About
I have spent my career on one idea: software that acts on our behalf.
In 1990 and 1991 I collaborated with Tim Berners-Lee at CERN on the very early concepts of the World Wide Web. At IBM Research in Tokyo I co-created Aglets, one of the first mobile-agent platforms, and co-wrote the book on programming it. As CTO of General Magic I was chief architect of OnStar. At Microsoft I architected the very first version of Bing Mobile Maps and built the machine learning platform for Microsoft’s data scientists. At Amazon I launched Amazon Machine Learning, one of the first machine learning services in the cloud. At Uber I led machine learning, including the Michelangelo platform. At Unity I led AI, from the ML-Agents toolkit to synthetic data for computer vision and robotics. At Google I led business intelligence and AI for Looker and shipped its first data agent.
Agents are now going into production, and the decisions that matter most sit with boards and CEOs: where AI creates value, what it should cost and how to govern it. That is my work today, as a board director, as an advisor to Goldman Sachs Asset Management and its portfolio companies, and through my firm, Agentimus.
Boards and advisory
Current roles
- Trifork Group AGNasdaq CopenhagenBoard member, since 2026
- ZeroNorthBoard member, since 2022
- ARoS Aarhus Art MuseumBoard member, since 2018
- Goldman Sachs Asset ManagementValue Accelerator Advisor, since 2025
- AgentimusAI strategy and advisoryFounder, since 2025
What I bring to a board
- AI strategy and governance
- Technology due diligence
- Data and machine learning platforms at global scale
- AI-driven operating change
- A transatlantic perspective, from board service in Denmark and an executive career in the United States
Career
2023–2024
Google
Vice President, Business Intelligence and AI (Looker)
Launched Conversational Analytics, Looker’s first data agent.
2016–2023
Unity Technologies
Senior Vice President, AI
ML-Agents toolkit, synthetic data for computer vision and robotics, and the partnership with DeepMind.
2015–2016
Uber
Head of Machine Learning
The Michelangelo platform and the models behind arrival-time prediction and dispatch.
2014–2015
Amazon
General Manager, Amazon Machine Learning
Launched Amazon ML, one of the first machine learning services in the cloud.
2005–2014
Microsoft
Large-scale machine learning and Bing
Architected the very first version of Bing Mobile Maps and built the machine learning platform for Microsoft’s data scientists.
2001–2005
Vocomo
Founder and CTO
Voice interfaces for cars.
1997–2001
General Magic
CTO
Chief architect of OnStar.
1993–1997
IBM Research, Tokyo
Co-created the Aglets mobile-agent platform.
1987–1993
Brüel & Kjær
Including collaboration with Tim Berners-Lee at CERN on the very early concepts of the World Wide Web (1990–1991).
Credentials
- Granted US patents
- 24
- Google Scholar citations
- 11,700+
- PhD in computer science, Technical University of Denmark (1994), and MS (1990)
- Co-author of Programming and Deploying Java Mobile Agents with Aglets (Addison-Wesley, 1998)
- “Seven Good Reasons for Mobile Agents,” Communications of the ACM (1999)
- “Unity: A General Platform for Intelligent Agents,” arXiv (2018)
Themes for writing and talks
The forty-year agent thread
What has changed since the mobile agents of the 1990s, what has not, and what that history says about where agentic AI goes next.
Agents need identities
An agent acting inside a company needs the controls an employee has: an identity, permissions tied to the data it may touch, and an audit trail.
Value sits in the harness
Foundation models are converging, and the returns go to the domain-specific software, data and workflows built around them.
Tokens are a labor cost
Budget and measure AI spend like the work it replaces: per task, and against the cost of the people who did that work before.
Bios and photo
Short bio
Danny Lange is a board director and AI advisor with four decades of experience building software agents and machine learning platforms at IBM Research, General Magic, Microsoft, Amazon, Uber, Unity and Google. He serves on the boards of Trifork Group, ZeroNorth and ARoS Aarhus Art Museum and advises Goldman Sachs Asset Management on AI. He holds a PhD in computer science from the Technical University of Denmark.
Board bio
Danny Lange is a technology executive and board director who has spent four decades building software agents and machine learning platforms. He advises boards and CEOs on where AI creates value, what it should cost and how to govern it.
He serves on the boards of Trifork Group AG (Nasdaq Copenhagen), the Copenhagen maritime technology company ZeroNorth, and ARoS Aarhus Art Museum. As a Value Accelerator Advisor to Goldman Sachs Asset Management, he works with portfolio company CEOs on AI strategy and operations and contributes to technology diligence on new investments. He also leads Agentimus, his AI strategy and advisory firm.
At Google he was Vice President of Business Intelligence and AI, responsible for Looker, where his team launched Conversational Analytics, Looker’s first data agent. At Unity Technologies he was Senior Vice President of AI, leading the ML-Agents toolkit and the company’s synthetic-data work for computer vision and robotics. As Head of Machine Learning at Uber he led the team behind Michelangelo, the company’s machine learning platform. At Amazon he was General Manager of Amazon Machine Learning, which he launched as one of the first machine learning services in the cloud. Earlier, he spent nine years at Microsoft, where he architected the very first version of Bing Mobile Maps and built the machine learning platform for Microsoft’s data scientists. He was CTO of General Magic and chief architect of OnStar, and at IBM Research in Tokyo he co-created the Aglets mobile-agent platform.
He brings boards experience in AI strategy and governance, technology due diligence, data and machine learning platforms at global scale, and AI-driven operating change, along with a transatlantic perspective from board service in Denmark and an executive career in the United States.
He holds a PhD and an MS in computer science from the Technical University of Denmark and is a named inventor on 24 granted US patents.
“In machine learning you need to think more like Werner Heisenberg than Isaac Newton.”