While most businesses are still arguing whether AI is real or overhyped, 91% of companies actually using it report massive revenue jumps. Search terms like “AI business automation” and “prompt engineering” keep shooting up, not because of FOMO, but because people are getting results. Look, you don’t need a PhD to win at this. You just need to learn from folks already doing it. These aren’t consultants selling dreams. They’re builders, investors, and operators who ship products daily. Some run platforms serving millions. Others invest in companies disrupting trillion-dollar industries. All of them share what they learn, often for free. If you’re automating anything, building AI products, or just want to stop feeling left behind in 2025, bookmark these ten people.
10 Leading AI Experts to Follow
1. Andrew Ng
Ng co-founded Coursera and basically taught half the internet how machine learning works. Through DeepLearning.AI, he’s trained millions of people who had zero background in AI. His course on prompt engineering with OpenAI’s Isa Fulford isn’t trendy, it’s practical. You learn to chain API calls together properly, evaluate what your prompts actually produce, and build systems that don’t randomly break. Lately he’s been talking about speed. Specifically, how fast AI-first teams can move compared to traditional software companies. That matters if you’re trying to compete against startups with three people doing what used to take fifty. Ng’s gift is translation. He takes concepts that sound impossible and makes them obvious. His free “Generative AI for Everyone” course connects technical ideas to business outcomes, which explains why companies building AI teams treat it like mandatory training.
2. Reid Hoffman
You probably know Hoffman from LinkedIn. Now he’s knee-deep in AI investing and experimentation. Earlier this year, he used Replit’s AI agent to clone LinkedIn with a single prompt. The result wasn’t production-ready, but it worked and proved his point about how fast prototyping has become. Hoffman’s take on AI and jobs feels refreshingly sane. He thinks AI augments work instead of destroying it, similar to how Excel changed accounting without eliminating accountants. Through his podcast, essays, and his board role at Inflection AI, he focuses on actual use cases instead of sci-fi scenarios. His “person-plus-AI” framework clicks for executives who want to integrate AI without panicking their entire workforce. If you’re a business leader stuck between excitement and fear, Hoffman gives you both permission to move forward and a map for doing it smartly.
3. Allie K. Miller
Miller ran machine learning at AWS and built it into a multi-billion-dollar business. Time Magazine put her on their list of the 100 most influential people in AI, and her nearly 2 million followers suggest people pay attention. Her clients include Salesforce, Coca-Cola, Novartis, OpenAI, and Anthropic, not exactly small accounts. What separates Miller from generic AI advisors? She’s lived through actual enterprise implementations. She knows AI doesn’t happen in a vacuum. You need engineering, marketing, sales, and operations all working together. Her frameworks tackle questions most advice skips: how to structure your AI team, where to actually hire, how to measure ROI beyond vague productivity claims. Through her firm Open Machine, she helps organizations become AI-first companies instead of companies dabbling in AI. If you’re past the pilot project phase and need to scale, Miller’s playbooks cut through the noise.
4. Cassie Kozyrkov
Kozyrkov was Google’s first Chief Decision Scientist. She trained over 20,000 Googlers and consulted on 500+ projects before launching Data Scientific. Her angle differs from most AI experts. She focuses on decision intelligence. Instead of obsessing over model accuracy, she asks whether you’ve framed the decision correctly. In an era where AI spits out answers instantly, her core insight matters: the value isn’t in AI’s response, it’s in asking the right question first. She advises Fortune 500 companies like Lenovo, NASA, and Gucci on using AI to enhance judgment instead of replacing it. For anyone working with prompts or building AI systems, her frameworks clarify when to automate, when to augment, and how to align AI decisions with actual organizational values. Kozyrkov prevents companies from efficiently building the wrong thing, which might be her most valuable skill.
5. Neil Patel
Patel runs a blog, YouTube channel, and podcast that reaches millions of marketers. He’s made a career out of making complex marketing tactics accessible to businesses without massive budgets. His stance on AI? It’s mandatory now, not optional. But the real ROI isn’t content generation, it’s smart automation. Patel hammers on data consolidation, predictive analytics, and dynamic decision-making as prerequisites. He warns constantly that siloed data kills every AI initiative, which resonates with marketing leaders tired of disconnected tools. Recently he’s been pushing people to optimize for conversational search platforms like Perplexity and ChatGPT Search, not just traditional Google. His frameworks help businesses adopt AI efficiently while dodging common mistakes that waste time and money. If you’re in marketing or sales and need practical AI guidance, Patel delivers it without the fluff.
6. Jeremy Howard
Howard’s fast.ai taught thousands of people machine learning without requiring a PhD in mathematics. Now through Answer.AI, his team of just 14 people ships breakthroughs that make enterprise leaders question what they’re doing with their 200-person AI divisions. Howard talks about “Dialog Engineering”, his term for iterative collaboration between humans and AI instead of one-shot prompting. This approach lets teams prototype and ship absurdly fast, which addresses the biggest question CTOs have: how do we actually build with this? His team’s work on efficient fine-tuning methods like FSDP and QLoRA, plus open-source tools like FastHTML, proves democratizing AI isn’t just idealistic. It creates competitive advantage. For organizations building AI products, Howard offers both philosophy and functioning tools you can use today.
7. Yann LeCun
LeCun is Meta’s Chief AI Scientist and won the Queen Elizabeth Prize for Engineering. He’s predicting the next phase: embodied and multimodal AI that interacts with the physical world through robotics, computer vision, and real-time decision-making. LeCun challenges the hype around current large language models. He points to their limitations in reasoning and physical interaction as the actual frontier worth watching. For enterprises and startups, his insights signal where capabilities are heading and where R&D investment pays off by 2030. His emphasis on agentic systems, ones that make autonomous decisions in changing environments, applies directly to business automation from supply chain robotics to autonomous customer service. Following LeCun helps you avoid dead-end investments and build for what’s actually coming instead of what’s popular today.
8. Paul Graham
Graham co-founded Y Combinator and his advice to founders increasingly centers on AI. His recent essays emphasize execution speed over secrecy, picking the right co-founder, and staying scrappy, especially when AI tools let small teams punch way above their weight. He’s observed that successful AI start-ups pick a specific market, deeply understand workflows, then use AI to augment human judgment. Graham pushes back hard against AI hype for its own sake, insisting founders solve genuine problems. For entrepreneurs building AI-first companies, Graham offers both psychological support through his “founder mode” essays and practical tactics for distribution. His Y Combinator network also connects founders to resources they need for scaling. Graham’s voice matters because he’s seen thousands of start-ups and knows what separates winners from wannabes.
9. Dharmesh Shah
Shah co-founded HubSpot and as CTO has built Agent.ai, an agentic AI platform that hit 1.1 million users by early 2025. HubSpot pioneered Model Context Protocol integrations connecting ChatGPT directly to CRM data and invested heavily in AI across sales, marketing, and customer success. Shah sold the os.ai domain to Perplexity, signalling his belief that a dedicated AI Operating System represents the next major shift. His perspective bridges enterprise infrastructure with cutting-edge AI applications. For business leaders evaluating platforms, Shah’s transparent communication about AI’s role in CRM and workflow automation provides critical signals about competitive advantage. His insights on integrating AI into existing business software without ripping everything out and starting over, show how enterprises can transform operations incrementally while still moving fast.
10. Isa Fulford
Fulford researches at OpenAI and co-teaches the ChatGPT Prompt Engineering for Developers course with Andrew Ng. She’s less visible than some other names on this list, but her direct involvement in OpenAI’s official prompt engineering curriculum makes her guidance uniquely credible. Her frameworks for evaluating prompt quality, handling different API use cases, and building production-ready AI systems reflect lessons from OpenAI’s customer base. For teams shipping real AI products, Fulford’s structured approach to prompt iteration, testing, evaluation, refinement, forms the foundation. She bridges academic rigor with engineering practicality, making sure teams don’t build fragile systems based on guesswork and hope. Her collaboration with Ng also shows she’s committed to democratizing best practices, which matters increasingly when the gap between theory and shipping determines winners.
Want To Explore Further?
These ten experts represent the cutting edge, but new voices emerge constantly. Staying current means tapping into curated resources beyond individual accounts. For comprehensive coverage, check out Feedspot’s specialized directories: AI in Business Podcasts, AI in Marketing Podcasts, AI and Machine Learning Influencers, Prompt Engineering Podcasts, Prompt Engineering Blogs, Artificial Intelligence Blogs in the US. These directories update continuously, surfacing emerging experts alongside established ones so you catch trend shifts and tool launches before they hit mainstream awareness.