collaboration, Leadership & Project Management
  • Understanding AI Ethics & Social Impact
  • Foundation for Career & Continued Professional Development

Additional Benefits

  • National & Global Certification
  • Opportunity for Advanced Empowerment Programs
  • Independent Learning in Emerging Technologies

Expert Tutor

2025

Expert Instructor & Program Lead

Said Mirza Pahlevi, D.Eng

Said Mirza Pahlevi, D.Eng

Head of Center for Digital Talent Development (BPSDM Komdigi) Senior Data Scientist & GenAI Engineer

Diaspora Expert Instructor

Louis Owen

Louis Owen

AI Researcher | AI Research Engineer, Author of Hyperparameter Tuning with Python

Cahya Wirawan

Cahya Wirawan

System Engineer at CTBTO Austria | System Engineer, Software Engineer, AWS Community

Adhiguna Surya Kuncoro

Adhiguna Surya Kuncoro

Research Scientist | NLP, Multilingual AI, Deep Learning

Industry Expert Instructor

Winton

Winton

Business-Driven Technology Leader at IBM Indonesia | AI, Cybersecurity and Hybridcloud Technologist

Muhammad Maliqi Akbar

Muhammad Maliqi Akbar

Solution Architect at Alibaba Cloud Indonesia | Technology Enthusiast, Data & AI Expert

Expert Instructor from an International University (Sungkyunkwan University)

Murugarj Odiathevar, PhD.

Murugarj Odiathevar, PhD.

Research Business Foundation Sungkyunkwan University, Republic of Korea

University of Tokyo (Matsuo Lab)

Shunsuke Kamiya, Ph.D.

Shunsuke Kamiya, Ph.D.

Researcher at Matsuo-Iwasawa Lab | University of Tokyo

Dr. Zihui Li (Irene)

Dr. Zihui Li (Irene)

Project Lecturer at Matsuo-Iwasawa Lab | University of Tokyo

University of Twente

Dr. Alexia Briassouli

Dr. Alexia Briassouli

Assistant Professor on Artificial intelligence

Program Timeline

Timeline (2026)

Activity 1

Participant Registration and Selection

The initial phase of AITF participant registration, encompassing administrative screening, written examinations, and interviews conducted by the Ministry of Communication and Digital Affairs and the University of Brawijaya

Activity 2

Onboarding and Associate Data Scientist Training

Participants undergo a comprehensive onboarding process followed by specialized Associate Data Scientist training

Activity 3

Associate Data Scientist Briefing and Certification

Participants undergo a technical briefing and Associate Data Scientist certification as a prerequisite for the subsequent stages.

Activity 4

Workshop 1

Initial briefing on Large Language Model (LLM) concepts and data collection preparation for advanced training processes. Furthermore, participants undertake Deep Learning training as an advanced continuation of the Associate Data Scientist curriculum.

Activity 5

Workshop 2

Briefing on Continued Pre-Training (CPT) and Supervised Fine-Tuning (SFT) preparations using curated datasets. Additionally, participants will undergo Advanced Data Analytics training as a progression from the Deep Learning phase

Activity 6

Workshop 3

Evaluation of CPT and SFT outcomes, alongside preparations for transforming LLMs into a Minimum Viable Product (MVP). Participants will also continue their ongoing Advanced Data Analytics training

Activity 7

Workshop 4

Participants will present their Proof of Concept (PoC) innovations utilizing LLMs and receive comprehensive briefings on the real-world implementation and maintenance of LLM systems

News

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Heading Towards Demo Day: AITF Komdigi x UGM Workshop III Solidifies System Integration and MVP Technical Readiness

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Expert Lecture x UB: Addressing the Challenges of AI Reliability and Transparency in the Real World

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Strengthening the National Artificial Intelligence Ecosystem, Komdigi Holds Workshop II AITF 2026

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Our Partners

DITJEN PENGAWASAN RUANG DIGITAL
Kementerian Sosial
Institut Teknologi Sepuluh Nopember
Direktorat Jendral Komunikasi Publik dan Media (KPM) Komdigi
Google Indonesia
Amazon Web Services
Sungkyunkwan University
Gadjah Mada University
IBM Indonesia
Alibaba Cloud Indonesia
Jica
Matsuo Lab
Universitas Brawijaya

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