Jakarta (ANTARA) - Artificial intelligence (AI) is reshaping the landscape of global economic competition.
A country's ability to use this technology no longer only determines work efficiency, but also affects industrial productivity, human resource quality, and economic competitiveness.
For Indonesia, the biggest challenge is not only speeding up AI adoption, but ensuring that people can master the technology and create value from it.
This shift poses a fundamental challenge for the national education system. When technology develops faster than curriculum, the gap between graduates' skills and industry needs could widen.
Universities are expected to produce not only educated workers, but also adaptable graduates who can think critically and solve problems through technological approaches.
The growing use of AI among students is part of the challenges. Various applications are already used to write assignments, look for references, analyze information, and make presentations.
However, ease of use does not necessarily reflect mastery of the technology. Without understanding data validity, algorithm limitations, and ethics of use, AI actually risks weakening the ability to think independently.
Therefore, AI education must be driven to go beyond introducing applications toward mastering competencies.
Students must understand how the technology works, when its use is relevant, how to verify its results, and how far decisions can be assisted by machines without removing human responsibility.
One cooperation focused on the goal of intelligence sovereignty was realized, for example, by Sophia Training and Consulting, i3L University, and EduMark on October 19, 2026.
Under a memorandum of understanding, the three institutions agreed to integrate AI learning materials into higher education while expanding training for students and professionals.
Sophia is a UK-based consulting and training company engaged in AI, data management, digital strategy, and executive education.
i3L University has academic capacity in education, research, and innovation, while EduMark is a Jakarta-based education consultancy focused on developing partnerships and readiness for changing workforce needs.
The cooperation can serve as an example of a collaborative approach to address the digital competence gap.
Its strategic value lies not in the signing of the agreement, but in the ability to translate knowledge into measurable skills needed by businesses and society.
Work productivity
In economic terms, AI education is directly linked to labor productivity. Technology can speed up information processing, help with data analysis, improve planning accuracy, and reduce repetitive administrative work.
However, productivity gains do not happen automatically just because companies use AI tools.
Economic benefits only emerge when technology is integrated with business processes, supported by high-quality data, and operated by workers who understand its purpose and the risks of its use.
Without that readiness, digital investment can become a cost burden without delivering meaningful gains.
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That is why upskilling, or improving skills, and reskilling, or equipping workers with new skills, have become urgent needs.
AI transformation concerns not only new graduates, but also existing workers who must adjust their skills to changes in production and organizational processes.
i3L's plan to offer AI training to companies and advanced learning programs for professionals shows the importance of aligning higher education with industry needs.
This kind of learning model needs to be designed around real problems, not merely the ability to operate certain applications.
The success indicators must be concrete. Training needs to be judged by participants' ability to raise efficiency, improve decision quality, produce innovation, or solve problems that previously required more time and cost.
On the other hand, AI education also needs to pay attention to the characteristics of each line of work.
The needs of an economic analyst differ from those of a health worker, educator, manufacturing worker, or micro, small, and medium enterprise (MSME) entrepreneur.
A uniform learning approach risks producing general skills without depth of application.
For the MSME sector, for example, AI could help with demand analysis, inventory management, customer service, and digital marketing.
However, the benefits depend on entrepreneurs' digital literacy, data availability, financing capacity, and how well the technology fits the scale of the business.
Access gap
Another critical issue is the gap in access to digital education. If quality AI training is only available to students or workers at large companies, technological transformation could actually widen inequality of economic opportunity.
Universities, the government, and businesses need to build more inclusive learning models through partnerships, tiered training, and the use of learning technology that can reach the regions.
Besides access, governance of AI usage must be an integral part of education. Issues of personal data protection, information security, algorithmic bias, intellectual property rights, and decision accountability must not be treated as additional material.
The ability to generate information quickly does not always guarantee accuracy and truth. In work involving safety, public service, or economic decisions, misuse of AI can have serious consequences.
Education should position AI as a tool that expands human capacity, not one that replaces reasoning and professional responsibility. Digital skills need to go together with integrity, analytical ability, and sensitivity to social impact.
In the long term, Indonesia also needs to move from being a user to being a developer of technology.
Dependence on foreign applications and systems without improving research capacity, data mastery, and talent development risks limiting the nation's ability to create economic value.
International collaboration pioneered for intelligence sovereignty can open access to global knowledge and learning practices.
However, its success needs to be measured by skill transfer, strengthening of instructors' capacity, curriculum relevance, and participants' ability to produce solutions for Indonesia's needs.
That way, AI education does not stop as a response to technology trends, but becomes part of a strategy for human resource development and national economic transformation.
Indonesia has an opportunity to use AI to raise productivity, expand quality job opportunities, and speed up innovation. However, this opportunity requires adaptive education policy, substantive industry partnerships, and equal access to digital skills.
Indonesia's competitiveness is determined not by how many people use AI, but by how far the technology improves people's ability to produce economic and social benefits.
Sovereignty in the AI era does not mean having to create all technology oneself. Sovereignty means having the knowledge, skills, and capacity to choose, control, and develop technology in line with the national interest.
Indonesia needs a generation capable of steering that change to create national productivity, prosperity, and progress.
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Translator: Hanni, Kenzu
Editor: Bayu Prasetyo
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