WSJ Tech News Briefing – "Is the AI Revolution Slowing Down? What to Expect in 2026"

Date: December 30, 2025
Host: Danny Lewis (WSJ)
Guests: Bel Lynn (WSJ), Chip Cutter (WSJ), Stephen Rosenbush (WSJ Leadership Institute)

Overview: Main Theme and Purpose

This episode investigates whether the pace of the AI revolution is actually slowing down or simply evolving as it enters 2026. The panel of WSJ experts reflects on the standout moments of the past year, rising investor skepticism, the impacts on the labor market, shifting leaders in AI technology, mounting energy demands, and what regulation and innovation may look like in the near future. The discussion aims to clarify how companies are reacting to AI’s rapid advancement and what listeners should expect in the coming year—especially regarding jobs, infrastructure, and competition within the AI ecosystem.

Key Discussion Points and Insights

1. The Most Important AI Events of 2025

Bel Lynn (01:44)

• OpenAI’s "Code Red" Memo (December): Marked a shift as Google’s Gemini models began to seriously threaten OpenAI’s dominance.
  • "It was this really profound moment to me because it indicated that OpenAI...was really threatened by Google's Gemini models." [01:50]
• Circular AI Deals: Major players like Nvidia, AMD, Oracle, and Microsoft created an interconnected web, raising bubble fears.
• MIT Study: Found 95% of AI pilots at companies fail, highlighting doubts about AI’s immediate ROI and fueling concerns of an overhyped industry.

Stephen Rosenbush (03:01)

• AI Infrastructure Growth: Google now processes 50 times more AI tokens than a year prior, showing a massive acceleration.
  • "Google is now processing more than 50 times the amount of AI measured in these units called tokens, than it was last year. That's just an enormous increase." [03:06]
• Disney and Walmart Join OpenAI Ecosystem: Points to AI becoming fundamental in new commerce and payment infrastructures.

2. Impact on Jobs and the Workplace

Chip Cutter (04:17)

• Changing Leadership Tone: Mid-2025 saw Amazon CEO Andy Jassy signal major reductions in corporate workforce due to AI advancements.
  • "We expect this will reduce our total corporate workforce." (Referencing Jassy’s note) [04:27]
• Layoffs Ripple Effect: Companies shift from talent hoarding to rationalizing and reducing headcount, inspired by startup models with high valuations and tiny teams.

2026 Job Market Outlook (05:22)

• Continued Layoffs: More companies likely to view staff as an impediment rather than an asset, moving toward smaller, more efficient AI-aided organizations.
  • "They almost feel like staffers are an impediment to growth, that having a bigger headcount actually hurts a company's ability to reach its goals." [05:30]

Creation of New Roles (06:09)

• Emerging Positions: Walmart’s “agent builder” role and expansion in high-touch customer areas show AI is not purely negative for employment.
  • "Walmart...created an agent builder position this year. That's an employee who helps build AI tools to help merchants." [06:16]
• Even non-tech companies are hiring AI-focused leaders.

3. State of AI Agents

Stephen Rosenbush (06:55)

• The year was expected to be the "Year of the AI Agent" but saw only incremental progress. Adoption is real and growing, but wholesale transformation hasn't arrived.
  • "We have not gotten to the point where they're ubiquitous and they're like transforming the company on a wholesale level. But adoption is growing." [07:08]

[Break for Ads Skipped]

4. AI Market Leaders & Shifting Positions (09:14)

Bel Lynn:

• OpenAI's Shakiness: Once undisputed, now faces strong competition from Anthropic, Cohere, and renewed interest in diversified AI models. Companies increasingly select from multiple models instead of defaulting to OpenAI.
  • "Its status as by far the market leader is no longer a guarantee...we're increasingly seeing companies use a bunch of different models." [09:19]

Stephen Rosenbush (09:52)

• Hardware Competition: Google exerts pressure on Nvidia in the GPU market.
• Jevons Paradox Applied to AI: As AI compute costs drop, consumption inexorably rises:
  • "There's this idea in tech of...Jevons Paradox, which means that as the price goes down...they'll buy two boxes of cereal." [09:59]

5. Energy Demands and Data Infrastructure (10:36)

Stephen Rosenbush (10:45)

• Energy Demand "Ginormous": Meeting AI's future power requirements will demand “throwing everything at it,” including reviving nuclear plants and experimenting with new energy sources.
  • "The energy demands for AI are somewhere between ginormous and astronomical." [10:46]
  • "Three Mile island plant is being revived by Microsoft." [10:50]

Bel Lynn (11:11)

• Power as Bottleneck: U.S. power grid lags behind China's in terms of capacity to support AI advances, making further innovation (nuclear, geothermal, infrastructure permitting) critical.
  • "Power is really the primary constraint in developing more compute power for AI." [11:12]
  • Expected increased federal support for data center development.

6. The Realities for Entry-Level Jobs (12:04)

Chip Cutter

• Entry-Level Job Scarcity: Recent college graduates struggle to find white-collar work, as AI increasingly automates entry-level tasks (analysts, first-rung positions).
  • "These AI models make mistakes, but so do junior analysts...he could have kind of a tenth of his analyst team than he had at this point last year." [12:22]
• Never-ending Layoffs: Layoffs likely to become a persistent feature as companies continually optimize with software.

Stephen Rosenbush (13:15)

• No Easy Answers: Immediate human costs of job losses are not offset by theoretical future job creation.
  • "If someone loses their job today, the fact that their nephew or niece may have a fantastic new job down the road doesn't really help them right now." [13:18]

Chip Cutter (13:36)

• Consumer Demand Dilemma: Fewer people in jobs raises questions about who will buy products.
  • "Who's going to buy all these products if people don't have work? And that's a fair point. And I'm not sure we've really grappled with it." [13:38]

7. Final Reflections and Looking Forward

Stephen Rosenbush (14:02)

• Rapid Change: The AI landscape is so dynamic that predictions can change within weeks, not years.

Bel Lynn (14:17)

• Counterpoint – Room for Optimism: Industry cheerleaders predict the rise of new, AI-related jobs; however, upskilling in AI is a difficult barrier for many.
  • "There are cheerleaders...who say that job displacement...really skews too heavily on the job destruction side, that new jobs will be created. It’s just a moment of change." [14:20]
  • Calls for cautious optimism but acknowledges transition challenges.

Notable Quotes & Memorable Moments (with Timestamps)

• Bel Lynn on OpenAI's challenge:
  "OpenAI...was really threatened by Google's Gemini models." [01:50]
• Stephen Rosenbush on infrastructure growth:
  "Google is now processing more than 50 times the amount of AI measured in these units called tokens, than it was last year." [03:06]
• Chip Cutter on workforce downsizing:
  "We expect this will reduce our total corporate workforce." (paraphrasing Amazon CEO) [04:27]
• Stephen Rosenbush on energy:
  "The energy demands for AI are somewhere between ginormous and astronomical." [10:46]
• Chip Cutter on persistent disruption:
  "What we could see going forward is...the drip, drip, drip of layoffs happen throughout the year." [12:54]
• Bel Lynn on industry optimism:
  "New jobs will be created. It’s just a moment of change." [14:20]

Timestamps for Key Segments

• AI in 2025: Standout Moments – 01:44 to 04:09
• Job Impact and Amazon Memo – 04:09 to 06:52
• AI Agents: Reality vs Expectation – 06:52 to 07:52
• AI Market Leadership and Open Competition – 09:14 to 09:52
• Energy, Infrastructure, and Policy Shifts – 10:36 to 12:04
• Entry-Level Worker Crisis & Ongoing Layoffs – 12:04 to 13:46
• Final Reflections – Risks, Rewards, Uncertainties – 13:46 to 14:51

Closing Thoughts

The episode presents a nuanced picture: AI advancement is not slowing, but it is entering a more complex and challenging phase. Competition is heating up, infrastructure demands loom large, and the labor market faces unprecedented disruption—though, for optimists, perhaps equally unprecedented new opportunities. The pace of change makes exact predictions difficult, but all agree that the next year will be critical in shaping the future of AI’s impact on business, jobs, and society.