Best AI Podcasts to Follow in 2026

The number of AI podcasts more than doubled between early 2024 and late 2025. Every VC firm launched one, every research lab started putting out audio, and every tech journalist pivoted to covering AI full-time. The sheer volume makes finding signal almost harder than following no podcasts at all.

This list cuts through that noise. We tracked these shows across all of 2025 and into early 2026, paying attention to consistency, depth, and whether episodes actually changed how listeners think about AI — not just repeated what was already circulating on Twitter. Every show below earned its place through months of sustained quality. A single viral episode or a big-name host phoning it in does not get you on this list.

Pick three or four shows that match what you actually do. A researcher needs different pods than a startup founder. An engineer shipping AI features needs different pods than an investor evaluating AI deals. The recommendations below are organized so you can build a rotation that fits your week without the guilt of an ever-growing backlog.

The Must-Listen Tier

If you wiped your podcast app clean and started over, these five shows would go back in first. They cover research, business, engineering, and current events with almost no overlap between them.

Lex and Dwarkesh both do long-form interviews, but they scratch completely different itches. Lex gives guests three or four hours to fully unpack a worldview — you walk away understanding how someone thinks, not just what they believe. Dwarkesh runs tighter at 60 to 120 minutes with sharper, more confrontational questions that pull specifics out of guests who would rather stay vague. His audience expanded roughly 5x through 2025 as clips went viral across platforms.

Hard Fork and Latent Space are both weekly staples serving completely different layers. Hard Fork tells you what happened this week in AI. Latent Space tells you how to build with what happened this week. No Priors bridges the gap between investment thinking and technical reality, helping founders and engineers understand the business side without oversimplifying anything.

Research and Deep Dives

The papers, architectures, and breakthroughs driving everything else. If you want to understand the science underneath the headlines, these shows go where mainstream coverage cannot follow.

Lex Fridman Podcast remains the heavyweight for researcher interviews. His 2025 conversations with Dario Amodei (Anthropic) and Demis Hassabis (Google DeepMind) became landmark episodes that shaped public discourse around frontier model capabilities and alignment. His early 2026 sit-down with Andrej Karpathy on the state of open-source models drew millions of views across platforms. The long format is the whole point — guests explain nuance rather than delivering soundbites.

The Gradient Podcast fills the gap between arXiv papers and mainstream reporting. Hosted by ML researchers, episodes bring on paper authors to walk through methodology, explain what worked and what failed, and why specific results matter. When a paper drops and everyone is arguing about the abstract on social media, The Gradient gives you the full story. This kind of depth is hard to replicate in written form — if you follow the broader AI trends shaping 2026, The Gradient helps you understand the research behind them.

Machine Learning Street Talk is the most technically rigorous AI podcast running right now. Tim Scarfe and rotating co-hosts tackle mechanistic interpretability, scaling laws, alignment research, and reasoning model internals with a precision most shows avoid. Their 2025 series on chain-of-thought faithfulness was months ahead of mainstream coverage. Not for casual listening — but nothing else matches the depth.

Dwarkesh Podcast bridges technical research and civilizational-scale thinking. His 2024 Ilya Sutskever interview remains one of the most-discussed AI podcast episodes ever recorded. His 2025 conversations on compute scaling economics and training run cost curves helped frame how the entire industry thinks about next-generation models.

Business, Startups, and Investing

AI is reshaping entire industries, and these podcasts track the money side — who is raising, which business models survive contact with real customers, and where the market is heading versus where the hype says it is. For a broader view of the companies behind these stories, our AI companies landscape maps out who is who across the ecosystem.

Acquired by Ben Gilbert and David Rosenthal has become one of the biggest podcasts in tech, full stop. Their multi-hour company deep dives function as free MBA-level case studies. The 2025 NVIDIA episode — over four hours — traced the entire GPU supply chain and explained why Jensen Huang's decade-long bet on AI compute created a $3 trillion company. Their early 2026 episodes on Anthropic and AI infrastructure buildout are essential listening for understanding the capital dynamics driving this wave. Acquired reportedly crossed 500,000 downloads per episode through 2025, making it one of the fastest-growing business podcasts anywhere.

All-In Podcast features Chamath Palihapitiya, Jason Calacanis, David Sacks, and David Friedberg hashing out the week's biggest stories. The chemistry is genuinely entertaining, and the insider perspectives on deals, regulation, and market dynamics are hard to get elsewhere. AI coverage sharpened through 2025 as Sacks took on a higher-profile role in tech policy and Chamath pushed harder on AI's labor market impact. Weekly downloads reportedly exceed one million.

a16z Podcast delivers the Andreessen Horowitz perspective on where AI is heading. Episodes on AI infrastructure, developer tooling, and the application layer reflect billions of dollars in investment thesis. Worth listening to even when you disagree — understanding what the largest dedicated AI fund believes shapes the market whether their bets land or not.

No Priors zeroes in on AI startups specifically. Sarah Guo (Conviction) and Elad Gil consistently bring on founders building real businesses, not demo products. Their episodes on AI-native SaaS, vertical AI applications, and the unit economics of inference helped frame how AI startup funding actually works beyond the headline-grabbing mega-rounds.

Engineering and Practical AI

Building with AI is a fundamentally different skill from reading about it. These podcasts speak directly to developers, ML engineers, and product builders who are getting AI features into production.

Latent Space leads this category by a wide margin. Swyx and Alessio Fanelli built a thriving community around AI engineering, and their episodes reflect the problems practitioners face daily — prompt engineering at scale, evaluation frameworks, fine-tuning versus RAG tradeoffs, getting agents to work reliably outside of demos. Their 2025 coverage of the shift from monolithic LLM calls to compound AI systems proved prescient as the rest of the industry caught up to that framing in early 2026. If you build software that touches language models, this belongs in your weekly rotation. Their agent-focused episodes pair well with our roundup of the best AI tools by category reshaping development workflows.

Changelog — Practical AI focuses on the infrastructure side of machine learning. Episodes cover MLOps, model deployment, data pipelines, monitoring, and the unglamorous but critical work of keeping AI systems running at scale. Their 2025 episodes on LLM observability tooling and the emerging evaluation stack were strong enough that teams referenced specific episodes in internal planning docs.

The TWIML AI Podcast (This Week in Machine Learning & AI) hosted by Sam Charrington has been running since 2016 and stays relevant by grounding every episode in real-world applications. Production case studies from companies deploying AI at scale make this one of the most practical shows available. The 2025 series on enterprise RAG deployments — including the failure modes nobody discusses publicly — was unusually candid.

News and Weekly Analysis

Staying current without drowning in noise. These shows distill the week so you can skip the endless social media threads and newsletter overload.

Hard Fork from the New York Times is the best weekly AI news podcast running right now. Kevin Roose and Casey Newton pair real investigative journalism with accessible, entertaining delivery. Through 2025 they covered AI-generated content flooding search results, workplace AI adoption struggles, the EU AI Act's first enforcement actions, and the ongoing regulatory battles in Washington. Their download numbers reportedly passed several legacy tech podcasts through the year, making Hard Fork the default answer when someone asks "what single show should I follow for AI news?"

The Vergecast covers broader tech but increasingly devotes full segments to AI. Nilay Patel, David Pierce, and Alex Cranz bring a consumer-first lens that balances the enterprise and research bias of most AI shows. Their coverage of AI features rolling into everyday devices — Apple Intelligence updates, Google's Gemini integration across Android, Microsoft Copilot's expansion into Windows and Office — fills a gap other podcasts ignore entirely.

Decoder with Nilay Patel goes deep on single topics: AI regulation, chip export controls, the economics of training runs, copyright lawsuits. Guests are the decision-makers themselves, not commentators reacting to decisions. The 2025 episodes on NVIDIA export restrictions and the first wave of AI Act compliance challenges were standout policy coverage.

If episode volume across these shows overwhelms you, our guide comparing podcast summaries, newsletters, and YouTube can help you figure out which format works best for different types of content. And if you want to pair audio with written sources, the best AI newsletters covers the strongest options for 2026.

Safety, Ethics, and Policy

AI governance moved from theoretical debate to enforcement reality in 2025. The EU AI Act started applying to high-risk systems, the US issued a series of executive orders on AI safety, and multiple lawsuits over training data reached courtrooms. These podcasts cover the regulatory and ethical dimension that pure tech shows tend to skim over.

The AI Policy Podcast from the Center for a New American Security brings policy analysts and government officials into conversation with technologists. Episodes break down specific regulatory proposals, export control updates, and international AI governance frameworks with a level of detail that news shows cannot match. Their 2025 coverage of the US-China chip export restrictions and the EU AI Act's risk classification system was some of the most thorough analysis available in any format.

Your Undivided Attention from the Center for Humane Technology, hosted by Tristan Harris and Aza Raskin, tackles AI's societal impact head-on. Their framing of AI risks resonated broadly through 2025 — the show pulled in guests from national security, public health, and education alongside the usual tech figures. Episodes on deepfake proliferation and AI-generated misinformation during election cycles were widely shared beyond the typical podcast audience.

80,000 Hours Podcast hosted by Rob Wiblin regularly features AI safety researchers from organizations like the Alignment Research Center, Redwood Research, and Anthropic's safety team. These episodes go substantially deeper than surface-level "AI risk" conversations, exploring specific technical alignment challenges and career paths for people who want to work on making AI go well. The 2025 series on governance careers at frontier AI labs drew significant interest from early-career researchers.

How to Actually Keep Up

Nobody has time for all of these. A realistic system you stick with for six months beats an ambitious one that falls apart after two weeks.

Pick Your Core Three

Choose one show from each category that matches your day-to-day work. Subscribe to those and commit to listening weekly. Everything else goes in a "check when interesting" bucket where you scan for standout episodes based on guest or topic.

• Research-focused? Lex Fridman + The Gradient + Dwarkesh
• Founder or investor? Acquired + No Priors + All-In
• Engineer shipping AI? Latent Space + Practical AI + Hard Fork
• Generalist staying informed? Hard Fork + Dwarkesh + No Priors
• Safety and policy? 80,000 Hours + AI Policy Podcast + Decoder

Best Podcast Apps for AI Shows

Speed and Queue Tips

• 1.5x speed works well for conversational shows. Drop back to 1x for technical episodes discussing code, math, or architecture details.
• Skip intros — most apps support custom skip buttons. A 30-60 second forward skip clears the sponsorship read on nearly every show.
• Ruthless queue hygiene matters more than anything else. If an episode sits untouched for two weeks, delete it. You are not going back, and the backlog guilt makes you less likely to play the fresh episodes that actually matter.
• Pair audio with written summaries when time is tight. Listen fully to your core three and use podcast summaries for the rest. This keeps you aware of important episodes across shows without falling behind on the ones you care most about.

What Changed in the AI Podcast Landscape Through 2025

The past year reshaped how people consume AI audio content in several concrete ways:

• Dwarkesh Podcast grew from a niche interview show into one of the most-cited sources in serious AI discourse. His audience expanded roughly 5x through 2025, fueled by clips going viral across Twitter and YouTube.
• Hard Fork became the consensus first recommendation for anyone asking "how do I follow AI news?" — reportedly surpassing several long-running tech podcasts in weekly downloads by mid-2025.
• Video-first consumption accelerated. Lex Fridman, Dwarkesh, and All-In all saw higher viewership on YouTube than through traditional podcast apps. This pushed other shows to invest in video production and multi-format distribution.
• AI-generated podcast summaries became a real product category. Tools that condense two-hour episodes into structured five-minute reads changed how busy listeners triage their queues. You can compare the best options in our podcast summary tools guide.
• Niche vertical AI podcasts emerged for healthcare, legal tech, education, and financial services — a clear signal that AI discourse has matured past the general tech audience phase into domain-specific content.
• Listener fatigue hit surface-level shows hard. The podcasts that survived were the ones offering analysis you genuinely could not find in a newsletter or tweet thread. Shows that just recapped headlines lost audience to faster text formats and AI-generated summaries.
• Community-driven shows gained ground. Podcasts with active Discord servers, subscriber-only content, and live events — Latent Space and All-In being prime examples — built stronger retention than shows relying purely on passive consumption. The AI podcast audience proved willing to pay for access and community when the quality justified it.

More AI Podcast Resources

• Best AI News Podcasts — Weekly shows covering breaking AI stories
• Best AI Podcasts for Developers — Technical podcasts for engineers building with AI
• Best AI Startup Podcasts — Shows focused on AI founders and venture funding
• AI Podcast Summaries — Tools for triaging your listening queue
• AI Newsletters — Pair your podcast rotation with the best written sources
• AI Learning Resources 2026 — Courses, books, and communities beyond podcasts
• AI Trends 2026 — The broader context behind what these shows cover

Last updated: March 2026