35 Leading AI Thought Leaders in Silicon Valley

Silicon Valley is not simply where artificial intelligence is being built. It is where the fundamental questions about what AI should become are being asked, argued over, and answered in real time. The density of talent, capital, research institutions, and commercial ambition concentrated between San Jose and San Francisco has produced something the world has never seen before: a single geographic region responsible for the most consequential technological shift in human history.

The numbers alone are striking. San Jose held more patents in 2023 than any other city in the United States, with over 4,198 registered in a single year. The region is home to 91 venture-backed AI startups collectively valued at approximately $6 billion, according to the City of San Jose's own economic data. Stanford University's Human-Centered AI Institute has become the world's leading academic centre for the ethical and technical development of artificial intelligence, while San Jose State University produces more tech graduates than any other university in the Bay Area. NVIDIA chose San Jose as the home for GTC, the world's largest AI conference, drawing more than 30,000 attendees from over 190 countries in 2026 alone.

But the real story of Silicon Valley's AI leadership is not the conferences or the patents. It is the people: the researchers who spent decades working in obscurity before the world caught up to their ideas; the founders who built companies around problems most people could not yet see; the ethicists and governance experts who are fighting to ensure that the power being concentrated here is used wisely; and the investors who are deciding, every week, which visions of the future get the resources to become real.

This list brings together 35 of the most significant and actively contributing AI thought leaders working in Silicon Valley right now. They span seven disciplines: AI research and academia, foundation model leadership, enterprise AI and product innovation, AI ethics and governance, AI investment and ecosystem building, civic and public sector AI, and applied AI and startup innovation. Each of them is making a genuine and specific contribution to how the world thinks about, builds, and deploys artificial intelligence.

The goal of this list is not to celebrate Silicon Valley's self-importance but to make it genuinely useful to anyone trying to understand AI at the depth the moment demands. Whether you are a technology executive navigating an AI transformation, a leader trying to understand what the next five years will require of your organisation, or a practitioner who wants to know whose thinking deserves your sustained attention, the voices on this list are worth following closely.

To discuss how AI is reshaping leadership and team dynamics in your organisation, reach out to Jonno White, bestselling author of Step Up or Step Out (10,000+ copies sold globally) and Certified Working Genius Facilitator, at jonno@consultclarity.org.

Why Silicon Valley's AI Leadership Matters

The stakes of getting AI leadership right have never been higher. According to McKinsey's 2025 State of AI report, 78 percent of organisations globally have now integrated AI into at least one business function, up from 55 percent the year prior. The decisions being made by the people on this list, about which capabilities to build, which safety constraints to apply, which governance frameworks to adopt, and which communities to include or exclude, are shaping the systems that will touch billions of people's lives within a decade.

What makes Silicon Valley uniquely consequential is not just the concentration of capital or computing power. It is the unusual proximity of the people who build AI systems, the researchers who study their effects, the investors who fund their development, and the ethicists who challenge their assumptions. In most other places, these communities barely interact. In Silicon Valley, they share conference rooms, coffee shops, and sometimes the same organisations.

The voices on this list represent the full breadth of that conversation. Some of them are building the largest AI systems in the world. Some are sounding the clearest warnings about what those systems could become. Some are working inside city halls, enterprise boardrooms, and university labs to ensure that the benefits of AI are not captured by a narrow few. All of them are worth paying close attention to.

Understanding who is shaping AI in Silicon Valley is one of the most important forms of strategic literacy available to any leader in 2026. The people on this list are not simply commentators. They are architects. Following their thinking closely, and acting on what they reveal, is one of the most valuable investments a leader or organisation can make right now.

Jonno White works with leadership teams to translate the ideas these thinkers champion into practical decisions on Monday morning. To explore how that might work for your team, email jonno@consultclarity.org.

How This List Was Compiled

The selection criteria for this list prioritised three things: formal credentials in the form of published research, significant leadership roles, or recognised contributions to the field; geographic connection to Silicon Valley through their current or primary institutional affiliation; and genuine disciplinary diversity to ensure the list reflects the full breadth of AI's development rather than defaulting to the same handful of well-known names.

Geographic eligibility was defined broadly but deliberately. Silicon Valley encompasses the cities and towns that make up the peninsula and South Bay ecosystem, including San Jose, Santa Clara, Sunnyvale, Mountain View, Menlo Park, Palo Alto, Foster City, and the San Francisco Bay Area more broadly. San Jose sits at the urban heart of this ecosystem, hosting NVIDIA's annual GTC conference and housing both the largest concentration of tech talent in the region and the civic AI leadership of the City of San Jose itself.

The final 35 includes voices from AI research, foundation model leadership, enterprise product innovation, responsible AI and governance, investment and ecosystem building, civic and public sector AI, and applied AI startup innovation. Geographic and gender diversity targets were applied throughout the selection process.

The Researchers and Academics

The academic institutions of Silicon Valley, led by Stanford University and San Jose State University, are producing both the fundamental research that underlies modern AI and the ethical frameworks that govern its use. The researchers in this category are not simply publishing papers. They are defining the vocabulary, the benchmarks, and the standards by which the entire industry measures progress and safety. Their work moves from lab to product faster in Silicon Valley than anywhere else on earth, because the distance between a Stanford computer science department and a major technology company is sometimes measured in minutes rather than years.

1. Jensen Huang | NVIDIA

The story of modern AI cannot be told without Jensen Huang, who founded NVIDIA in 1993 from a Denny's restaurant in San Jose, California. As the company's CEO for more than three decades, Huang made a series of long-term bets on GPU-accelerated computing that most of the industry dismissed as irrelevant until they became the essential infrastructure of the AI age. NVIDIA's market capitalisation crossed $5 trillion in October 2025, making it the world's most valuable company at that time and validating a vision that Huang had been building quietly for years.

Huang's thought leadership on AI goes well beyond running a hardware company. His annual GTC keynote, delivered in San Jose, has become the most important annual address in AI, setting the intellectual agenda for how the industry thinks about accelerated computing, AI factories, agentic systems, and the physical AI that will power the next generation of robotics and autonomous systems. In 2026, he was appointed to the President's Council of Advisors on Science and Technology, confirming his status as the closest thing Silicon Valley has to an AI statesman.

2. Fei-Fei Li | World Labs / Stanford University

Fei-Fei Li created ImageNet, the large-scale visual dataset that triggered the deep learning revolution, at a time when most of her colleagues thought the project was too large and too ambitious to succeed. The decision proved transformative, and Li is now recognised as one of the most important figures in the history of AI. Named one of TIME's Persons of the Year in 2025 and a recipient of the Queen Elizabeth Prize for Engineering, she co-founded Stanford's Human-Centered AI Institute to ensure that as AI grew in power, the field retained its commitment to human values and human wellbeing.

Her most recent venture, World Labs, raised $1 billion in 2026 to advance spatial intelligence, an approach to AI that enables systems to understand and reason about three-dimensional physical environments. Li's book The Worlds I See, published in 2023, has become essential reading for anyone who wants to understand AI's development through the eyes of one of its most thoughtful architects. She holds dual roles as Cofounder and CEO of World Labs and Sequoia Professor of Computer Science at Stanford, a combination that gives her thought leadership a rare grounding in both commercial development and fundamental research.

3. Andrew Ng | DeepLearning.AI

Andrew Ng has trained more people in artificial intelligence than perhaps any other individual on earth. As the founder of DeepLearning.AI, the founding lead of the Google Brain team, former Chief Scientist at Baidu, and adjunct professor at Stanford University, Ng has spent his career making AI genuinely accessible to practitioners, students, and business leaders who might otherwise be shut out of the field's rapid development. More than 8 million learners have taken his courses through DeepLearning.AI and Coursera.

His weekly newsletter on AI is one of the most-read publications in the field, and his LinkedIn presence, with regular posts on AI education, business strategy, and policy, ensures that his thinking reaches an audience well beyond the academic community. Ng's foundational role in establishing the AI Fund as a venture studio and investment vehicle for AI-first companies has also made him a significant force in shaping which AI companies get built. His perspective on democratising AI education while also investing in frontier AI applications gives him a distinctive vantage point that few others in Silicon Valley can match.

4. Anima Anandkumar | Caltech

Anima Anandkumar holds the Bren Professor of Computing chair at the California Institute of Technology and has been one of the most productive and influential AI researchers working at the intersection of machine learning and scientific discovery. Her work on neural operators, mathematical tools that can solve the kinds of partial differential equations that govern weather patterns, fluid dynamics, and materials behaviour, represents a significant advance in using AI for scientific simulation. During her time at NVIDIA as Senior Director of AI Research, she co-developed the FourCastNet weather model, which demonstrated that AI could produce high-resolution weather forecasts tens of thousands of times faster than conventional numerical models.

Named to the TIME100 Impact Award for 2025 for using AI to accelerate scientific discovery, Anandkumar is a 2024 Blavatnik Award winner and a 2023 Guggenheim Fellow. She delivered a TED2024 talk on AI's ability to connect the digital and physical worlds, and her active LinkedIn presence ensures that her research findings reach practitioners and business leaders, not just academic peers. Her voice is essential for anyone trying to understand how AI is moving beyond language and into the physical sciences.

5. Percy Liang | Stanford HAI

Percy Liang is the director of the Center for Research on Foundation Models at Stanford University and one of the most rigorous and consequential researchers working on the evaluation and governance of large AI systems. He leads the development of HELM, the Holistic Evaluation of Language Models benchmark, which has become the most comprehensive publicly available framework for assessing what large language models can and cannot do reliably. HELM's methodology has influenced how AI developers, policymakers, and enterprise buyers think about comparing and selecting AI systems.

Liang also leads the Foundation Model Transparency Index, a systematic effort to assess how openly AI developers disclose information about their models' training data, capabilities, limitations, and deployment practices. This work sits at the critical boundary between technical AI research and AI governance, making Liang one of the few people in Silicon Valley with the credibility to engage productively with both domains. His research directly informs regulatory discussions at both state and federal levels, and his voice is essential for any leader navigating the governance landscape of enterprise AI deployment.

6. Rishi Bommasani | Stanford HAI

Rishi Bommasani is a researcher at Stanford HAI whose work on the societal impacts of foundation models has become some of the most cited and most influential in the AI safety and governance field. As the lead author of the Stanford HAI report On the Opportunities and Risks of Foundation Models, which introduced the term 'foundation model' into the AI lexicon, Bommasani helped frame the conceptual vocabulary that the entire industry now uses to discuss large-scale AI systems and their implications.

His ongoing work includes the Foundation Model Transparency Index and contributions to the AI Safety Benchmark developed in collaboration with multiple institutions globally. Bommasani posts regularly on LinkedIn about AI policy developments, research findings, and governance frameworks, making his thinking accessible to practitioners and policymakers who engage with his work in different professional contexts. He represents the next generation of Stanford HAI researchers whose contributions are already shaping policy and practice well beyond the academic community, and whose voice is particularly valuable for organisations navigating AI governance and risk decisions.

7. Chelsea Finn | Stanford University

Chelsea Finn is an assistant professor of computer science and electrical engineering at Stanford University and co-founder of Physical Intelligence, known as Pi, a robotics AI company building general-purpose robots that can operate across a wide range of physical environments and tasks. Her research at Stanford focuses on meta-learning and robot learning, two of the most technically significant and practically consequential areas of AI development. Her work on model-agnostic meta-learning (MAML) has been cited tens of thousands of times and has influenced virtually every major AI research group working on few-shot learning.

Her lab at Stanford, IRIS, is affiliated with the Stanford Artificial Intelligence Laboratory and leads research on enabling robots to acquire new skills quickly and transfer that learning across different physical environments. Finn's active research posting on LinkedIn, including summaries of new papers and commentary on research directions in robot learning and embodied AI, makes her an important follow for anyone trying to understand where AI capability is heading beyond language models. She received the Presidential Early Career Award for Scientists and Engineers in 2025, confirming her standing as one of the most technically productive AI researchers of her generation.

8. Daphne Koller | Insitro

Daphne Koller is the co-founder and CEO of Insitro, a South San Francisco-based company applying machine learning to drug discovery and development with the goal of making biomedical research fundamentally more productive and successful. She is also the co-founder of Coursera, the world's largest online learning platform, and a former Stanford professor whose contributions to probabilistic graphical models and Bayesian machine learning, including her book Probabilistic Graphical Models: Principles and Techniques, co-authored with Nir Friedman, have earned her the ACM Prize in Computing and election to the National Academy of Engineering.

Insitro's approach, which uses high-throughput biological data generation combined with large-scale machine learning to identify drug candidates and predict clinical outcomes, represents one of the most ambitious applications of AI to a domain with genuinely life-or-death consequences. The company has raised approximately $800 million in capital and has drug discovery partnerships with Bristol Myers Squibb. Her LinkedIn activity covers AI in drug discovery, the intersection of biological and machine intelligence, and the future of AI-driven scientific research, making her an important follow for anyone interested in how AI is transforming healthcare and the life sciences specifically.

The Builders: Foundation Models and the New AI Companies

No collection of Silicon Valley AI thought leaders would be complete without the founders and executives who are building the most consequential AI systems in the world. The San Francisco Bay Area is home to OpenAI, Anthropic, Perplexity, and a generation of AI companies whose products are already being used by hundreds of millions of people. The leaders in this category are not simply technology executives. They are making decisions every day about which AI capabilities exist, how they are shaped, and what constraints govern their deployment. Their thought leadership is inseparable from the companies they are building and the choices those companies make.

9. Dario Amodei | Anthropic

Dario Amodei co-founded Anthropic in 2021 after leaving OpenAI, where he had served as Vice President of Research, with a singular conviction that building powerful AI safely required a different organisational structure and a different set of research priorities than most in the industry were willing to adopt. Anthropic's Constitutional AI framework, which Amodei has championed as an approach to aligning AI systems with human values, has become one of the most widely discussed alignment methods in the field and has influenced governance discussions at government level in multiple countries.

By late 2025, Anthropic's annual revenue had surged to $4.5 billion, and the company had raised a total of $13 billion at a $183 billion valuation, establishing Claude as one of the most capable and widely adopted AI assistants available to enterprises and individuals. Amodei's public statements on AI development, safety timelines, and the responsibilities of AI laboratories, delivered through essays, congressional testimony, and conference appearances, make him one of the most influential voices on the philosophical dimensions of building frontier AI in Silicon Valley.

10. Aravind Srinivas | Perplexity AI

Aravind Srinivas is the co-founder and CEO of Perplexity AI, the San Francisco-based answer engine that has established itself as one of the most serious challenges to Google's decades-long dominance of internet search. Under Srinivas's leadership, Perplexity grew to 780 million monthly queries by mid-2025, raised $500 million at a $14 billion valuation, and forced the entire search industry to rethink what finding information on the internet should feel like in an AI-native world.

What makes Srinivas particularly valuable as a thought leader is his willingness to engage publicly and specifically with the technical and product decisions that shape Perplexity's development. His LinkedIn presence is one of the most substantive among Silicon Valley AI founders, featuring genuine engagement with research papers, product decisions, and strategic questions about the future of AI-powered information retrieval. He represents a generation of Silicon Valley AI founders who are building companies around AI applications rather than infrastructure, and whose success is demonstrating that the value of the AI era will be captured at the product layer as much as the model layer.

11. Mira Murati | Thinking Machines Lab

Mira Murati served as Chief Technology Officer at OpenAI before departing in late 2024 to found Thinking Machines Lab, a research company that raised a $2 billion seed round at a $12 billion valuation in July 2025. During her tenure at OpenAI, she oversaw the development and launch of ChatGPT, DALL-E, and the GPT-4 family of models, making her one of the most consequential product and research leaders in AI's modern era.

Thinking Machines Lab's mission and technical approach remain largely undisclosed, but the extraordinary funding raised on the strength of Murati's technical vision and leadership track record signals the premium that investors and the broader AI community place on her judgment. Her presence in Silicon Valley, and her willingness to engage publicly on AI development principles and the responsibilities of AI laboratories, makes her a significant voice in shaping how the next generation of AI companies approach the balance between capability and safety. Her trajectory from OpenAI to independent lab founder mirrors a pattern that is defining the current moment in Silicon Valley AI development.

12. Clara Shih | Meta

Clara Shih is one of Silicon Valley's most thoughtful and prolific executive voices on the practical application of AI in enterprise and consumer contexts. As the former CEO of Salesforce AI, where she oversaw the development and launch of Einstein GPT and the broader generative AI strategy for one of the world's largest enterprise software companies, and now as the head of Meta's Business AI group, she has spent the last several years at the leading edge of making AI genuinely useful for businesses and the people who work in them.

Named one of TIME's 100 Most Influential People in AI, Shih is a Stanford alumna who joined HubSpot's board in November 2025 and regularly contributes original analysis and commentary on LinkedIn about AI strategy, ethics, and the practical realities of deploying AI at enterprise scale. Her perspective on why making AI accessible to the 200 million businesses that use Meta's platforms requires a fundamentally different approach than enterprise AI is among the most practically grounded thinking available on AI's commercial development in Silicon Valley.

The Ethics and Governance Voices

Silicon Valley's most urgent conversation is not about which AI system is most capable. It is about who AI systems work for, what harms they cause to people they were not designed to serve, and what governance frameworks can prevent those harms from becoming permanent features of the AI landscape. The voices in this category are doing the most important and often least rewarded work in the AI field. They are building the conceptual vocabulary, the technical tools, the policy frameworks, and the institutional capacity that will determine whether AI's benefits are broadly shared or narrowly captured.

13. Timnit Gebru | DAIR Institute

Timnit Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute, known as DAIR, an independent research organisation she founded in Oakland following her departure from Google in 2020. Her firing from Google's AI ethics team, after she co-authored a paper raising concerns about the risks of large language models, became one of the most debated moments in AI's recent history and galvanised global discussion about power dynamics in AI research and the treatment of researchers who challenge institutional narratives.

At DAIR, Gebru leads research on the harms of AI systems to marginalised communities, the structural conditions that produce those harms, and the policy and technical interventions that can address them. Her 2021 paper Stochastic Parrots, co-authored with Emily Bender, Angelina McMillan-Major, and Margaret Mitchell, introduced one of the most influential conceptual frameworks for understanding the limitations and risks of large language models. Gebru's LinkedIn presence and public commentary are direct, substantive, and willing to challenge assumptions that many in Silicon Valley take for granted, making her an essential follow for anyone who wants to understand AI's impact on people outside the industry's usual circles of concern.

14. Rumman Chowdhury | Humane Intelligence

Rumman Chowdhury is one of the world's leading practitioners of responsible AI, with a career that spans Accenture, Twitter, the Biden administration, and Harvard's Berkman Klein Center for Internet and Society. She co-founded Humane Intelligence, a nonprofit organisation that builds community practice around AI model evaluation through red-teaming exercises and bias bounty challenges, most notably organising Hack the Future in collaboration with eight major technology companies and 4,000 participants.

Named one of TIME's 100 Most Influential People in AI and recognised as a Bay Area top 40 under 40, Chowdhury has also served as the United States Science Envoy for Artificial Intelligence, advising the Department of State on international AI policy. As Distinguished Advisor and co-founder of Humane Intelligence, her expertise in algorithmic bias, AI red-teaming, and the governance mechanisms needed to make AI systems publicly accountable is among the most practically grounded in the field. Her TED Talk, her writing in The Atlantic and Harvard Business Review, and her LinkedIn engagement all reflect a commitment to making responsible AI concepts accessible to non-technical leaders who need to act on them.

15. Beena Ammanath | Deloitte

Beena Ammanath leads the Global Deloitte AI Institute and Deloitte's AI Incubator, where she works with organisations worldwide on the practical implementation of trustworthy and responsible AI. She is the author of two books, Trustworthy AI and Zero Latency Leadership, both of which have become reference texts for executives navigating AI adoption with ethical rigour. Her career spans GE, HPE, Thomson Reuters, British Telecom, and Bank of America before her arrival at Deloitte, giving her a cross-industry perspective on AI implementation that is unusually broad.

Ammanath is a sought-after keynote speaker and serves on the boards of MIT SMR Editorial Advisory Board and the World Economic Forum Centre for Trustworthy Technology, among others. Her LinkedIn content is consistently substantive, translating responsible AI principles into practical guidance for senior leaders making real decisions about AI deployment and governance. She is also the founder of Humans For AI, a nonprofit dedicated to increasing diversity in the AI field. For any executive who needs to understand what trustworthy AI looks like in practice, not just in principle, Ammanath's voice is among the most consistently useful available.

16. Cassie Kozyrkov | Decision Intelligence

Cassie Kozyrkov served as Google's Chief Decision Scientist for years, developing and championing the discipline of decision intelligence, an applied field that brings together data science, behavioural science, and management science to improve how individuals and organisations make decisions. After leaving Google, she has continued to develop the field through advisory work, teaching, and one of the most consistently engaging bodies of AI thought leadership available on LinkedIn, where she has been named a LinkedIn Top Voice for multiple consecutive years.

Her particular gift is making complex statistical and AI concepts genuinely accessible without sacrificing accuracy or rigour. She writes about AI bias, the misuse of statistics, how to evaluate AI systems honestly, and the gap between what AI systems can do and what organisations expect them to do. Her perspective on the importance of defining 'good' before writing a single line of AI code has influenced how AI product teams approach specification and evaluation. For any leader who wants to understand AI decision-making at a level deeper than the marketing material, Kozyrkov is among the most essential follows available.

17. Kanjun Qiu | Imbue

Kanjun Qiu is the co-founder and CEO of Imbue, a San Francisco-based AI research company whose mission is to build AI systems that can reason and act reliably in the real world, with a focus on AI safety and the development of agents that can perform complex long-horizon tasks. Imbue's approach to building AI that can genuinely reason, rather than just pattern-match at high speed, places Qiu at the technical frontier of the most consequential open question in AI development: whether current approaches can produce systems that reliably do what they are intended to do in novel situations.

Her writing on AI safety, agent architecture, and the philosophy of intelligence is among the most genuinely thoughtful available from a working AI lab CEO. Qiu has spoken publicly about the importance of building AI systems that are legible and auditable, not just capable, and her willingness to engage with hard questions about AI alignment while simultaneously building commercial AI products gives her commentary a grounding that purely academic voices sometimes lack. Her LinkedIn presence is substantive and regularly features original analysis on topics ranging from reinforcement learning to the epistemics of AI research.

The Enterprise AI Innovators

Silicon Valley is also the home of the companies deploying AI at the largest scale into the everyday workflow of businesses worldwide. Zoom, Cisco, ServiceNow, Visa, and IBM Research are all headquartered in or immediately adjacent to San Jose, and the executives leading their AI efforts are shaping how AI is actually used by hundreds of millions of people who are not AI specialists. The thought leaders in this category are translating AI's possibilities into practical reality for the enterprise, and their voices are essential for any leader who needs to understand what AI adoption looks like from the inside of a large organisation.

18. Smita Hashim | Zoom

Smita Hashim is the Chief Product Officer of Zoom, headquartered in San Jose, where she oversees the product strategy behind Zoom AI Companion, one of the most widely adopted AI productivity tools in the enterprise market. A first-generation Indian immigrant, she holds engineering degrees from IIT Kanpur, Princeton, and UC Santa Barbara, and brings more than 20 years of product leadership experience from Google and Microsoft to her role at Zoom. Under her leadership, monthly active users of Zoom AI Companion grew fourfold year-over-year by late 2025.

Hashim is also the founder of the Women of IIT Network, a mentorship and leadership development community for women from IIT institutions worldwide. Her LinkedIn content addresses AI product development, enterprise AI adoption, the future of hybrid work, and women's leadership in technology, making her one of the most substantive voices on enterprise AI from within a Silicon Valley-headquartered company. For any leader navigating AI adoption in their own organisation, her perspective on what enterprise AI implementation actually looks like from the product side is among the most grounded and practically valuable available.

19. Shivani Govil | Cisco

Shivani Govil is a senior AI product and engineering leader at Cisco, headquartered in San Jose, where she works at the intersection of AI, networking, and enterprise security. An active participant in the Silicon Valley AI community through her involvement with TiEcon 2026 and regular engagement in Bay Area AI forums, Govil brings a practitioner's perspective on how AI is being deployed inside one of the world's largest technology companies serving enterprise customers globally.

Her LinkedIn content addresses AI product development, the human dimensions of AI adoption, and the leadership challenges that come with deploying AI at enterprise scale inside large, complex organisations. Her perspective is particularly valuable for leaders in industries adjacent to technology who are trying to understand how AI changes the operational and cultural dynamics of large organisations, not just the technical infrastructure. She represents the cohort of Silicon Valley AI practitioners whose contributions happen primarily inside organisations rather than in public research or startups, but whose impact on how AI is deployed in practice is substantial.

20. Vijay Kotu | ServiceNow

Vijay Kotu is the Chief AI and Analytics Officer at ServiceNow, the Santa Clara-based enterprise workflow automation company that has become one of the most significant platforms for deploying AI inside large organisations. Kotu is also the author of Data Science: Concepts and Practice, a widely used textbook that has introduced thousands of data science practitioners to the field. His work at ServiceNow focuses on building AI capabilities that help enterprises automate complex workflows, predict service disruptions before they occur, and give business leaders real-time visibility into AI performance across their organisations.

His LinkedIn content bridges the gap between academic data science and practical enterprise AI deployment, making his voice particularly useful for practitioners who need to understand both the technical and organisational dimensions of AI transformation. ServiceNow's approach to AI, which Kotu helps architect, emphasises explainability and auditability alongside performance, reflecting a responsible AI philosophy that is increasingly important as enterprises face regulatory scrutiny of their AI systems. For any leader responsible for enterprise AI strategy, his perspective on what good AI governance looks like from inside a major enterprise software company is essential reading.

21. Sriram Raghavan | IBM Research

Sriram Raghavan is the Vice President of AI Research at IBM Research, based in San Jose, where he leads a global research agenda on enterprise AI, foundation models, and AI trust and safety. IBM Research's San Jose lab is one of the longest-standing AI research institutions in Silicon Valley, and Raghavan's leadership shapes how one of the world's most significant enterprise technology companies thinks about and builds AI for its global customer base.

His research interests include natural language processing, knowledge-grounded AI, and the development of AI systems that are verifiable, explainable, and safe for deployment in regulated industries including healthcare, finance, and government. IBM's Watsonx platform, which Raghavan's research contributes to, represents one of the most significant enterprise AI investments outside of the major consumer AI labs, and his perspective on what enterprise AI needs to look like in terms of governance and reliability is shaped by IBM's decades of experience deploying technology in the world's most demanding environments. His LinkedIn content is technically rigorous and practically oriented, making it valuable for any practitioner navigating the specifics of enterprise AI deployment.

22. Praveen Gunasekaran | Visa

Praveen Gunasekaran is a Chief AI Architect and Senior Director at Visa, headquartered in Foster City at the heart of Silicon Valley, where he leads the design and implementation of Visa's enterprise-wide generative AI platform. His background spans algorithmic trading systems on Wall Street and large-scale machine learning initiatives across financial services, and he has built a reputation as one of the most technically sophisticated enterprise AI architects working at the intersection of AI and payments infrastructure.

His platform integrates knowledge graphs with multi-agentic systems to create AI capabilities that can handle the complexity, reliability requirements, and regulatory constraints of global payments processing. He has spoken publicly about the challenge of building AI systems that are not just capable but trustworthy enough for the financial infrastructure on which global commerce depends. His LinkedIn presence features substantive technical and strategic commentary on agentic AI, enterprise AI architecture, and the governance of AI in regulated financial services environments, making him an essential follow for any practitioner working on AI deployment in industries where error rates and explainability carry genuine legal and operational consequences.

23. Sanjay Poonen | Cohesity

Sanjay Poonen is the CEO of Cohesity, a San Jose-based data security and AI company that helps enterprises manage, protect, and extract intelligence from their data at scale. A veteran Silicon Valley technology leader who previously held senior roles at VMware, SAP, and Symantec, Poonen has built one of the largest LinkedIn followings of any Silicon Valley tech CEO, with more than 100,000 followers and a consistent record of original and substantive commentary on AI strategy, enterprise technology trends, and technology leadership.

His leadership of Cohesity sits at the convergence of AI and data security, two of the most strategically important areas in enterprise technology. His perspective on how AI changes the risk profile of enterprise data management, and on how leaders can think about AI governance within their broader technology strategy, is shaped by direct operational experience with the world's most demanding enterprise customers. For any technology executive navigating the intersection of AI adoption and data security, Poonen's voice is among the most practically grounded available from a Silicon Valley CEO.

The Investors and Ecosystem Builders

In Silicon Valley, the decision about which AI companies and research directions get the resources to become real is concentrated in a relatively small number of investors and ecosystem builders. The voices in this category are not simply allocating capital. They are making explicit bets on which visions of AI's future are most likely to be both technically achievable and commercially viable, and those bets shape which problems get worked on, which founders get supported, and which markets get transformed first. Understanding their thinking is essential for any leader who wants to anticipate where AI is headed before it arrives.

24. Vinod Khosla | Khosla Ventures

Vinod Khosla is the founder of Khosla Ventures and one of Silicon Valley's most consequential AI investors, having placed the first institutional money into OpenAI at a $1 billion valuation in 2019. A co-founder of Sun Microsystems and one of the most celebrated venture capitalists in Silicon Valley's history, Khosla has spent the last several years delivering some of the most provocative and specific predictions about AI's economic impact: that by 2030, AI will be capable of doing 80 percent of the work in 80 percent of all jobs, triggering the most significant economic disruption since the industrial revolution.

His predictions are deliberately bold and his reasoning is published openly through interviews, essays, and public appearances, making him one of the rare investors who engages seriously with the long-term societal implications of the technologies he funds. Khosla Ventures is headquartered in Menlo Park, and Khosla remains one of the most active and vocal investor voices in Silicon Valley's AI conversation. For any leader trying to understand how AI's most committed long-term investors think about the field's trajectory, his perspective is essential.

25. Sonya Huang | Sequoia Capital

Sonya Huang is a partner at Sequoia Capital, one of Silicon Valley's most storied and influential venture capital firms, where she focuses on artificial intelligence investments across the generative AI and enterprise AI landscapes. As the author of Sequoia's widely-read Generative AI: A Creative New World report, which was among the first serious venture capital analyses of the generative AI opportunity and its implications for technology markets, she helped establish the intellectual framework that informed how the entire investment community approached the generative AI boom.

Her investment portfolio spans some of the most significant AI companies building at the application layer, and her LinkedIn content regularly features original analysis of AI market dynamics, investment theses, and the emerging patterns in how AI companies build sustainable competitive advantages. As one of the most visible women in Silicon Valley AI investment, she also provides an important perspective on how diversity in decision-making shapes which AI opportunities get funded and which do not. For any founder, executive, or investor trying to understand how Sequoia and the broader VC community is thinking about AI, her voice is among the most important to follow.

26. Tim Tully | Menlo Ventures

Tim Tully is a partner at Menlo Ventures, headquartered in Menlo Park, where he leads investments in AI and infrastructure with an unusual combination of operator experience and investment perspective. As a former technology executive who built products generating more than $100 million in sales before transitioning to venture capital, Tully brings a practitioner's understanding of what it takes to build AI products that actually work in production environments, not just in demos.

Menlo Ventures' $100 million Anthology Fund, a partnership with Anthropic launched in 2024 to back AI founders building around the Claude ecosystem, represents one of the most explicit bets in Silicon Valley on a particular AI architecture and its commercial trajectory. Tully's LinkedIn content addresses applied AI, infrastructure investment, and the operational realities of building AI companies, making his perspective valuable for founders and operators who want to understand how investors with genuine technical backgrounds evaluate AI opportunities. He is one of the most actively posting investment partners at a major Silicon Valley firm.

27. Pieter Abbeel | UC Berkeley

Pieter Abbeel is one of the world's leading researchers in robot learning and reinforcement learning, holding the position of Professor at UC Berkeley while also co-founding Covariant, a robotics AI company whose technology was acquired by Amazon in August 2024. Following the acquisition, Abbeel was appointed to lead Amazon's large language model efforts within its AGI organisation by December 2025, combining his academic research leadership with a major corporate AI role. His podcast The Robot Brains has become one of the most widely listened to resources for understanding AI research across robotics, machine learning, and embodied intelligence.

Abbeel's research on meta-learning, deep reinforcement learning, and the application of AI to physical tasks has been cited more than 250,000 times in academic literature, and his ability to translate that research into commercial products through Covariant, and now into Amazon's broader AI strategy, makes him a uniquely valuable bridge between research and application. His investment partnership at AIX Ventures adds a further dimension to his influence on which AI startups and research directions receive support in Silicon Valley's ecosystem.

The Civic and Applied AI Leaders

Silicon Valley's AI conversation is sometimes dominated by private sector voices, but some of the most important and underappreciated AI leadership in the region is happening in universities, city halls, and applied research institutions that are not building products for commercial sale. The leaders in this category are ensuring that AI's development serves communities and institutions beyond the technology industry's usual customers, and their work is shaping the governance frameworks, the public sector applications, and the educational foundations that will determine whether AI's benefits extend beyond the world's most commercially valuable companies.

28. Albert Gehami | City of San Jose

Albert Gehami serves as the Privacy Officer for the City of San Jose, where he has built one of the most sophisticated municipal AI governance frameworks in the United States. Under his leadership, San Jose has been recognised as a national leader in AI governance and privacy, cited as a model by the White House, the National Institute of Standards and Technology, the Department of Homeland Security, and the IEEE. He manages the GovAI Coalition, a network of more than 500 local, state, and federal agencies committed to responsible AI deployment and vendor accountability.

Gehami's work represents something rarely seen in AI leadership discussions: a practitioner who is building AI governance capacity inside a government institution rather than writing about it from the outside. His contribution to the field is making the City of San Jose a case study in how public sector organisations can deploy AI responsibly while maintaining accountability to the residents they serve. For any leader in local or state government, or any enterprise working with public sector clients, his perspective on what good AI governance looks like in practice is among the most practically grounded available anywhere.

29. Magdalini Eirinaki | San Jose State University

Magdalini Eirinaki is a Professor of Computer Engineering at San Jose State University, where she serves as Associate Chair of Graduate Affairs and leads research in machine learning, recommender systems, generative AI, and graph mining. SJSU, located in the heart of downtown San Jose, produces more tech graduates than any other university in the Bay Area according to the City of San Jose's economic data, and Eirinaki's research sits at the boundary between academic contribution and direct industry application in Silicon Valley's AI ecosystem.

Her research is funded by the NSF, Google, the California Learning Lab, and IBM, and she has published prize-winning work on multimodal AI benchmarking and personalised AI systems. As the steward of the computer engineering graduate programme that feeds Silicon Valley's AI talent pipeline, and as an active researcher contributing to the field while training the next generation of practitioners, Eirinaki represents the essential but often overlooked academic infrastructure that makes Silicon Valley's AI ecosystem possible. Her LinkedIn content covers AI research findings, educational AI applications, and the opportunities and risks of generative AI in academic and professional contexts.

30. Anand Akela | Cisco

Anand Akela is a senior AI practitioner at Cisco, headquartered in San Jose, and an active contributor to the Silicon Valley AI community through his involvement with TiEcon 2026 and regular engagement in Bay Area AI forums and events. His work at Cisco addresses the practical dimensions of deploying AI inside one of the world's most significant enterprise networking and security companies, where AI capabilities are being integrated into infrastructure products used by organisations globally.

His LinkedIn content features regular commentary on AI in enterprise technology, the future of agentic AI systems, and the human and organisational dimensions of AI transformation. As a practitioner working inside a major Silicon Valley technology company rather than a researcher or founder, Akela offers a perspective on AI adoption that is grounded in the operational reality of large-scale technology deployment. He regularly engages with the broader Silicon Valley AI community through events and online forums, making his presence in the ecosystem more than simply a professional role at a single company.

31. Aigerim Shorman | GV (Google Ventures)

Aigerim Shorman is an investor at GV, the corporate venture capital arm of Google, based in the Bay Area, where she focuses on AI and technology investments at the intersection of consumer, enterprise, and deep tech. As a woman of Kazakh origin working in Silicon Valley venture capital, she brings both a distinctive cultural perspective and an investor's vantage point on which AI applications are most likely to generate durable value in the current market environment.

Her LinkedIn presence reflects an active engagement with the Bay Area AI ecosystem, including participation in TiEcon and other Silicon Valley community events, and her commentary on AI investment trends and the opportunities she is most focused on provides a window into how one of the world's most significant corporate venture funds is thinking about the AI landscape. For any founder building in AI and seeking to understand how a Google-affiliated investment fund evaluates opportunities, or for any leader trying to understand which AI applications are attracting serious institutional investment, her perspective is worth following.

32. Siqi Chen | Runway

Siqi Chen is a product leader and AI voice based in Silicon Valley with a deep track record in consumer internet and AI products. He has built and scaled products to tens of millions of users and has become one of the most widely followed AI commentators in the Bay Area's practitioner community, known for direct and substantive commentary on AI product development, the future of AI-native companies, and the practical realities of building with and competing against large language models.

His LinkedIn content features genuine analysis of AI product strategy, the competitive dynamics of the AI market, and the specific decisions that differentiate AI products that succeed from those that do not. He is particularly attentive to the ways in which AI is changing the economics of software products and the implications that change has for founders, operators, and investors. For any practitioner trying to understand AI product development from someone who has built at scale, his voice is among the most practically grounded available in the Silicon Valley community.

33. Deedy Das | Google DeepMind

Deedy Das is a machine learning engineer and AI practitioner based in Silicon Valley whose LinkedIn presence has made him one of the most widely followed practitioner voices on ML career development, AI research, and the realities of working in AI at major technology companies. His posts on machine learning careers, technical interview preparation, and the day-to-day realities of AI engineering have been shared hundreds of thousands of times and have made him a genuine resource for the next generation of AI practitioners entering the field.

His perspective is unique because it bridges the highly technical world of ML engineering and the broader questions about AI's trajectory and implications that concern business leaders and policy audiences alike. At Google DeepMind, he contributes to AI research and engineering at one of the world's most significant AI research laboratories, giving his commentary the grounding of direct experience with frontier AI development. He is among the most actively engaging AI voices on LinkedIn in Silicon Valley, with a track record of substantive original content that has earned him one of the field's most engaged and growing followings.

34. Rana el Kaliouby | Smart Eye

Rana el Kaliouby is a pioneer in emotion AI, the field dedicated to enabling computers to recognise, interpret, and respond to human emotional signals through analysis of facial expressions, voice patterns, and physiological data. As a scientist, entrepreneur, and thought leader, she is the author of Girl Decoded, a memoir that traces her journey from Egypt to MIT and into the commercialisation of emotion AI through the company Affectiva, which she co-founded and which was acquired by Smart Eye in 2021. She was named one of TIME's 100 most influential people in AI.

El Kaliouby's work raises some of the most consequential questions in AI ethics about privacy, consent, and the risks of AI systems that can read and respond to human emotional states at scale. Her advocacy for human-centred AI, her experience building an AI company from academic research to commercial scale and acquisition, and her perspective on the ethical dimensions of AI systems that engage with human psychology make her one of the most distinctive and important voices in the field. Her active presence at Bay Area events and her sustained public commentary on the intersection of AI, emotion, and human dignity give her thought leadership a dimension that is genuinely missing from most Silicon Valley AI conversations.

35. Nikunj Parekh | Bay Area

Nikunj Parekh is one of Silicon Valley's most consistently engaging AI voices among the practitioner community, known for his weekly AI blog on LinkedIn and active involvement in Bay Area AI events including TiEcon. His content synthesises recent AI developments into practical insights for business leaders, product managers, and technologists who need to stay current with a rapidly evolving field without spending their entire professional lives tracking it.

What distinguishes Parekh from many LinkedIn AI voices is his focus on actionable application rather than hype amplification. His commentary on specific AI tools, frameworks, and use cases provides genuine signal in a space dominated by noise, and his engagement with his audience through comments and direct dialogue reflects the kind of community-building that gives his voice genuine reach beyond his immediate network. He represents the cohort of Silicon Valley AI practitioners who are not building frontier models or leading research labs but whose contribution to how AI is understood and applied by the thousands of companies and leaders surrounding them is genuinely valuable. Following his weekly analysis is one of the most efficient ways for a working professional in Silicon Valley to stay meaningfully current on AI's practical development.

Notable Voices We Almost Included

Several excellent candidates were considered and came close to making the final 35. Daniela Amodei, President of Anthropic and co-founder alongside her brother Dario, was considered but ultimately did not make the final list given amplification constraints. Her contributions to Anthropic's commercial growth and enterprise strategy are substantial and worth following independently. Lisa Su, CEO of AMD in Santa Clara, brings semiconductor leadership directly relevant to AI infrastructure, but her primary focus is hardware strategy rather than AI thought leadership in the way this list defines it. Reid Hoffman, co-founder of LinkedIn and Greylock partner, has been a vocal AI advocate, but a preference for higher-amplification alternatives shaped the final selection. Greg Brockman, co-founder of OpenAI, is on a leave of absence from the company, and his contribution to the active conversation has been less consistent than in previous years. Aicha Evans, CEO of Zoox in Foster City, was very close to inclusion given her compelling voice on autonomous AI and diversity, and she remains one of the strongest voices on the boundary of this list.

Common Mistakes to Avoid When Engaging With AI Thought Leadership

The first and most common mistake is treating AI thought leadership as a substitute for building internal capability. Following Fei-Fei Li on LinkedIn, attending Jensen Huang's GTC keynote, or reading Andrew Ng's newsletter is genuinely valuable. None of it replaces the work of developing your own organisation's understanding of what AI means specifically for your decisions, your risks, and your customers. The voices on this list set the frame. Your organisation has to do the work of applying it.

The second mistake is consuming thought leadership without distinguishing between different kinds of claims. A researcher announcing a new benchmark result is making a different kind of claim than an investor predicting which AI companies will dominate in five years, which is different again from an ethicist identifying a pattern of harm in how AI is currently deployed. All of these claims are valuable. None of them should be received in the same way or given the same weight of certainty.

The third mistake is following only the most globally famous voices. Jensen Huang, Andrew Ng, and Fei-Fei Li are essential follows. They are also the voices whose perspectives are most heavily repeated and discussed. The genuine insight, especially for leaders who need to act on AI developments rather than simply understand them, often comes from the less globally famous voices: Percy Liang's work on AI evaluation, Rishi Bommasani's foundation model transparency research, Smita Hashim's perspective on enterprise AI adoption, Albert Gehami's governance frameworks. These voices are more likely to give you something genuinely new.

The fourth mistake is confusing Silicon Valley's AI culture for the whole of AI. The perspectives represented here are powerful and important. They are also shaped by a particular geography, a particular funding ecosystem, and a particular set of values about what constitutes technological progress. The voices on this list who most actively challenge those defaults, including Timnit Gebru, Rumman Chowdhury, and Kanjun Qiu, are worth paying particular attention to precisely because their challenges come from inside the ecosystem that most needs to hear them.

The fifth mistake is waiting until you fully understand AI before you act on it. The leaders most at risk in the current moment are not the ones who moved too fast and made mistakes. They are the ones who waited for certainty that is not coming. The AI thought leaders on this list, across all their different disciplines and perspectives, share one conviction: the decisions being made right now will shape the decade that follows, and the window for shaping them well is narrower than it looks.

Implementation Guide: Building Your Silicon Valley AI Reading List

The most practical thing you can do with this list right now is decide which three of the 35 people on it most closely align with your most pressing professional challenge, and commit to reading everything they publish for the next 90 days. Not skimming. Reading. The quality of your AI strategy is directly proportional to the quality of your understanding, and the quality of your understanding is directly proportional to the depth of your engagement with the people on the front lines of AI's development.

For leaders focused on enterprise AI adoption and organisational transformation, the most immediately useful voices are Smita Hashim, Vijay Kotu, Sanjay Poonen, Sriram Raghavan, and Beena Ammanath. These are practitioners who are deploying AI inside large organisations right now and thinking publicly about what works and what does not.

For leaders focused on AI governance and responsible deployment, the essential voices are Timnit Gebru, Rumman Chowdhury, Cassie Kozyrkov, Percy Liang, Rishi Bommasani, and Albert Gehami. Their work will give you the frameworks you need to navigate the governance questions that regulators, boards, and employees are increasingly asking.

For leaders focused on understanding where AI is going technically, the most valuable voices are Fei-Fei Li, Anima Anandkumar, Chelsea Finn, Pieter Abbeel, Kanjun Qiu, and Andrew Ng. Their research is at the frontier of what AI systems will be able to do in the next three to five years, and their accessible communication of that research removes the need for deep technical expertise to benefit from it.

For investors and executives trying to understand market dynamics, Sonya Huang, Tim Tully, Vinod Khosla, Aravind Srinivas, and Siqi Chen provide the most substantive and specific commentary on which AI opportunities are genuinely compelling and why.

Beyond LinkedIn, most of the people on this list publish in multiple formats. Several host podcasts: Pieter Abbeel's The Robot Brains, Andrew Ng's The Batch newsletter. Several write substantive essays: Vinod Khosla publishes long-form pieces on his website. Several appear frequently in high-quality media: you will find Fei-Fei Li, Dario Amodei, and Rumman Chowdhury interviewed in venues ranging from Nature to The Atlantic.

The most important platform for following this community remains LinkedIn in 2026, which has become the primary professional learning network for AI practitioners and leaders. A well-curated LinkedIn feed built around this list functions as a free, ongoing AI strategy briefing from some of the most credentialled people working on these questions anywhere on earth.

To explore how the ideas these thinkers are advancing could be put into practice in your own leadership team or organisation, email Jonno White, author of Step Up or Step Out (10,000+ copies sold globally) and Certified Working Genius Facilitator, at jonno@consultclarity.org. International travel is often far more affordable than clients expect.

Frequently Asked Questions

What makes someone a Silicon Valley AI thought leader rather than just a Silicon Valley technology executive?

The distinction is between people who are actively contributing to how the field understands itself and where it is going, and people who are primarily executing within their organisations. The people on this list are doing both: building organisations and publishing research, writing essays and building products, speaking at conferences and shaping policy. The thought leader designation is earned by the quality and specificity of their public contribution to the AI conversation, not by their title or their organisation's valuation.

How was this list compiled and what criteria were applied?

The selection prioritised formal credentials in the form of published research, significant leadership roles, or recognised contributions to the field; geographic connection to Silicon Valley through current or primary institutional affiliation; and genuine disciplinary diversity to ensure representation across AI research, foundation model leadership, enterprise AI, ethics and governance, investment, civic AI, and applied startup innovation. Geographic and gender diversity targets were applied throughout. The goal was a list that is genuinely useful and editorially credible, not simply a compilation of the most famous people in AI.

Why does the list include ethics and governance voices alongside researchers and executives?

Because AI's development cannot be separated from the questions about how it should be governed, who it serves, and what harms it risks causing. The researchers and executives on this list are building the most powerful AI systems in the world. The ethics and governance voices are building the frameworks and accountability mechanisms that will determine whether those systems benefit everyone or primarily the people and organisations who build them. Both sets of voices are essential for any serious AI strategy.

How often should I check on these thought leaders' content?

Quality matters more than frequency. A useful rhythm is checking the LinkedIn profiles of your top five chosen voices twice a week, reading anything longer than a paragraph from cover to cover rather than scanning, and dedicating 30 minutes per week to a longer-form piece from at least one person on the list. Consistent, deep engagement with a smaller set of voices produces better learning than daily skimming of everyone.

Can I hire someone to facilitate AI-related leadership workshops or keynotes for my team?

Yes. Jonno White, bestselling author of Step Up or Step Out with over 10,000 copies sold globally, Certified Working Genius Facilitator, and host of The Leadership Conversations Podcast with 230+ episodes reaching listeners in 150+ countries, works with leadership teams to translate the ideas these thinkers champion into practical decisions on Monday morning. Whether your team needs a keynote on the human side of AI, a workshop on leading through AI-driven change, or an executive offsite focused on what AI means for your organisation's strategy and culture, email jonno@consultclarity.org. International travel is often far more affordable than clients expect.

Final Thoughts

Silicon Valley is changing faster than it ever has. The 35 people on this list are among the primary reasons why. From Jensen Huang's conviction, sustained over three decades, that GPU computing would eventually power everything we now call AI, to Timnit Gebru's equally sustained conviction that the power being built in Silicon Valley must be accountable to the people it affects, this list represents the full, sometimes contradictory, always consequential breadth of AI leadership in the region that is defining the technology's global trajectory.

The most important thing this list can do for you is not save you time. It is direct your attention. The AI conversation is enormous, and most of it is noise. The voices on this list have earned the right to your sustained engagement through the quality and consistency of their contributions to a field that is reshaping everything.

Following these thinkers closely is not a passive activity. The best way to engage with thought leadership is to bring it into contact with your own specific context, your organisation's strategy, your team's capabilities, and your own leadership challenges. The moment when an idea from Percy Liang's research on AI transparency connects with a governance decision your organisation is facing, or when Smita Hashim's perspective on enterprise AI adoption clarifies a product decision your team is wrestling with, is when thought leadership becomes genuinely valuable.

The leaders who will navigate the AI age most effectively are not the ones who move fastest or adopt most aggressively. They are the ones who understand most clearly, act most deliberately, and lead most humanely. The people on this list, in different ways and from different vantage points, are all trying to show what that looks like.

To discuss what AI leadership development looks like for your specific team, contact Jonno White, Certified Working Genius Facilitator and host of The Leadership Conversations Podcast, at jonno@consultclarity.org.

About the Author

Jonno White is a Certified Working Genius Facilitator, bestselling author, and leadership consultant who has worked with schools, corporates, and nonprofits across the UK, India, Australia, Canada, Mongolia, New Zealand, Romania, Singapore, South Africa, USA, Finland, Namibia, and more. His book Step Up or Step Out has sold over 10,000 copies globally, and his podcast The Leadership Conversations has featured 230+ episodes reaching listeners in 150+ countries. Jonno founded The 7 Questions Movement with 6,000+ participating leaders and achieved a 93.75% satisfaction rating for his Working Genius masterclass at the ASBA 2025 National Conference. Based in Brisbane, Australia, Jonno works globally and regularly travels for speaking and facilitation engagements. Organisations consistently find that international travel is far more affordable than expected.

To book Jonno for your next keynote, workshop, or facilitation session, email jonno@consultclarity.org.