After Hours International》The K-Shaped Workplace Has Arrived! Sean Cheng Reveals the Era of 'Cognitive Inflation': Junior Salaries Become Senior Computing Power Costs, One Group Faces Severe Impact

iKala Chairman Sean Cheng has observed the phenomenon of 'cognitive inflation' in the AI wave. On 'After Hours International,' he pointed out that intelligence is becoming commoditized and will, in the future, become humanity’s third fundamental infrastructure—akin to water and electricity. This is why he believes AI is not a bubble: AI has evolved beyond simple Q&A to actually 'do tasks for you,' even identifying decision blind spots and offering multi-angle insights during corporate strategy discussions.

As computing power expands and costs continue to fall, the unit price of 'intelligence' itself is also depreciating. This is the essence of cognitive inflation: the value of human white-collar cognitive work is being gradually diluted.

'Junior salaries become senior computing power costs.'

Cheng paints a picture of the 'K-shaped workplace': white-collar workers within companies will polarize—one group surging upward, the other falling downward. This phenomenon is already evident among software engineers, where top-tier AI and software engineers in Silicon Valley can earn up to 100 times the salary of average engineers.

The reason lies in AI as an 'amplifier': the expertise of senior workers is amplified tenfold, and so is that of junior workers—but with different baselines, the outcomes are vastly different. A person scoring 1 and another scoring 10 originally differ by 9 points; after a tenfold amplification, they become 10 and 100, creating a 90-point gap.

This is changing corporate budgeting logic. Cheng bluntly states that while companies once considered paying juniors a base salary and seniors two to three times that, the new logic is: 'Rather than spend the budget on junior salaries, invest it in computing power so seniors can work with AI.' In other words, 'junior salaries have become senior computing power costs.' Even more harshly, companies are increasingly reluctant to have senior employees mentor newcomers, as their time must be dedicated to AI collaboration and innovation. Resources are being stripped layer by layer and concentrated on those who can maximize output.

Cheng specifically highlights that the group hardest hit at the bottom of the K-shaped curve is those 'currently within three years before or after graduation.' Their careers are just beginning, yet foundational training opportunities are being stripped away, as no one has had time to prepare them for AI adaptation. In contrast, K-12 students still have ample time to gradually adapt to this transformation. This explains why, at recent graduation ceremonies, audiences boo whenever speakers mention AI.

However, Cheng is not entirely pessimistic. He notes that the first phase of the AI wave is 'cost reduction,' which brings structural unemployment pain, especially hitting software talent as the first major victims. But the second phase is 'efficiency enhancement.' Once companies truly integrate AI into R&D cycles—such as using AI to discover more durable shoe materials or assist in chip design—new roles and business opportunities will emerge.

Cheng even describes this transformation as 'not just the end of the industrial revolution, but possibly the beginning of a new Renaissance.' For job seekers and business leaders at a career crossroads, recognizing the reality of the K-shaped divide and securing positions where they can collaborate with AI to create value will be the most critical survival challenge of this generation.