What Experts Say About AI, Jobs, and Creative Careers
This is an English version of the earlier summary, with direct links to the original answers, interviews, posts, and research wherever possible.
1. Andrew Ng
Andrew Ng, founder of DeepLearning.AI and former head of Google Brain, has given a very direct answer to people worried about AI displacing their jobs:
“Learn about AI and take control of it.”
His broader point is that one of the most valuable future skills will be the ability to tell a computer precisely what you want it to do. He argues that understanding software and at least some coding can help people direct AI systems much more effectively.
Ng gives a creative example from his own work. While producing Generative AI for Everyone, he worked with a collaborator who had studied art history. That collaborator could prompt Midjourney using specific terminology about historical styles, palettes, and artistic influences, and produced much stronger results than Ng could on his own.
The implication is that domain knowledge still matters. AI can generate the output, but expertise helps a person describe, judge, and steer that output.
Source: Andrew Ng, “Learn the Language of Software,” DeepLearning.AI
Related interview: Andrew Ng at Davos 2025, Moneycontrol
2. Ethan Mollick
Ethan Mollick, professor at the Wharton School, argues that professional expertise continues to matter when working with AI.
After experimenting with AI systems on research, coding, and creative tasks, he described himself at different times as a creative director, a troubleshooter, and a domain expert validating results. His conclusion was that the quality of the final output depended heavily on his own expertise.
That means the human role increasingly includes deciding what should be made, recognizing whether an AI result is good or bad, and knowing how to correct it.
Mollick also gives a very practical recommendation for learning AI. Instead of spending all your time reading about it, he suggests spending roughly 10 hours actually using a frontier AI model on things you already do for work or for fun. The goal is to develop an intuitive understanding of where AI performs well, where it fails, and how to collaborate with it.
Source: Ethan Mollick, “Speaking things into existence,” One Useful Thing
Practical advice: Ethan Mollick, “Thinking Like an AI,” One Useful Thing
Additional interview: “Co Intelligence: An AI Masterclass with Ethan Mollick,” Stanford Graduate School of Business
3. Dylan Field
Dylan Field, cofounder and CEO of Figma, has said that the more time he spends thinking about AI, the more confident he becomes in the role of designers.
His argument is that design is much broader than producing an interface or image. A designer combines cultural context, brand, product experience, user needs, and problem solving. As software becomes easier to create, Field believes design becomes more important rather than less important.
He also expects professional boundaries to become less rigid. Some people who currently call themselves developers may increasingly think of themselves as designers because their work will involve shaping the entire product experience, not only writing code.
Figma expressed the same idea at Config 2024: when AI can produce functioning interfaces from a simple prompt, design becomes the thing that differentiates excellent products from obvious solutions.
Source: Dylan Field and Garry Tan on design, AI, and the power of “locking in,” Figma
Related Figma position: “Config 2024 in review,” Figma
Further reading: “What is good design in the age of AI?” Figma
4. Scott Belsky
Scott Belsky, founder of Behance and a longtime Adobe executive, argues that as AI removes more of the technical friction involved in making things, the differentiating value shifts toward human judgment, taste, ideas, intuition, and creative direction.
One of his most concise formulations is:
“Taste will outperform skill, because skill is going to be offloaded to compute.”
Belsky distinguishes the mechanics of producing creative work from the parts that make it meaningful. In his writing, he argues that as execution becomes easier, original ideas, judgment, process innovation, personal perspective, and the story behind a piece of work become more important.
He also expects professional creators to face a higher bar because nonprofessionals will increasingly be able to produce polished content. His response is not that professional creativity disappears, but that professionals need to push further beyond generic or formulaic output.
Source: Scott Belsky, “Creating in The Era of Creative Confidence”
5. Jensen Huang
Jensen Huang, founder and CEO of NVIDIA, has repeatedly described AI as an assistant that will become part of almost every kind of work.
At SIGGRAPH 2024 he said:
“Everybody will have an AI assistant.”
He argued that AI will affect nearly every industry and will collaborate with creators on tasks such as generating images and virtual scenes. His framing is that AI can amplify human productivity and creativity rather than simply operating as a separate replacement system.
In NVIDIA’s 2026 annual report, Huang makes a related distinction between a task and the purpose of a job. His examples include coding as a task versus innovation as the purpose, and reading medical scans as a task versus caring for patients as the purpose. His argument is that AI can automate more tasks while leaving people to focus more heavily on the higher level purpose of the work.
Source: NVIDIA, “Everybody Will Have an AI Assistant,” SIGGRAPH 2024
2026 source: NVIDIA 2026 Annual Report, SEC filing
6. Adobe Research on Creative Careers
Adobe published research in June 2026 based on two waves of United States job posting data, a survey of 1,433 working creatives, a study of 3,300 people training to enter creative fields, and qualitative research.
One of the clearest labor market signals was that the share of creative job postings explicitly asking for AI skills increased from 10 percent in September 2025 to 15 percent in April 2026.
The research did not conclude that AI fluency had become mandatory across all creative work. In fact, Adobe noted that 85 percent of United States creative professional postings in April 2026 still did not explicitly require AI skills.
The broader pattern was more selective. Working creatives reported integrating AI heavily into areas such as brainstorming and ideation while drawing boundaries around other parts of the process. Adobe’s researchers summarized the emerging role of the human creative professional around directing, evaluating, and taking responsibility for the work, rather than simply asking AI to generate a finished artifact.
Source: Adobe Research, “How AI Is Redistributing Creative Work,” June 2026
Related research: Adobe Research, “How Creatives Are Thinking About AI,” June 2026
Overall Pattern Across These Answers
Across these sources, the recurring idea is not simply “learn prompting.”
Andrew Ng emphasizes learning enough about AI and software to direct computers effectively.
Ethan Mollick emphasizes hands on experimentation plus the expertise required to judge and correct AI output.
Dylan Field emphasizes design judgment and the ability to think holistically about products and user experience.
Scott Belsky emphasizes taste, meaning, ideas, intuition, and creative direction as execution becomes cheaper.
Jensen Huang emphasizes the distinction between automating tasks and replacing the broader purpose of a job.
Adobe’s 2026 research suggests that AI skills are becoming more visible in creative hiring, while human judgment and selective use of AI remain central to professional creative work.