The rapid advancement of Artificial Intelligence (AI) is reshaping Indonesia's technology landscape. Once primarily recognized and utilized by specialized professionals, AI is now becoming increasingly accessible to the broader public, supporting a wide range of personal and business activities.
As technology continues to evolve, businesses face important questions about how to adapt. Should organizations continuously invest in the latest innovations? Will AI eventually replace human jobs? And what skills will employees need to remain competitive in an AI-driven workplace?
As technology continues to evolve, businesses face important questions about how to adapt. Should organizations continuously invest in the latest innovations? Will AI eventually replace human jobs? And what skills will employees need to remain competitive in an AI-driven workplace?
As technology continues to evolve, businesses face important questions about how to adapt. Should organizations continuously invest in the latest innovations? Will AI eventually replace human jobs? And what skills will employees need to remain competitive in an AI-driven workplace?
Indonesia's Technology Transformation: From Digital Acceleration to AI
The technology industry has continuously evolved in response to innovation and changing market demands. According to Adriansyah, major technological shifts have traditionally occurred over cycles of approximately 10 to 15 years. However, the past five to six years have brought an extraordinary acceleration of technological change in Indonesia.
This transformation became particularly visible during the COVID-19 pandemic, when businesses across industries were pushed to accelerate digital adoption. E-commerce experienced significant growth, while digital financial services, fintech platforms, and mobile transactions became increasingly integrated into everyday activities.
During this period, technology startups also expanded rapidly, with many companies prioritizing business growth and user acquisition.
However, the industry entered a correction phase between 2022 and 2024. Business models that previously emphasized aggressive expansion began facing greater pressure to demonstrate sustainable financial performance. As a result, companies increasingly shifted their attention from the number of users they could acquire to the profitability and sustainability of their businesses.
Adriansyah compared this development to the dot-com bubble correction in the early 2000s, when rapid growth in technology-based businesses was not always supported by sustainable business fundamentals.
By 2024, the growing popularity of AI had become one of the most significant developments shaping the technology landscape.
Although AI itself is not a new concept, advancements in Large Language Models (LLMs) have made intelligent technologies considerably more accessible to the general public.
Capabilities that were previously associated with specialized technological applications are now available to users from various backgrounds, enabling them to retrieve information and complete tasks more efficiently.
This growing accessibility has played a major role in bringing AI into mainstream discussions and business practices. The transformation highlights an important point: technological progress is not only defined by the invention of new capabilities, but also by how widely and effectively those capabilities can be adopted.
Why Technology Integration Matters More Than Adopting the Latest Innovations
As AI continues to gain attention, many organizations are exploring new technological investments to improve productivity and operational efficiency.
However, does adopting the latest technology always guarantee better business performance?
From Adriansyah's perspective, the ability to integrate technology with existing systems and business operations is often more important than simply implementing the newest solutions.
Without effective utilization, even sophisticated technology may become little more than an expensive demonstration system that delivers limited operational value.
This consideration is particularly important for AI implementation because the effectiveness of intelligent systems depends heavily on the availability and quality of data.
To generate meaningful information, AI requires access to complete, accurate, consistent, and integrated business data.
When information remains fragmented across different systems, organizations may struggle to maximize the capabilities of AI.
In contrast, integrated and well-maintained data allows technology to process information more effectively and generate insights that support business activities.
This means organizations do not necessarily need to replace their existing infrastructure with the latest solutions. Established technologies can continue delivering significant value when they are properly integrated and aligned with operational requirements.
For example, an AI-powered customer service solution can become more effective when connected to relevant enterprise systems, enabling it to retrieve accurate information and support customer inquiries more efficiently. Ultimately, successful digital transformation is not solely about introducing new technology. It also requires organizations to establish strong connections between their systems, data, and business processes.
Will AI Really Replace Human Jobs?
Will AI Really Replace Human Jobs?
As intelligent technologies become increasingly capable of completing tasks within seconds, concerns continue to grow about whether AI will eventually replace human workers.
According to Adriansyah, the answer is not entirely straightforward.
AI primarily replaces tasks rather than automatically eliminating entire human roles.
Activities that are repetitive, routine, or follow predictable patterns are generally more suitable for automation. AI can significantly accelerate these processes, helping organizations improve efficiency and reduce the time required to complete certain activities.
Nevertheless, the impact of automation on employment remains an important consideration.
One particularly vulnerable group is entry-level or junior employees, whose responsibilities often involve tasks that are relatively easier to automate.
This creates a potential long-term workforce development challenge.
If organizations significantly reduce opportunities for junior professionals to gain experience and develop their capabilities, they may eventually face difficulties developing the next generation of senior professionals.
For this reason, Adriansyah emphasized the importance of continuing to develop junior talent while adapting their skills to evolving technological requirements.
He also highlighted another important perspective: the greatest competitive challenge for workers may not necessarily come directly from AI, but from other professionals who know how to use AI more effectively.
As a result, the ability to adapt, learn, and apply AI appropriately is becoming an increasingly important factor in professional development.
Essential Human Skills in the AI Era
The growing adoption of AI is also changing the skills required in the workplace.
One capability receiving significant attention is prompt engineering, which involves creating effective instructions to guide AI systems toward relevant outputs.
However, Adriansyah explained that writing prompts is only one part of using AI effectively.
Several underlying human competencies remain essential to achieving reliable results.
- Problem Framing: Defining the Right Problem
Different people can describe the same problem to an AI system and receive different responses.
These differences do not necessarily result from variations in the technology itself. They may also reflect how users formulate questions, provide context, and structure instructions.
This makes problem framing an increasingly valuable skill.
It involves understanding a situation, identifying the underlying challenge, and clearly explaining what needs to be addressed before requesting assistance from AI.
By developing stronger problem-framing capabilities, individuals can provide more precise instructions and improve the relevance of AI-generated responses.
- Critical Thinking and Judgment: Evaluating AI Outputs
Although AI can generate information quickly, its responses are not always accurate.
Large Language Models can produce outputs that appear convincing but contain incorrect or misleading information, a phenomenon commonly referred to as AI hallucination.
Consequently, users must maintain the ability to critically evaluate AI-generated content.
Critical thinking and judgment enable individuals to assess whether information is accurate, relevant, and appropriate for a particular business context.
Verification is especially important when AI-generated outputs are used to support professional analysis or business decisions. Rather than accepting responses without question, users must understand when additional review, validation, or correction is necessary.
- Domain Expertise: Understanding the Business Context
Another essential capability is domain expertise, or a deep understanding of a particular professional field or industry.
According to Adriansyah, individuals must understand the work they are asking AI to support.
Without sufficient knowledge of the relevant subject, users may struggle to identify mistakes or determine whether AI-generated recommendations are appropriate.
For example, business professionals using AI for analysis still need to understand operational processes, industry characteristics, and organizational objectives. AI can accelerate information processing, but human expertise remains essential for interpreting results and ensuring they are applied appropriately.
- Accountability: Taking Responsibility for AI-Assisted Work
An important aspect of AI adoption that is sometimes overlooked is accountability.
AI can help professionals complete tasks more quickly and produce various outputs or recommendations. However, when mistakes occur, responsibility cannot simply be transferred to the technology.
Adriansyah emphasized that individuals remain accountable for the results of the AI systems they use.
Therefore, accountability is a fundamental requirement for responsible AI usage. Professionals must not only understand how to utilize AI effectively but also recognize their responsibility to review its outputs and manage the consequences of decisions made with technological assistance.
Professionals must not only understand how to utilize AI effectively but also recognize their responsibility to review its outputs and manage the consequences of decisions made with technological assistance.
Human-AI Collaboration: Enhancing Capabilities Rather Than Simply Replacing Work
The development of AI provides organizations with opportunities to accelerate workflows and improve productivity.
However, its potential becomes more meaningful when technology is positioned as a tool that enhances human capabilities. As Adriansyah explained, AI initially serves as an instrument that helps people complete tasks more efficiently.
In practice, intelligent systems can assist with information processing, content preparation, and repetitive operational activities.
Meanwhile, humans remain responsible for understanding business problems, providing appropriate instructions, evaluating results, and ensuring accountability.
In customer experience operations, for example, AI can support routine inquiries and assist with retrieving relevant information. Human agents, however, remain important for validating responses, understanding complex customer needs, and determining appropriate resolutions.
This illustrates how AI can support greater operational efficiency while human expertise continues to play a central role in ensuring service quality and responsible decision-making.
Rather than treating automation as an objective in itself, organizations should focus on how technology can strengthen employee capabilities and improve overall business performance. To achieve this, businesses need to encourage continuous learning and create opportunities for employees to develop the skills required to work effectively with AI.
The Future of Indonesia's Technology Industry Depends on Human and Business Readiness
The growing accessibility of AI marks a significant development in Indonesia's technology industry. As intelligent technologies become more capable, organizations have greater opportunities to improve operational efficiency and explore new approaches to business processes.
However, successful AI adoption requires more than access to advanced technological solutions.
High-quality data integration, a clear understanding of business requirements, and the ability of people to utilize and evaluate AI effectively remain essential to creating meaningful value.
The discussion with Adriansyah Adnan in Smart ConneXion highlights that AI advancement does not simply eliminate the need for human involvement. Instead, it changes the skills, responsibilities, and ways of working that organizations must develop.
Businesses need to integrate emerging technologies thoughtfully, while employees must continuously strengthen their capabilities to remain productive and relevant.
Ultimately, the future of Indonesia's technology industry will not be determined solely by who adopts AI the fastest, but by who can use it most effectively, critically, and responsibly.
Watch the full Smart ConneXion discussion featuring Adriansyah Adnan, CTO of Anabatic Technologies, to explore more perspectives on Indonesia's evolving technology landscape and the changing role of humans in the AI era.
