30 Charts that will help you navigate the AI Transformation
My takeaways from the latest 340-page report by Mary Meeker.
Previously on Open Road Ventures: in the last episode of Venturing Insights, we explored the main insights from the latest episode of The Corporate Venturing Podcast with JLR’s InMotion Ventures. If you missed it, you can catch up here!
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Mary Meeker is often called the “Queen of the Internet” for a reason. Her team’s annual reports are long, sharp, and full of signals.
This year’s BOND report is 340 pages. I read it so you don’t have to.
My selection of these 30 charts show what’s happening in AI now: how companies use it, where money is going, and what leaders want from it.
TL;DR
↳ AI's rapid global spread, much faster than past technologies.
↳ Big companies' shift to AI for growth and revenue, not just cost savings.
↳ Fierce AI competition reshaping technology, business, and global power.
↳ The rise of AI agents that can reason and complete complex tasks.
↳ AI's rapid transformation of how we work.
What the data shows
You’ll find the full chart selection available to download at the end of this post.
1. AI adoption is global and fast.
It took the internet 23 years to reach 90% of global users (outside North America). ChatGPT did it in 3.
2. Big Tech talks AI — a lot.
Mentions of “AI” in earnings calls are rising. These firms now need to show results, not just intentions.
3. Growth > savings.
Companies use AI to grow revenue and improve customer impact, not to cut jobs or reduce cost.
4. People already find AI useful.
72% of working adults in the U.S. say AI tools help them work better and faster.
5. AI is becoming hard to spot.
In Q1 2025, 73% of testers mistook AI answers for human ones.
6. Drug discovery is speeding up.
AI reduces R&D timelines by 30% to 80%, compressing years into months.
7. Private sector leads in research.
Since 2015, companies have outpaced academia in training top ML models.
8. Training data is exploding.
Model datasets are growing 260% per year — for 15 years straight.
9. CapEx intensity is rising.
U.S. tech giants now spend 15% of revenue on infrastructure — nearly double the rate of a decade ago.
10. NVIDIA is a key platform.
From 2021 to now: +3.9x AI startups, +2.4x developers, +2.4x GPU-enabled apps.
11. Data centers go up fast.
xAI built a working data center in 122 days — faster than building a U.S. house.
12. They also use lots of power.
Energy demand from AI infrastructure is a growing concern.
13. Inference costs are collapsing.
Serving LLMs is now 99.7% cheaper per million tokens than two years ago.
14. AI efficiency is outpacing past tech.
The cost of generating 75-word GenAI outputs is falling faster than Moore’s Law-era gains.
15. Few control the stack.
Only a small number of players dominate model development, infrastructure, and cloud.
16. The LLM model is shifting.
Training remains expensive. Inference is cheap. Smaller, task-specific models are gaining ground.
17. People spend more time with AI.
ChatGPT saw +106% in daily usage and +47% in session length over 21 months.
18. Big platforms hold the keys.
OpenAI has 800M users — but Microsoft, Apple, Google, and Meta can reach billions.
19. Software may follow hardware.
Just as the iPhone redefined devices, Office could become the next all-in-one AI suite.
20. Vertical software is a growing space.
There’s demand for tailored AI solutions across fragmented markets.
21. AI is moving into new industries.
Next up: precision manufacturing, robotics, drug development, and autonomous finance.
22. Multimodal is here.
Models that handle text, images, audio, and video are up 1,150% in two years.
23. Agents are the next layer.
AI agents don’t just answer — they act, reason, and complete complex tasks for users.
24. Open-source is catching up.
Closed models still lead in UX and raw power, but open models are cheaper, better, and more accessible.
25. China leads in physical AI.
It has more industrial robots installed than the rest of the world combined.
26. Robotaxis are real.
Waymo runs a fully autonomous ride-hailing service in San Francisco — at scale.
27. U.S. and China lead the model race.
They dominate in launching new LLMs. The EU is far behind.
28. AI helps people, not replaces them.
Top enterprise priorities: better CX and internal efficiency — not layoffs.
29. AI is creating jobs.
Job titles with “AI” are up 200% in two years. New roles are emerging.
30. The AI story is just beginning.
This wave will reshape not just software, but how companies operate and create value.
👇🏻 Download the full 30 charts below (PDF)
Each chart has a short caption to help you see what matters and what’s likely noise.
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