At a time when many people worry that artificial intelligence will replace human jobs, a different view is coming from one of the world’s best-known AI leaders. Andrew Ng says the real challenge is not job loss but a lack of people who can actually build AI systems. Even as companies spend huge amounts of money on AI, he believes there are simply not enough skilled workers to meet the demand. His message offers hope and clear direction to students and young professionals watching the fast changes around them. In India, this advice feels timely and practical today now.
Andrew Ng is the founder of Google Brain and also started the online learning platform Coursera. Over the years, he has become a respected voice in the global technology space. In a recent post on X, he said the world is missing the bigger picture about AI and work. According to him, the problem is not too many machines but too few trained people.
Also read: Satya Nadella says AI must boost human productivity, not replace jobs
Ng says AI may be growing fast, but it still depends heavily on human effort. He points out that areas like system design, testing, and real-world use need skilled hands. Because of this, companies are struggling to hire the right people even after offering high pay. Ng says he often hears the same worry from students and fresh graduates. They ask if learning AI still makes sense when tools seem to be doing more on their own. His answer, he says, is always a clear yes.
He believes that as AI spreads into health, banking, farming, and education, it creates more jobs, not fewer. Many firms, he adds, are unable to find people who can take ideas and turn them into working systems. Ng also shared three simple tips for those who want an AI-related job by 2026.
His first advice is to focus on building complete systems, not just small demos. He says employers value people who understand the full journey from data to daily use. The second tip he offered is to practise regularly. Ng warns that only reading books can leave gaps, while only building without basics can cause mistakes. Practice, he says, helps people build strong and reliable solutions.
His third tip is to read research papers if possible. He explains that this is useful for those who want to work on new problems. Ng has also spoken earlier about why fears of AI taking over all jobs are misplaced. In an interview last year, he said today’s AI still needs careful human training and support. He stressed that reaching truly independent machines is still far away.