NextFin News - The landscape of professional evaluation in the technology sector is undergoing its most significant transformation since the dawn of the internet. As of February 20, 2026, the industry has moved past the experimental phase of artificial intelligence, officially codifying AI proficiency as a primary benchmark for hiring and performance reviews. This shift is no longer confined to specialized AI research roles; it has permeated the entire software development, design, and management lifecycle.
According to the IT industry on the 20th, South Korean tech giant Naver has begun implementing "AI utilization ability in the field" as a preferential qualification for experienced developers and designers. This move is mirrored in Silicon Valley, where companies like Meta, Amazon, and Microsoft are revamping their performance reviews to heavily reward top-tier performers who demonstrate measurable output gains through AI integration. The trend is driven by a fundamental necessity for corporate survival: as AI investments balloon into the billions, executives are under immense pressure to prove that these tools are translating into tangible productivity spikes.
The data supporting this shift is stark. An analysis of recruitment announcements for large companies conducted by the platform Catch for college graduates reveals that job postings including "AI utilization" as a keyword rose 16.8% year-over-year, reaching 743 in the past year. Within the IT sector specifically, this requirement appeared in 80% of all analyzed cases. Naver Cloud, for instance, now explicitly seeks candidates who have demonstrably improved their productivity using tools such as Claude Codes, Gemini, and GitHub Copilot. Even creative roles are not exempt; UX and UI designers are now evaluated on their ability to use generative AI tools alongside traditional design software.
This evolution marks the birth of the "AI-native" professional. In this new era, the value of a developer is no longer measured solely by their ability to write syntax, but by their skill in prompting, debugging, and orchestrating AI agents. This is a logical progression of the "efficiency mania" that has gripped the tech sector since U.S. President Trump took office in 2025, emphasizing deregulation and rapid technological dominance. Under the current administration's focus on maintaining a competitive edge in the global AI race, U.S. President Trump has encouraged a corporate environment where output is the ultimate currency.
However, the deep analysis of this trend reveals a growing divide within the workforce. By shifting the focus from "potential" to "measurable output," tech companies are creating a winner-take-all dynamic. According to reports from Business Insider, the new performance review models at firms like Meta are designed to reward the top 5% of performers with bonuses of up to 300%, while average workers—those who may be slower to adapt to AI workflows—receive minimal incentives. This creates a "middle-child syndrome" where the backbone of the workforce feels sidelined, potentially leading to burnout and a talent drain of experienced but non-AI-native staff.
Furthermore, the use of AI to evaluate AI usage creates a feedback loop of intensified oversight. Meta now employs internal dashboards to monitor how frequently and effectively employees engage with AI tools. While this data-driven approach aims to minimize human bias in evaluations, it introduces a new form of algorithmic pressure. Employees find themselves in a high-stakes environment where every "badge-swipe" and line of code is scrutinized by the very technology they are expected to master. This level of surveillance, while efficient for the bottom line, risks stifling the creative risk-taking that historically drove Silicon Valley’s breakthroughs.
Looking forward, the integration of AI into evaluations will likely spread beyond IT into professional services such as law, auditing, and consulting. The "AI-native" requirement will become the new literacy. For the workforce, the message is clear: adaptability is the only path to job security. For corporations, the challenge will be balancing the pursuit of hyper-productivity with the need to maintain a healthy, collaborative culture. As we move further into 2026, the success of a tech company will be defined not just by its AI models, but by its ability to manage the human-AI synergy without breaking the human element of the equation.
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