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Top AI Leaders you need to be following in 2025

Meet the top AI leaders to follow in 2025. Stay updated on the latest in AI with insights, trends, and breakthroughs from the visionaries shaping the future of tech.

Rose McMillan · November 1, 2024
Top AI Leaders you need to be following in 2025Top AI Leaders you need to be following in 2025

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Everyone is talking about AI, it's one of the biggest technological advancements of the last decade. AI technologies are constantly evolving to reach new levels of sophistication and new AI tools are frequently being released. These advancements are being led by a handful of AI leaders and tech giants making significant contributions to data and AI solutions.

Collectively they have made major impacts in their fields and have been nominated or won major awards including Time's 100 Most Influential People and MIT Technology Review's Innovators Under 35. As we close out the year we thought it was time to acknowledge the impact these AI leaders have had on this growing and developing technology and consider the advancements they'll continue to make in 2025 and beyond.

Kate Crawford

A photo of Kate Crawford

Over the last 20 years, Kate Crawford has established herself as an industry thought leader through her renowned work as a scholar and researcher. She currently works as a Research Professor at USC and a Senior Principle Researcher at Microsoft.

She has authored multiple influential books including "Atlas of AI" and "Tech's Bias Problem" exploring the potential biases and inequalities in AI technology. In 2017, Crawford cofounded the AI Now Institute alongside Meredith Whittaker, a female organization that produces diagnosis and policy research on artificial intelligence and advises policymakers on ethical AI practices. Her work has shaped debates on AI system regulation and influenced the development of ethical guidelines and standards, including the EU’s AI Act.

Dr Andrew Ng

photo of Dr Andrew Ng at a talk

Dr Ng is a world computer scientist and entrepreneur making significant contributions to the ethical advancements of AI systems. His innovative use of AI has driven significant business growth in the organizations he’s been part of. He has co-authored over 200 research papers in machine learning, robotics, and data analytics, contributing to the ethical advancements of AI systems. As the co-founder of the Google Brain project, a research team dedicated to developing deep learning algorithms, he was a driving force in the growth of Baidu’s AI group.

Ng is passionate about making AI accessible and co-founded Coursera and his own platform, DeepLearning.AI to offer free, open source courses that have dedicated millions. He also founded Landing AI, a company focused on developing AI-powered SaaS products and launched the AI Fund to invest in promising AI startups and drive innovation in the field. He also works closely with industry leaders to develop ethical and responsible AI practices and advises government agencies on issues related to AI and national security.

Meredith Whittaker

photo of Meredith Whittaker

Meredith Whittaker is one of the top AI leaders due to her research and advocacy on the social implications of artificial intelligence and the tech industry behind it. She focuses on power and political economy driving the commercialization of computer technology. She is also the current President of Signal, a communications app much like WhatsApp only much much safer and more private, as well as a co-founder and Chief Advisor of the AI Now Institute.

She previously worked at Google for over a decade and led product and engineering teams. She founded Google's Open Research Group and co-founded M-Lab a global distributed network measurement platform that provides the world's largest source of open data on internet performance. She has worked to support government and civil society organizations on artificial intelligence and internet policy, including the White House, the FCC, and the FTC.

Alex Smola

photo of Alex Smola

Alex Smola is the co-founder and CEO of Boson.ai, an AI company building personalized experiences in a virtual world. As a former profession at Carnegie Mellon University and the current Vice President and Distinguished Scientist for Machine Learning at Amazon Web Services since 2016, he develops advanced tools for data scientists focusing on computer vision, deep learning, and natural language processing. His work at Amazon Web Services has been pivotal in driving digital transformation through advanced AI tools and services.

As a leading expert in machine learning, his research spans deep learning algorithms, kernel methods, and statistical modeling focusing on building scalable and efficient models for large systems. His work has made a significant impact on areas like user modeling, document analysis, and drug discovery. As a distinguished data scientist, he has pushed the boundaries of AI technologies developing innovative tools to analyze vast datasets. His work has led to his recognition as one of MIT Technology Review’s Innovators under 35.

Dr Fei-Fei Li

photo of Dr Fei-Fei Li

Dr. Fei-Fei Li is a leading figure in the world of AI. She's made major contributions to machine learning, computer vision, and natural language processing, cementing position as a leading figure in the world of AI. She co-founded and led the ImageNet project, a large labeled image dataset that has transformed deep learning and image recognition, driving breakthroughs in AI technology. Her work in developing algorithms to accurately identify objects and scenes in complex environments has been foundational in modern computer vision.

As a strong advocate for AI democratization, Dr. Li co-founded AI4ALL in 2017. The organization works to promote diversity and inclusion in AI. She also co-directs the Stanford Institute for Human-Centered AI and the Stanford Vision and Learning Lab, two organizations dedicated to fostering human-focused AI research. Outside of her work as a research scientist, Dr Li frequently conducts talks and writes papers in hopes of inspiring the next generation of scientists.

Rana el Kaliouby

Rana el Kaliouby

Dr. el Kaliouby is a highly respected computer scientist and entrepreneur in the field of artificial emotional intelligence. She is best known for her work developing technology capable of recognizing and responding to human emotions through facial expressions, voice, and non-verbal cues. She aspires to humanize technology and enable machines to understand and interact with humans on an empathetic level.

In 2009, Dr el Kaliouby co-founded Affectiva, a company affiliated with MIT's Media Lab where she conducted a lot of her early research. As a leader in the development of "emotion AI" and "affective computing", Affectiva has applications in various fields including marketing, healthcare, and even automotive industries by improving driver safety through emotion detection. As a strong advocate for ethical AI and diversity in tech, Dr. el Kaliouby frequently conducts public talks about the importance of female and minority representation in STEM fields. She also wrote a memoir titled "Girl Decoded" that explores her personal journey and vision for human-centric AI.

Ian Goodfellow

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Ian Goodfellow is a prominent figure in the field of artificial intelligence, particularly known for his contributions to deep learning and the invention of generative adversarial networks (GANs). His work on GANs has played a crucial part in enabling AI to create realistic images, videos, and other types of data, with applications spanning from video game development to medical imaging. Goodfellow is deeply passionate about making AI more accessible to all and is an advocate for open-source software and data, working to provide tools and resources that facilitate the development and deployment of AI systems.

Outside of his work as a research scientist, Goodfellow is very active in driving AI policy and industry initiatives. He's collaborated with industry leaders and government agencies to promote ethical and responsible AI practices as well as advising on issues like national security. His work has significantly influenced public policy and industry standards, promoting more responsible and ethical approaches to AI development and implementation.

Ruslan Salakhutdinov

a man in a blue shirt is smiling for the camera .

Salakhutdinov is the current Vice President of Generative AI Research at Meta and a UPMC Professor of Computer Science at Carnegie Mellon University (CMU). He previously worked as the Director of AI Research at Apple for over three years, where he played a considerable role in advancing AI technologies within the company.

Salakhutdinov is a leading figure in artificial intelligence and machine learning, known for his contributions to deep learning. His work has been instrumental in developing neural networks, unsupervised learning techniques, and probabilistic models, with applications in natural language processing, computer vision, and reinforcement learning.

Throughout his career, Salakhutdinov has focused on improving AI's ability to learn from complex, unstructured data, which has significantly impacted the development of more robust and capable AI systems. His extensive research and leadership have earned him a strong reputation as a notable AI leader, and his contributions have shaped both academic research and industrial applications in AI. He has also been named one of MIT Technology Review's Innovators Under 35.

Jeremy Howard

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Jeremy Howard is a prominent Australian data scientist and entrepreneur, well-known for his contributions to the field of machine learning and artificial intelligence. He is the co-founder and former CEO of Fast.ai, an organization dedicated to making deep learning more accessible through education and open-source software. Fast.ai is particularly recognized for its practical deep-learning courses, which have educated thousands of students and professionals globally.

Howard has a strong academic background, having worked as a lecturer at the University of San Francisco and is a founding member of the Kaggle, the world's largest AI and machine learning community, where he has won numerous data science competitions. His expertise spans various areas within AI and machine learning, including computer vision and natural language processing. Howard has worked to emphasize the importance of practical applications of machine learning, focusing on how AI can solve real-world problems in diverse fields, including healthcare, education, and business. His efforts to bridge the gap between advanced AI techniques and practical usage have made remarkable impacts on the data science community.

Kai-Fu Lee

A photo of Kai-Fu Lee

Kai-Fu Lee is a prominent leader in the field of artificial intelligence, playing a pivotal role in the advancement and implementation of AI technologies around the world. He is the current CEO of 01.AI and has made significant contributions to speech recognition and natural language processing. He was a key team member who developed the first continuous speech recognition system for Mandarin, marking a major breakthrough in natural language processing at that time. His contributions have also been essential to the evolution of intelligent virtual assistants, chatbots, and other AI systems that facilitate human-computer interaction.

Lee is a strong advocate for the advancement of AI technologies, founding Sinovation Ventures, a venture capital firm focused on investing in AI startups. Lee emphasizes the importance of ethical and responsible AI deployment, advocating for greater transparency and oversight in creating and applying AI systems. He has worked closely with organizations to develop AI policies and industry initiatives, serving as an advisor to the Chinese government. Through these efforts, he aims to establish ethical practices within the AI sector and has already considerably influenced public policy and industry standards, contributing to the establishment of more responsible approaches to AI development and implementation.

Mustafa Suleyman

photo of Mustafa Suleyman

Mustafa Suleyman is a British entrepreneur, computer scientist, and a key figure in shaping the field of artificial intelligence. He is best known as the co-founder of DeepMind, an AI research lab renowned for its groundbreaking systems and algorithms that advance reinforcement learning and general intelligence. Here, Suleyman led teams responsible for deploying advanced AI systems across various Google products and external sectors, showcasing the real-world applications of AI research.

After his tenure at DeepMind, Suleyman directed AI product development and policy at Google. Here, he influenced how AI was integrated into products while ensuring ethical considerations were prioritized. In 2022 he co-founded Inflection AI a company focused on developing natural language interfaces and generative AI to enhance human-computer interaction. He is now the current CEO at Microsoft AI. Outside of his research he shares insights through public speaking and his involvement with influential organizations, such as serving on The Economist's Board working as part of the Technology investment committee.

Timnit Gebru

A photo of Timnit Gebru

Timnit Gebru is a prominent computer scientist and one of the most influential advocates for diversity, equity, and inclusion (DE&I) in artificial intelligence. As the co-founder and President of Black in AI, she works to increase the representation and inclusion of Black research scientists in the AI field. She is also the founder of Distributed AI Research Institute, which focuses on conducting AI research that prioritizes social good and ethical considerations.

As the former co-lead of Google's Ethical AI team, she played a crucial role in ensuring that the company's AI products didn't perpetuate racial bias. But, following her departure in 2020 she published a paper that examined the ethics of AI language models and critiqued Google's approach to these complex issues. Due to her impactful work, Gebru was named one of Time Magazine's 100 Most Influential People in the World. Today she continues to advocate for responsible AI practices and emphasizes the importance of ethical standards and transparency in AI research and applications.

Sam Altman

photo of Sam Altman

As the co-founder of OpenAI, Sam Altman has cemented himself as one of the leading voices in AI research and generative AI. Since the release of ChatGPT, Altman has played a pivotal role in shaping the future of AI innovation. OpenAI's success has created a surge of interest among major tech companies prompting tech giants like Google and Meta to explore their own AI solutions. Microsoft and Tesla have made significant investments in OpenAI's research, helping to accelerate the advancement and global adoption of AI technologies.

Altman's influence expands well beyond his contributions to ChatGPT. As the former president of the startup accelerator, Y Combinator, he has helped to launch well-known companies like Airbnb, Dropbox, and Reddit. He has established himself as an innovator in the AI industry and has been behind numerous groundbreaking AI initiatives that have shaped the tech industry for over a decade.

Altman is a big advocate for ethical AI development, emphasizing the importance of creating transparent and accountable AI systems highlighting the need for AI to address pressing global issues like climate change and healthcare.

The Godfathers of AI

No list of AI leaders would be complete without three prominent figures dubbed the "AI Godfathers". In 2018, Yoshua Bengio, Yann LeCun, and Geoffrey Hinton received the prestigious Turing Award, considered the "Nobel Prize" of computing, for their groundbreaking contributions to deep learning.

They advanced neural network algorithms and architectures, leading to significant improvements in machine learning applications like computer vision, speech recognition, and natural language processing. Hinton developed the backpropagation algorithm, essential for training deep neural networks, while LeCun pioneered convolutional neural networks (CNNs) for image processing. Bengio focused on generative models and unsupervised learning. Together, their work has transformed the field of artificial intelligence, making deep learning a foundational element of modern AI systems.

Yoshua Bengio

photo of Yoshua Bengio

Bengio is a Canadian computer scientist and leading AI specialist, particularly in deep learning. His work on restricted Boltzmann machines, deep belief learning networks, and convolutional neural networks has been crucial to the progress of deep learning and the development of many popular AI systems. He's authored and co-authored many influential research papers and books that have shaped the discourse and direction of deep learning research. He also actively mentors and guides the next generation of AI researchers.

He actively advocates for responsible AI practices and development, emphasizing the importance of ethical concerns around AI. He also cofounded Mila, the Montreal Institute for Learning Algorithms, a world-famous research institute dedicated to advancing deep learning research and collaboration.

Geoffrey Hinton

A photo of Geoffrey Hinton

Widely regarded as a pioneer in artificial intelligence, computer scientist Geoffrey Hinton has been instrumental in the development of deep learning with foundational contributions to artificial neural networks and learning algorithms. He co-authored a seminal paper introducing backpropagation as a key technique for training neural networks that provided the critical mathematical framework necessary to advance machine learning. This breakthrough enabled algorithms to detect patterns in large data sets, leading to the development of neural networks now essential in image recognition, language processing, and other AI applications.

Beyond his technical contributions, Hinton has been a vocal advocate for the ethical and responsible advancement of AI. In 2023, he resigned from his senior role at Google to raise awareness about AI’s potential risks and has since advocated for protective measures. Hinton is also committed to using AI for social good, working with groups like the Red Cross and the United Nations on disaster response and healthcare projects. Through his research and mentorship, he promotes collaboration and knowledge-sharing in the AI community, cementing his influence in the field.

Yann LeCun

A photo of Yann LeCun

Yann LeCun is widely recognized for his groundbreaking contributions to deep learning, a branch of machine learning that enables computers to analyze and interpret complex data. His work has been crucial to the progress of AI, especially through his development of convolutional neural networks (CNNs), which were essential for improving image and speech recognition. In the 1990s, LeCun pioneered CNNs for image recognition, enabling computers to accurately classify images and laying the foundation for modern computer vision. This advancement has since been applied across industries, from self-driving cars to medical imaging.

LeCun currently serves as Chief AI Scientist at Meta, where he leads research efforts and shapes AI development. He has also published numerous influential research papers and mentors emerging AI researchers. Additionally, he established the Computational and Biological Learning Lab at New York University, a research group pushing the boundaries of AI and machine learning.

Wrapping up

AI is clearly a technology trend that is here to stay, and as it continues to evolve and transform it's crucial that businesses stay ahead of the curve by following these top AI leaders.

Their contributions are reshaping industries, from healthcare to finance, and influencing policy frameworks that prioritize ethical and inclusive AI. Following these experts provides insights into the future trajectory of AI and its societal impact.

Keeping up to date with these AI leaders can help you not only understand today’s AI advancements but also the direction of tomorrow’s tech landscape, where AI’s potential continues to expand.

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