Episode Overview

Podcast: WSJ Tech News Briefing
Episode Title: How Russia Fell Behind In the AI Race
Date: December 9, 2025
Host: Julie Chang
Guests:

• Stephen Rosenbush – WSJ Chief of the Enterprise Technology Bureau
• Peter Ciampelli – WSJ Reporter
• Georgi Khonchev – WSJ Foreign Correspondent

This episode explores the current state of artificial intelligence adoption in business—spotlighting early wins at major U.S. companies—and takes an in-depth look at why Russia, once a technology powerhouse, has fallen so far behind in AI compared to global leaders like the U.S. and China. The discussion ranges from enterprise applications of AI agents to the devastating impact of sanctions, war, and brain drain on Russia’s AI ambitions.

Key Topics & Discussion Points

1. AI Agents in Business: Real Returns & Big Challenges

(00:18 – 05:19)

What are AI agents and how are companies using them?

• Definition:
  • AI agents are tools that perform actions on behalf of humans, from booking reservations to debugging code or analyzing trends.
• Applications:
  • “The handful of companies that are seeing a really meaningful return, in many cases they’re using agents behind the scenes… financial operations, supply chain management, coding, customer service.”
    — Stephen Rosenbush (01:17)
  • Not all problems are suited for agents. Tasks with consistent, repetitive processes (like accounting) are easier to automate than one-of-a-kind challenges.
• Agent roles vary:
  • Can assist individuals or operate across large-scale organizations.

Case Study: Financial Services Provider BNY

• Over 100 AI solutions in use, touching nearly every aspect of the bank.
• “This was the company that really pioneered the idea of the digital employee… in some cases finding say, problems in software code and even proposing solutions or taking action in simple cases.”
  — Stephen Rosenbush (02:35)
• The roster of these digital employees is growing.

Case Study: Walmart

• Uses AI agents for:
  • Customer-facing, employee-facing, and partner-facing tasks.
  • Vetting code—a common application.
  • Detecting product trends (e.g., teen consumer behavior), designing new products, and accelerating go-to-market timelines.
• “They’re able to reduce their time to market by as much as 18 weeks.”
  — Stephen Rosenbush (03:23)
• Agents collaborate to deliver measurable ROI, though the implementation is “very, very hard” with significant trial, cost, and error.
• “What you’re seeing is a proof of concept really at a very large scale in which you’re using hundreds of agents distributed among organizations with tens and tens of thousands of employees…”
  — Stephen Rosenbush (04:44)

Memorable Quote:

• “No one is saying this is easy… developing agents wasn’t just hard, it was very, very hard.”
  — Stephen Rosenbush quoting BNY’s CIO Leon Russell (04:28)

2. Why Russia is Lagging in the AI Race

(06:23 – 11:31)

How did Russia fall behind in AI?

• Despite President Putin’s calls for AI leadership, “the country is stuck on the sidelines as others pull ahead.”
  — Julie Chang (06:23)
• Stanford University ranked Russia 28th out of 36 for AI ecosystem strength, with its leading model barely in the global top 25.

Key Setbacks for Russia:

• Hardware Shortages:
  • “The Western sanctions that followed the full scale invasion in 2022 have just choked off Russia’s access to critical hardware. Computer chips are the most crucial…”
    — Georgi Khonchev (06:58)
  • Legal import of leading-edge GPUs (e.g., Nvidia) is impossible, forcing reliance on third countries and workaround methods—limited and inadequate at scale.
• Brain Drain:
  • Mass exodus of AI and tech talent since the war and draft escalations.
  • “According to some estimates, 70, 80% [of top AI researchers] have left.”
    — Georgi Khonchev (09:52)
  • IT worker shortage could reach 400,000 or more.
• Funding Constraints:
  • Isolation from international markets has shrunk Russia’s pool of venture capital for AI startups and research.

Russia’s Current Coping Strategies:

• Increasing dependence on China for hardware, investment, and AI models.
• Use of third-party intermediaries (like Armenian companies) even for basic services (e.g., ChatGPT subscriptions).
  • “Even stuff like getting a simple subscription to ChatGPT is difficult because Visa, MasterCard and kind of Western payment methods are banned.”
    — Georgi Khonchev (08:32)
  • “Russian companies have to get a provider in Armenia to buy it for them…”
    — Georgi Khonchev (08:50)

3. The Stakes: What If Russia Doesn’t Catch Up?

(10:19 – 11:31)

National & Economic Implications:

• “Ultimately, we live in a time where obviously AI is transforming the economy and business and how everything is run. But it’s also important for various countries to have some form of control over their AI infrastructure, the models, the data… It’s a matter of state.”
  — Georgi Khonchev (10:24)
• Sovereignty is at risk: Without competitive AI, Russia is forced to be dependent on China and others for critical technology.
• Military vulnerability: The need for homegrown AI is underscored by its usage in current conflicts.

Conclusion:

• “Right now… Russia is not able to achieve [sovereignty] in the AI sphere for sure, and also in other parts of the economy, too.”
• Marked shift: “AI is becoming one of these sectors where Russia is, to some extent, totally dependent on outside models, hardware, and just outside help.”
  — Georgi Khonchev (11:15)

Notable Quotes & Timestamps

• Stephen Rosenbush (01:17):
  “The handful of companies that are seeing a really meaningful return, in many cases they’re using agents behind the scenes… for coding and customer service, or financial operations or supply chain management.”
• Stephen Rosenbush (03:23):
  “They’re able to reduce their time to market by as much as 18 weeks.”
• Stephen Rosenbush (04:28):
  “Leanne Russell at BNY made the point that developing agents wasn’t just hard, it was very, very hard.”
• Georgi Khonchev (06:58):
  “It’s really the Ukraine war that has set back the Russian kind of AI ambitions. Ultimately the Western sanctions… have just choked off Russia’s access to critical hardware.”
• Georgi Khonchev (09:52):
  "According to some estimates, 70, 80% [of top AI researchers] have left."
• Georgi Khonchev (10:24):
  “But it’s also important for various countries to have some form of control over their AI infrastructure, the models, the data, to avoid this dependence on other countries in military too… It’s a matter of state.”
• Georgi Khonchev (11:15):
  “AI is becoming one of these sectors where Russia is, to some extent, totally dependent on outside models, hardware, and just outside help.”

Segment Timestamps

• 00:18 – 05:19 | The promise and hurdles of AI agents in business; examples from BNY and Walmart.
• 06:23 – 10:19 | Russia’s decline in AI, causes (sanctions, brain drain, funding loss), dependence on China, and workaround strategies.
• 10:19 – 11:31 | The consequences for Russia of missing the AI wave—loss of sovereignty, military disadvantage, and technological dependency.