Author: lethuphuong

📌 South Korea is betting big on domestic AI with an investment of about 400 billion won (~$300 million), aiming to build infrastructure and reduce dependence on Big Tech. The development of its own LLM and domestic GPUs shows that AI has become a factor of national competitiveness. Beyond software, the country is also investing in the semiconductor supply chain, demonstrating a comprehensive strategy to gain control of technology in the AI era.

📌 AI is moving towards a new stage: not just being individually smart but needing to “collaborate like humans.” However, the lack of shared context and intent prevents agents from creating true collective intelligence. Efforts like the “internet of cognition” could unlock the next leap, where AI not only works faster but also thinks together to solve complex problems.

📌 AI reveals the limits of communication based on explicit data, whereas humans can process the unspoken and the ambiguous. As work environments prioritize speed and efficiency, the capacity for deep listening is eroding. The difference between “hearing” and “listening” is key: AI optimizes responses, while humans create meaning. The future is not about competing with AI, but about retaining the capacity for deep listening—the core advantage of human intelligence.

📌 Generative AI is transforming market research into an unprecedentedly fast, cheap, and scalable process, with the ability to reduce costs by tens of thousands of dollars and speed up analysis by up to 60 times. Digital twins and AI interviewing help generate deep insights with a correlation of 0.75 – 0.88 compared to real data. Nevertheless, businesses still need strict control to avoid bias, fake data, and declining research quality when over-relying on AI.

📌 Even if AI can write like a human to the point of being indistinguishable, human psychology remains deeply attached to the value of “authenticity.” With over 27,000 participants and 16 experiments, the results show that simply knowing the origin is AI leads to a significant drop in evaluation. This indicates that the major barrier for AI is not just technology but social perception, where humans still prioritize creativity with a human touch over machines.

📌 Agentic AI is transforming the banking industry at breakneck speed, from 20-minute onboarding to handling 40% of requests automatically and reducing administrative work by up to 90%. Not only does it increase efficiency, but this technology also expands financial access for small businesses. Although still in its early stages, agentic AI is gradually becoming the core foundation for the bank of the future, where services are fast, personalized, and nearly instantaneous.

📌 OpenAI is not just developing AI but also proposing a complete redesign of the economic system to adapt to a superintelligent future. Ideas such as public wealth funds, robot taxes, and a 4-day work week show that AI can reduce jobs but increase productivity. The core issue is the redistribution of value created by AI to avoid inequality and ensure social stability.

📌 The biggest bottleneck of AI is not technology but trust and organizational structure. When 95% of businesses have yet to create value, switching to a decision-driven model with decision products, real-time monitoring, and human-in-the-loop mechanisms is mandatory. This is the key for generative AI to escape experimentation and become a real, sustainable value-creating tool in the enterprise.

📌 KPMG is redefining the role of the expert: from software user to software creator. With the vibe coding model, development time is drastically shortened, accelerating time-to-market. When business expertise combines directly with tool-building capability, the boundary between business and technology vanishes, opening up a new HR model with productivity levels many times higher than traditional ones.

📌 McKinsey predicts AI will create “The Great Flattening,” where middle management layers are cut and leaders can run larger teams thanks to AI. By automating many functions and supporting faster decision-making, businesses can reduce costs and speed up operations. However, this also requires a new governance model to control “digital workers” and ensure long-term efficiency.