Explore how AI-powered strategy is reshaping the future of consulting in this episode, as our expert guest shares actionable insights on integrating AI into workshops, ideation sessions, and customer feedback analysis. Discover practical techniques for balancing human judgment with AI-driven analytics, diagnosing organizational culture, and generating management insights. Listeners will gain real-world examples of clustering survey data, enhancing consultant productivity, and predicting customer engagement metrics, equipping them with innovative approaches for more effective and efficient strategic planning.

In this episode, Team-X AI Co-Founder explores the transformative shift from 'humans plus AI' as a technical tool to AI as a catalyst for collective sense making and shared mental models within organizations. Discover how the generative AI layer is redefining team collaboration, the importance of embedding AI in organizational processes from the outset, and the impact of collaborative, team-level AI adoption. You’ll gain actionable insight into redesigning workflows, addressing cognitive diversity barriers, and fostering psychological safety and trust to build resilient, future-ready organizations.

Join Future Minds Lab as they explore how AI-driven change is reshaping society and what individuals and organizations need to thrive. This episode covers practical insights from neuroscience and psychology on effective AI-specific change management, introducing the SMILE framework for knowing when to trust your intuition versus AI. Discover why designing AI to augment human skills is vital, and learn about strategies for maintaining critical thinking, the cognitive benefits of visual mental imagery, and the emerging therapeutic and creative potentials of AI for personal transformation.

In this episode, Diyi Yang discusses how large language models can meaningfully augment human capabilities in both work and well-being. She explains her research on building AI partners and mentors that help people practice supportive communication skills through realistic, coached interactions—an approach designed not to replace human connection but to strengthen it. She also describes her team’s landmark “Future of Work with AI Agents” study, which mapped how workers across many occupations want AI to automate or augment their tasks, revealing major gaps between what workers want, what AI can do, and where research is currently focused. A central idea throughout is “human agency”: understanding how humans and AI share control across tasks and why the right granularity—looking at workflows, not whole jobs—is essential for successful augmentation.

The conversation also explores emergence, the creation of new roles and opportunities when humans and AI collaborate rather than compete. Yang shares insights from studies on AI-generated research ideas, revealing an “ideation-execution gap” where AI proposals appear highly novel but often fall short in practical implementation. She emphasizes the importance of understanding hidden human skills through workflow auditing, designing AI that enhances long-term well-being rather than short-term engagement, and building systems that surface latent human capabilities. Ultimately, she is optimistic about a future where humans and AI expand what is possible together—and where conversations, creativity, and domain expertise remain at the center of meaningful progress.

In this conversation, behavioral data scientist Ganna Pogrebna discusses how human behavior, bias, and decision-making shape AI systems. She explains that nearly all algorithms are trained on human-labelled data—carrying human biases into machine outputs—using examples like Amazon’s hiring algorithm and video-based interview tools that rated identical answers differently depending on background visuals. Pogrebna emphasizes that truly effective AI-human collaboration begins with understanding these biases, using AI intentionally for creativity rather than precision, and developing strong prompting skills that provide context and purpose. She also warns against relying blindly on AI-generated information, highlighting the importance of verifying sources and maintaining personal accountability in team environments where misinformation can damage human reputation.

The discussion extends into the future of human-AI teams, where Pogrebna argues that organizations should treat AI as a brainstorming partner rather than a perfect advisor. She explores how digital twins and behavioral simulations can support strategic decision-making, from content creation to stakeholder modelling, as long as they are grounded in real human data and supplemented with direct customer engagement. While machines and humans think differently—machines requiring far more examples to learn—Pogrebna believes the real challenge lies not in AI design but in teaching people to recognize, collaborate with, and properly communicate with machines. She concludes with an optimistic outlook: if we embrace AI as a tool for augmentation rather than control, we can uncover meaningful benefits for individuals, teams, and businesses.

In this insightful conversation, Ross Dawson and Dr. Sue Keay explore how artificial intelligence—particularly through robotics—can be used to address global challenges such as climate change and environmental preservation. Dr. Keay shares a compelling example of an underwater vision-guided robot designed to help restore the Great Barrier Reef, illustrating how AI can take on tasks beyond human capability. She emphasizes that AI’s true value lies in augmenting human efforts, from ecological restoration to agriculture, where precision robotics can enhance productivity and sustainability.

The discussion also delves into the organizational, societal, and national dimensions of AI transformation. Dr. Keay highlights the importance of open-minded leadership, experimentation, and ethical governance in integrating AI across industries and education. She cautions against cognitive offloading, advocates for human-AI collaboration in the workplace, and calls for stronger national investment in sovereign AI infrastructure and talent development. Drawing from her experience at the UNSW AI Institute, she envisions a future where nations like Australia can retain AI expertise, build their own models, and create meaningful global impact while preserving human autonomy and innovation.

In this insightful episode, futurist Ross Dawson speaks with strategist Dominique Turcq about the evolving nature of strategy in a world transformed by artificial intelligence. Turcq traces how corporate strategy has shifted from shareholder-focused planning to a broader responsibility toward society and the planet. He discusses the decline of traditional Chief Strategy Officer roles and emphasizes the growing need for long-term thinking, scenario planning, and foresight in an era defined by environmental limits, demographic shifts, and rapid technological change.

The conversation then turns to AI’s impact on governance and cognition. Turcq explains how generative AI is reshaping the relationship between executive teams and boards, introducing new ethical, regulatory, and communication challenges—but also new opportunities. He warns of the risk of “cognitive atrophy” as humans increasingly offload thinking to machines, calling for an “ecology of mind” where technology enhances rather than weakens our mental capacities. Together, Dawson and Turcq envision a future in which strategy, leadership, and learning evolve hand-in-hand with intelligent systems.

In this episode, Ross Dawson speaks with nonprofit technology leader Beth Kanter about how artificial intelligence can free up valuable time for mission-driven organizations. Kanter introduces the concept of the “dividend of time” — when AI automates routine tasks, nonprofits can reinvest those saved hours into stronger relationships, deeper learning, and more innovative impact. She encourages teams to view AI as a collaborator, using frameworks like the prep chef, sous chef, and family recipe to determine where automation, augmentation, and uniquely human work should fit within their workflows.

Kanter also shares practical ways AI can enhance nonprofit fundraising, personalize donor engagement, and elevate critical thinking rather than replace it. Through thoughtful use of large language models as learning partners — not answer machines — nonprofit professionals can strengthen reflection, strategic decision-making, and creativity. The conversation explores ethical considerations, team norms for AI collaboration, and the emerging human skills needed to build more adaptive, humans-plus-AI organizations in the future.

Futurist Ross Dawson returns to the Humans Plus AI podcast with updates from his recent keynotes in Dubai and Riyadh, where he explored how artificial intelligence can amplify human potential and reshape the future of organizations. He reaffirms that Humans Plus AI is more than a concept—it’s a growing movement dedicated to understanding how people and AI can collaborate to create better outcomes for individuals, companies, and society. Dawson also introduces Thought Weaver, a new application designed to enhance human-AI thinking workflows, inviting the community to participate in its development.

He then outlines his “Six Levels of Humans Plus AI in Organizations” framework, which describes how businesses evolve through six stages: augmented individuals, human-AI hybrid teams, learning communities, fluid talent, evolutionary enterprises, and ecosystem value co-creation. Each level represents a deeper integration of AI into human collaboration and decision-making—from improving personal productivity to transforming entire ecosystems. Drawing examples from organizations like Morgan Stanley, Schneider Electric, Siemens, Unilever, Maersk, and MELLODY, Dawson illustrates how forward-thinking companies are already embracing this transformation.

In this episode, Ross Dawson speaks with Iskander Smit about the evolving relationships between humans, AI, and autonomous “things.” Drawing on his Cities of Things research, Iskander explains how AI is moving beyond being just a tool or mirror to becoming a collaborator, co-author, or even an “intern” that can structure thinking, reflect back new insights, and challenge human biases. The conversation highlights the importance of intent and conversational feedback loops in shaping valuable interactions, showing how AI can enrich rather than replace human reflection.

From a design perspective, Iskander emphasizes the shift toward co-creative systems that are continuously evolving. He advocates for introducing intentional “friction” in AI experiences—interruptions and adaptive narratives that help users engage more deeply and avoid black-box outcomes. Looking ahead, he sees designers taking on the role of creative directors working with AI partners, while human-to-human and human-AI conversations remain central to building collective intelligence.

In this episode, Ross Dawson speaks with Brian Kropp about how organizations can move beyond AI experimentation to truly drive adoption and performance. They discuss the gap between executive expectations—often aiming for 20–50% improvements in performance—and the current reality of single-digit results. Kropp emphasizes that while the technology is ready, the real challenge lies in adoption: creating the right incentives, redesigning organizational structures, and ensuring leaders are both comfortable and competent with AI.

The conversation explores practical approaches such as focusing on measurable pain points, forming cross-functional teams, and fostering a culture where experimentation and even failure are celebrated. Kropp also shares insights into the future of management, noting how AI will flatten hierarchies by reducing the need for middle managers and shifting leadership toward relationship-building and strategic guidance. Together, they highlight how organizations that embrace AI boldly—accelerating into the “turns”—will be best positioned to gain a competitive edge in the years ahead.

In this episode, futurist Ross Dawson speaks with Suranga Nanayakkara, founder of the Augmented Human Lab, about reimagining the relationship between people and technology. Suranga shares his personal journey of feeling “not good enough” with early computers, and how that experience inspired him to design human-computer interfaces that assist and empower rather than intimidate. He discusses breakthrough projects such as ISee, a wearable device that helps blind people — and travelers like himself — access visual information seamlessly, and Prospero, a cognitive training tool that adapts learning moments to an individual’s readiness and cognitive load.

The conversation explores the Lab’s wider innovations, including AI-augmented reasoning, wearable fact-checkers, interactive tools co-designed with autistic children, and even the concept of an “AI inner voice” that nudges people toward healthier and more confident choices. Suranga emphasizes co-design with stakeholders, context-awareness, and non-invasive augmentation as guiding principles. Looking ahead, he sees the convergence of AI, robotics, and consumer wearables as opening new horizons for technologies that help us make better decisions, learn more effectively, and ultimately become better versions of ourselves.

In this episode, Ross Dawson speaks with renowned computer scientist Michael I. Jordan about the misconceptions surrounding artificial intelligence and human intelligence. Jordan emphasizes that despite advances in machine learning, we are far from understanding the depths of human intelligence, which is not just cognitive but also deeply social and cultural. He argues that current AI systems are largely brute-force tools trained on massive datasets, lacking the creativity, shared experience, and contextual understanding that define human thought. Instead of chasing “superintelligence,” he suggests we focus on how AI can complement humans and enhance overall social welfare.

The discussion also explores the idea of “collective genius,” where innovation emerges not from isolated individuals but through shared knowledge and collaboration. Jordan stresses the importance of embedding economic principles—such as incentives, information asymmetry, and social welfare—into the design of AI systems. By viewing AI as an economic facilitator that helps shape markets and decision-making, rather than as a replacement for human intelligence, he sees potential for technology to empower people. However, he cautions against the concentration of power in the hands of a few and urges for broader, collective approaches that prioritize fairness, adaptability, and human values.

Salesforce’s Chief Ethical and Humane Use Officer, Paula Goldman, joins Ross Dawson to discuss how organizations can design and deploy AI responsibly while maximizing its benefits. She emphasizes that ethical AI is not just about avoiding harm, but about fostering trust through transparency, safeguards, and collaborative design. Goldman outlines practical strategies like adversarial testing, inclusive stakeholder input, and clear escalation processes between humans and AI to ensure systems perform reliably and support meaningful human oversight. She also introduces the concept of “human at the helm,” reframing traditional “human in the loop” models to better suit autonomous, agentic AI while preserving human control over critical decisions.

The conversation also covers AI governance in real-world settings, advocating for iterative, minimum viable governance structures that start with clear goals, basic performance metrics, and heightened diligence for sensitive use cases. Goldman stresses the importance of board-level oversight, diverse advisory councils, and open channels for employee feedback to ensure responsible deployment. Ultimately, she envisions a future where AI augments human creativity, deepens connections, and frees people for higher-value work—underscoring that the technology’s positive potential depends on intentional, values-led implementation.

In this thought-provoking conversation, Ross Dawson speaks with neuroscientist and entrepreneur Vivienne Ming about using artificial intelligence to amplify human potential. Ming shares powerful personal stories—from hacking her son’s diabetes equipment to founding companies that pioneer AI-driven health diagnostics. She explains how true innovation lies in systems that don't replace human ability but instead enhance it—even after the technology is turned off. Drawing on her work in neuroprosthetics and postpartum depression, she explores how human-AI hybrid systems can help us plan better for the future through data, diagnostics, and trust-based, personalized health insights.

The conversation expands into education, metacognition, and the ethical use of AI in learning environments. Ming warns against over-reliance on AI tools that can dull cognitive engagement, emphasizing the need to foster reflective thinking, uncertainty awareness, and diverse problem-solving. She challenges us to embrace AI not as a crutch, but as a partner in discovery—one that enhances creativity rather than conformity. Her vision of the future is one where individual uniqueness is not just preserved but magnified through thoughtful, human-centered design.

In this episode of the Humans Plus AI podcast, Ross Dawson speaks with Matt Beane, author of The Skill Code, about how artificial intelligence is disrupting traditional paths to skill development. Beane shares insights from over a decade of research, revealing that true skill-building doesn't come from formal training alone, but from solving complex problems with expert support. He introduces the “Three Cs” framework—Challenge, Complexity, and Connection—as essential conditions for meaningful learning at work. As AI systems increasingly enable experts to work independently, junior professionals are often cut out of critical learning opportunities, threatening long-term talent pipelines.

The conversation explores innovative strategies to reverse this trend, such as “inverted apprenticeships” and AI-assisted workflows that still involve and upskill junior team members. Beane highlights real-world examples from fields like surgery, software development, and investment banking, illustrating how organizations can re-engineer work to preserve learning while boosting productivity. He urges leaders to demand more from AI vendors—specifically tools that enhance user skill over time—and warns of the long-term cost of neglecting employee growth. This is a must-listen for anyone focused on the future of work, talent development, and human-AI collaboration.

In this insightful conversation, Ross Dawson reconnects with tech pioneer Tim O’Reilly to explore the transformative power of artificial intelligence and its parallels with previous technological revolutions. O’Reilly emphasizes that AI represents a profound shift in how humans interact with machines — continuing a historical trend of lowering the barriers to computation and creativity. Rather than framing AI as a job-destroying force, he urges a perspective that highlights new capabilities, expanded access, and human-machine collaboration. Drawing comparisons to the disruptive impact of the printing press, O’Reilly underscores how democratizing tools lead to periods of upheaval but ultimately unlock greater societal advancement.

The discussion also delves into the concept of “architecture of participation,” where innovation thrives not just through open source code but through communities that share knowledge and build together. O’Reilly warns against the “enshittification” of platforms driven by capital over value creation, advocating for AI development that prioritizes user empowerment and cooperation over monopoly control. With examples from industry, open source history, and his own company’s journey, he illustrates how organizations can become AI-native by fostering curiosity, allowing grassroots innovation, and enabling teams to co-evolve with the technology — turning collective learning into lasting transformation.

In this insightful conversation, anthropologist and former professional rugby player Jacob Taylor shares how his unique background informs his work on collective intelligence and the Sustainable Development Goals (SDGs). Drawing from his experiences at the Brookings Institution and initiatives like 17 Rooms, Jacob explains how fostering collaboration through “rooms” aligned with each SDG enables action-focused teamwork across sectors. He emphasizes that intelligence emerges through action and shared goals, and introduces the importance of ritual, community bonding, and feedback loops as mechanisms to strengthen learning and coordination in teams.

The discussion dives into innovative concepts like "vibe teaming"—a new model of using AI collaboratively to synthesize expert insights—and explores the potential of digital twins to represent communities, ecosystems, and even non-human species. Jacob highlights real-world pilots of “interspecies money,” where AI-inferred preferences of gorillas, elephants, and trees influence how funds are used to protect habitats. Ultimately, the episode envisions a future where AI is built bottom-up to serve human and planetary flourishing, powered by a new ecosystem of aligned technologies, inclusive experimentation, and deeply human collaboration.

In this special solo episode, Ross Dawson shares key reflections from his participation in Human Tech Week in San Francisco, where he delivered the opening keynote and led a panel discussion with John Hagel and Charlene Li on the future of strategy. Drawing from that rich conversation, Ross explores how AI is reshaping the strategic landscape—accelerating decision cycles, decentralizing innovation, and emphasizing the uniquely human capabilities of judgment, synthesis, and sense-making.

He delves into themes such as the erosion of institutional trust, the shifting role of leadership, and the balance between long-term vision and short-term action. Highlighting the importance of trust-based relationships, storytelling, and continuous learning, Ross argues that strategy in the AI era must serve not only organizations but also the broader ecosystems and communities they’re part of. He invites listeners to engage with the Humans Plus AI community and continue the conversation as we navigate this rapidly evolving future together.

In this insightful conversation, Ross Dawson interviews Matt Lewis, a leading voice in brain capital and mental health innovation. Drawing on nearly two decades of experience in AI and neuroscience, Matt shares how technologies like machine learning and generative AI are being used to identify patterns in mental health, personalize interventions, and support cognitive well-being. He emphasizes the importance of seeing individuals in their full context—beyond clinical data—while discussing the shift toward lived-experience-driven solutions and the growing role of citizen data scientists in shaping more responsive care systems.

The discussion also explores the potential and risks of generative AI in mental health—from offering companionship to the lonely, to the danger of reinforcing cognitive distortions in vulnerable users. Matt introduces the concept of "brain capital," a framework centered on enhancing individual and societal cognitive capacity for a better future. He shares his optimistic outlook on the decade ahead, calling for moonshot goals like eradicating mental illness and preventing brain disorders, while describing his venture studio’s mission to support entrepreneurs building toward that vision.