
(Based on The New York Times expert roundtable)
Productivity gains alone do not create growth.
Real economic transformation comes from:
Winning organizations will:
The biggest competitive risk is not AI adoption.
It is late, defensive adoption.
Here are the eight experts from the The New York Times AI roundtable, each with a one-sentence introduction and a relevant official or primary website.
Computer scientist at the Santa Fe Institute known for research on AI, complexity, and the limits of current machine learning systems.
Website: https://melaniemitchell.me
Historian and bestselling author (e.g., Sapiens) who analyzes the societal, political, and philosophical implications of AI.
Website: https://www.ynharari.com
Oxford economist studying automation, AI, and the future of work, known for research on how technology reshapes labor markets.
Website: https://www.oxfordmartin.ox.ac.uk/people/carl-benedikt-frey/
AI researcher, entrepreneur, and critic of deep-learning hype, focused on building more reliable and reasoning-based AI systems.
Website: https://garymarcus.com
Co-founder of the AI company Cohere and former Google Brain researcher working on practical large-scale AI systems.
Website: https://cohere.com
AI risk analyst at the nonprofit METR, known for research on long-term AI development timelines and societal impacts.
Website: https://metr.org
Co-founder and CEO of Perplexity, an AI-driven search company building conversational knowledge assistants.
Website: https://www.perplexity.ai
AI policy researcher and executive director at Georgetown’s Center for Security and Emerging Technology, focusing on governance and global AI competition.
Website: https://cset.georgetown.edu

Based on a New York Times Opinion roundtable
Artificial intelligence has moved from research labs to dinner-table conversations in just a few years. According to a recent The New York Times Opinion roundtable, even experts who work on AI every day disagree sharply about what comes next. But beneath the differences, a few clear themes emerge.
Below is a synthesis of the discussion among eight AI researchers, entrepreneurs, economists, and policy thinkers about where AI is heading in the next five years.
One of the strongest points of agreement is that AI will become deeply embedded in daily life. Nick Frosst, co-founder of Cohere, predicts that AI will become “boring in the best way,” fading into the background like GPS or spreadsheets.
But several experts push back against the idea that today’s systems represent human-like intelligence.
Bottom line: AI will be widespread and useful, but not close to human-level intelligence across the board.
Across sectors, the panel expects very different timelines and effects.
Most experts agree that coding is one of the most AI-friendly fields because it is purely digital.
Carl Benedikt Frey notes that developers complete tasks more than 50% faster with AI tools, although human review is still required.
Some predict major breakthroughs, but others are skeptical.
Mitchell points out that AI still struggles with core scientific tasks like asking the right questions or designing experiments.
One of the more subtle but important points comes from economist Carl Benedikt Frey.
He argues that:
He compares AI productivity tools to improved looms: they made cloth cheaper, but didn’t transform the economy the way new industries did.
Implication: The biggest value of AI will come from new business models, not just automation.
Several experts see the social impact as more uncertain than the technical one.
Opinions diverge on whether AI will increase unemployment.
But most agree work will change significantly rather than disappear entirely.
Yuval Noah Harari warns that the AI transition could trigger a global psychological crisis as societies struggle to adapt.
The panel is split on technical risks, but several agree that AI will likely play a role in major global security events by 2030.
Others highlight more subtle risks:
Ajeya Cotra suggests that AI companies may automate their own operations, potentially speeding up progress dramatically.
Aravind Srinivas, CEO of Perplexity, predicts a future where people have highly personal AI assistants that work privately for them.
In this view, AI becomes:
Several experts also believe most people will use AI chatbots daily by 2030.
Perhaps the most striking takeaway is how little agreement there is on artificial general intelligence.
Even among top experts, the timeline for human-level AI remains deeply uncertain.
Across all viewpoints, three themes stand out:
Or as Yuval Noah Harari puts it, humanity may be entering the largest psychological experiment in history — without knowing the outcome.
For companies, the message is surprisingly pragmatic:
The future of AI will likely be less about sci-fi breakthroughs — and more about slow, uneven, but very real transformation across every sector.












































