# ✨ AI and the future of R&D: My chat (+transcript) with McKinsey's Michael Chui Page: https://stenobird.com/podcast/faster-please-the-podcast-5630783/ai-and-the-future-of-r-d-my-chat-transcript-with-mckinsey-s-michael-chui Text version: https://stenobird.com/podcast/faster-please-the-podcast-5630783/ai-and-the-future-of-r-d-my-chat-transcript-with-mckinsey-s-michael-chui.md Podcast: [Faster, Please! — The Podcast](https://stenobird.com/podcast/faster-please-the-podcast-5630783) Published: 2025-07-31T14:43:44+00:00 Episode link: https://fasterplease.substack.com/p/ai-and-the-future-of-r-and-d-my-chat Audio file: https://api.substack.com/feed/podcast/169696229/973fdbea0f4bb4f0ff0972ad550224a0.mp3 Processing state: not_requested JSON: https://stenobird.com/v1/public/podcasts/faster-please-the-podcast-5630783/episodes/ai-and-the-future-of-r-d-my-chat-transcript-with-mckinsey-s-michael-chui Duration seconds: 1390 ## Resource My fellow pro-growth/progress/abundance Up Wingers, The innovation landscape is facing a difficult paradox: Even as R&D investment has increased, productivity per dollar invested is in decline. In his recent co-authored paper , The next innovation revolution—powered by AI , Michael Chui explores AI as a possible solution to this dilemma. Today on Faster, Please! — The Podcast , Chui and I explore the vast potential for AI-augmented research and the challenges and opportunities that come with applying it to the real-world. Chui is a senior fellow at QuantumBlack, McKinsey’s AI unit, where he leads McKinsey research in AI, automation, and the future of work. In This Episode * The R&D productivity problem (01:21) * The AI solution (6:13) * The business-adoption bottleneck (11:55) * The man-machine team (18:06) * Are we ready? (19:33) Below is a lightly edited transcript of our conversation. The R&D productivity problem (01:21) All the easy stuff, we already figured out. So the low-hanging fruit has been picked, things are getting harder and harder. Pethokoukis: Do we understand what explains this phenomenon where we seem to be doing lots of science, and we're spending lots of money on R&D, but the actual productivity of that R&D is declining? Do we have a good explanation for that? I don't know if we have just one good explanation. The folks that we both know have been both working on what are the causes of this, as well as what are some of the potential solutions, but I think it's a bit of a hidden problem. I don't think everyone understands that there are a set of people who have looked at this — quite notably Nick Bloom at Stanford who published this somewhat famous paper that some people are familiar with. But it is surprising in some sense. At one… ## Actions - request_transcript: `POST https://stenobird.com/v1/public/podcasts/faster-please-the-podcast-5630783/episodes/ai-and-the-future-of-r-d-my-chat-transcript-with-mckinsey-s-michael-chui/transcription-requests` — Idempotently request low-priority transcript generation for this episode. - read_markdown: `GET https://stenobird.com/podcast/faster-please-the-podcast-5630783/ai-and-the-future-of-r-d-my-chat-transcript-with-mckinsey-s-michael-chui.md` — Read the agent-friendly Markdown representation of this episode resource. A page view does not enqueue transcription. Agents should invoke `request_transcript` explicitly when they need this episode processed. ## Transcript Full transcripts are not published on public pages unless there is a clear rights basis.