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.