Attribution & Disclaimer:
This post summarizes information from the report “Trends – Artificial Intelligence” authored by Mary Meeker, Jay Simons, Daegwon Chae, and Alexander Krey and published by BOND in May 2025. –
[Source – https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf]
All original research, visuals, and analysis are entirely the intellectual property of the authors and BOND.
This blog post is a brief summary shared solely for informational and educational purposes. For full details and proper context, please refer to the official report. All original content, data, and insights belong to the authors of the report. This is a summary for informational purposes only.
Intro:
Artificial intelligence is no longer an emerging trend—it’s redefining how we work, compute, invest, and compete globally.
According to “Trends – Artificial Intelligence” by Mary Meeker, Jay Simons, Daegwon Chae, and Alexander Krey at BOND (May 2025)
[Source – https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf], we are experiencing the fastest, most widespread technology adoption in history.
Note: All key insights and data referenced in this article are derived from the original work of the report’s authors and are credited fully to them.
Here’s a synthesized breakdown of the AI transformation underway, with proper attribution to the original authors and sources.
1. AI Adoption: Growth the World Has Never Seen
“AI user and usage trending is ramping materially faster… and the machines can outpace us.”
— Trends – Artificial Intelligence, BOND (2025)
According to BOND’s report:
- ChatGPT reached 1M users in just 5 days and grew to 800 million weekly users in under 18 months (p. 55).
- In comparison, it took the internet 23 years to reach 90% of global user penetration—ChatGPT did it in 3 years.
- The adoption of generative AI spans over 5.5 billion connected citizens, fueling user base and App usage dramatically.
This surge is not localized—it’s simultaneous and worldwide, disrupting the previous pace of the Internet’s rise.
2. AI Infrastructure: CapEx Boom Among the Tech “Big Six”
Massive capital flows are funding AI—from hyperscale infrastructure to silicon:
- Big Six Tech companies (Apple, Microsoft, Google, Meta, Amazon, Nvidia) increased CapEx by 63% YoY in 2024, reaching $212 billion (p. 97).
- GPU infrastructure from Nvidia alone supports a staggering 6 million developers as of 2025 (p. 38).
- Investment focus has shifted from storage and access to raw compute and massive inference capabilities.
This is evidenced by AI data centers, dubbed “AI factories” by Nvidia CEO Jensen Huang (p. 125), including xAI’s Colossus, which scaled to 200,000 GPUs in just 7 months (p. 123).
3. AI Economics: Soaring Costs vs. Falling Prices
- Training costs for frontier models have grown ~2,400x since 2016, now reaching up to $1B per model (p. 132).
- But cost-per-token inference fell 99.7% in just two years, thanks to breakthroughs in model efficiency and Nvidia’s Blackwell GPUs (p. 137 & 136).
- This divergence enables a “performance convergence” where cheaper, smaller models now compete with frontier systems on many real-world tasks (pp. 134–145).
This paradox—rising training cost, falling inference cost—is fueling unprecedented developer adoption while challenging LLM business models.
4. AI Developers: A Global Explosion of Talent and Innovation
- Developer growth in AI ecosystems is exponential:
- +6x growth in developers for Nvidia (to 6 million) (p. 38).
- +5x in Google’s Gemini developers (to 7 million) year-over-year (p. 39).
- GitHub AI repositories with 500+ stars increased 175% in just 16 months (p. 148).
- Developers aren’t just fine-tuning models—they’re creating modular stacks, tools, and apps at internet-era speed, thanks to plummeting inference costs (p. 144-145).
Result: The barrier to entry for AI development is collapsing, driving a wave of creativity, open-source tools, and commercial experimentation.
5. Geopolitical Race: USA, China, and the Open-Source Offensive
“AI leadership could beget geopolitical leadership.”
— Andrew Bosworth, Meta CTO (p. 8)
The report cites a strategic AI showdown:
- China’s model ecosystem is rapidly catching up in usage and reach (p. 293).
- Open-source LLMs (e.g., Meta’s Llama 3 and Alibaba’s Qwen 2.5) are undercutting proprietary models—as seen in competitive benchmarks and developer uptake (p. 29).
- The USA’s Big Six are aggressively investing to maintain control over infrastructure, while sovereign AI is rising globally (p. 77).
In short: AI is both a technology and a diplomacy tool, redrawing competitive lines between nations and ecosystems.
6. AI and the Workforce: Real and Rapid Evolution
- AI-related IT jobs in the U.S. rose +448% since 2018, while non-AI tech jobs fell -9% (p. 8).
- Tools like ambient AI scribes at Kaiser Permanente and agents in Salesforce’s Agentforce are actively reshaping operations, not just augmenting them (pp. 73, 91).
- In 2025, 72% of U.S. workers using AI chatbots say the tools improved their speed and work quality (p. 85).
AI is transitioning from assistant to agent—executing workflows, not just suggesting responses (p. 89).
7. From Models to Monetization: Chips, Clouds, and Agents
AI’s monetization model is increasingly clear:
- Nvidia’s revenue is up 28x in 10 years (p. 161); it commands 25% of all global data center CapEx (p. 109).
- Amazon Trainium and Google TPUs are scaling fast, aiming to reduce GPU dependency and cut cloud inference costs (pp. 162–163).
- Compute services like CoreWeave (+730%) and Oracle AI infrastructure (+50x) represent a second monetization layer (pp. 165–166).
Agent-based ecosystems—from OpenAI’s Operator to Anthropic’s Claude 3.5 integrations—are also shifting from reactive chat to action-driven execution (p. 91). This is core to the next wave of monetization.
8. AI Compounds Like Nothing Else Before
The report argues AI reflects the same compound acceleration seen in:
- Electricity (1800s)
- Internet (~1990s)
- But AI is steeper and faster — data multiplied, compute grew 360%/year, and performance leapt >100x on many benchmarks in just five years (pp. 14–17, 106).
AI sits at the intersection of cost collapse, performance surge, and mass adoption.
Final Thought: The Case for Optimism (and Caution)
This BOND report doesn’t ignore risk—it underscores how AI’s capital intensity, geopolitical stakes, and speed of deployment demand mature governance. But the potential upside remains extraordinary if leaders, developers, and industries adapt effectively.
“Statistically speaking, the world doesn’t end that often.”
— Brian Rogers, quoted on p. 8
Ultimately, AI is a flywheel—powered by more data, more compute, and more usage. The next big question? Who captures the value at each layer—model, infrastructure, agent—and how we govern that value globally.
Report Credited To:
“Trends – Artificial Intelligence”
Authors: Mary Meeker, Jay Simons, Daegwon Chae, Alexander Krey
Source: BOND (May 2025)
[Primary Source:Link to the report – https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf ]
Use Note: This blog post synthesizes and summarizes publicly available content from the referenced report with attributions. For the full original, please refer to the report directly via BOND or authorized publication channels.
[Note – Growthx has a video that has summarized this article of the original author, here is the link – https://www.youtube.com/watch?v=5YzUDP3JQ9A ]
Note on Attribution:
This blog post summarizes key points and insights from the publication “Trends – Artificial Intelligence,” authored by Mary Meeker, Jay Simons, Daegwon Chae, and Alexander Krey, and published by BOND in May 2025.
All original research, data, charts, and terms (including “AI factories,” “AI agent evolution,” and “knowledge distribution evolution”) are the intellectual property of the respective authors and respective companies.
Our goal is to respectfully synthesize the report’s publicly shared findings for educational and discussion purposes. We encourage readers to consult the full report for deeper analysis and context.
Citation:
BOND (2025). “Trends – Artificial Intelligence.” Mary Meeker, Jay Simons, Daegwon Chae, Alexander Krey. May 2025.
https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf
Disclaimer:
All information in this blog post is a summarized interpretation of the report “Trends – Artificial Intelligence” authored by Mary Meeker, Jay Simons, Daegwon Chae, and Alexander Krey, published by BOND in May 2025. All original insights, data, and analysis belong entirely to the authors and BOND. This summary is intended for informational and educational purposes only
