Breaking news

Nvidia CEO Jensen Huang Says AI Will Drive Job Growth

Optimism In The Face Of Transformation

Nvidia Chief Executive Jensen Huang has dismissed the notion that artificial intelligence poses a threat to American jobs. Speaking during an engaging conversation hosted by the Milken Institute and broadcast on MSNBC with Becky Quick, Huang presented AI as a transformative force that will re-industrialize the United States rather than usher in an era of mass unemployment.

AI As An Engine For Reindustrialization

Huang pointed to the rapid build-out of AI infrastructure, including advanced chips and data centers, as a source of new industrial activity. The scale of investment required to develop and operate these systems is already generating demand across engineering, manufacturing, and operations. In this context, the AI ecosystem is expected to rely on a wide range of roles, supporting the view that technological growth and employment can evolve together.

Dissecting Job Transformation Versus Replacement

A central distinction in Huang’s argument is between automating tasks and replacing jobs. AI is more likely to take over specific functions within roles, allowing workers to focus on broader responsibilities. This suggests a shift in how work is structured, with productivity gains driven by task automation rather than a direct reduction in employment.

Curbing Undue Fear Over AI Adoption

Huang also addressed concerns about AI risks, noting that some narratives overstate current capabilities. He cautioned that such views may not reflect the current stage of development and can shape public perception in ways not grounded in practical realities, while also contributing to heightened expectations within the industry.

Looking Ahead: Balancing Progress and Prudence

At the same time, projections from Boston Consulting Group suggest that around 15% of U.S. jobs could be affected by AI in the coming years, highlighting the complexity of the transition. These estimates point to a labour market that is likely to adjust as adoption increases, with outcomes depending on how businesses, workers, and policymakers respond.

Conclusion

Together, these perspectives position AI as a factor in structural economic change, influencing how work is performed and how industries evolve, while leaving open questions about the pace and distribution of these changes.

Image Model Releases Drive Download Surge For AI Mobile Apps

Revolutionizing App Growth With Visual Innovation

A report from Appfigures shows that releases of image models are driving stronger growth for AI mobile apps than traditional model updates. According to the data, image model launches generate 6.5 times more downloads than standard updates, marking a shift from earlier cycles that focused on conversational improvements and features such as voice interfaces.

Notable Industry Examples

Several major platforms have seen significant increases in downloads following image model releases. Apps such as ChatGPT and Google Gemini recorded tens of millions of additional installs after introducing image capabilities. Gemini’s Nano Banana model, for example, added more than 22 million downloads within 28 days, representing more than a fourfold increase compared with previous updates.

Economic Impact And Revenue Conversion

Higher download volumes have not consistently translated into revenue growth. While Nano Banana generated strong install numbers, it produced an estimated $181,000 in consumer spending over the same 28-day period. By comparison, ChatGPT’s GPT-4o image model led to more than 12 million additional downloads and generated approximately $70 million in gross consumer spending, which is around 4.5 times higher than in prior update cycles.

Other Trends And Market Dynamics

Additional releases have also contributed to increased installs. Meta’s Meta AI “Vibes” feature added around 2.6 million downloads in under a month, although, similar to other cases, this growth did not translate into comparable revenue gains. Among the examples analysed, ChatGPT remains the clearest case where increased user acquisition aligned with higher consumer spending.

Beyond Image Models: The DeepSeek Case

The report also highlights DeepSeek as an example of a different growth pattern. In January 2025, the app gained around 28 million downloads in a short period, driven by interest in its cost-efficient AI training approach rather than a specific feature release, showing that attention and market positioning can also influence adoption.

Conclusion

The findings indicate that image model releases are effective in driving user acquisition, but their impact on revenue varies across platforms. They also highlight the importance of linking product updates with monetisation strategies as competition in AI applications continues to grow.

Aretilaw firm
eCredo
Uol
The Future Forbes Realty Global Properties

Become a Speaker

Become a Speaker

Become a Partner

Subscribe for our weekly newsletter