MJ Petroni
Cyborg Anthropologist & Futurist
MJ Petroni
Cyborg Anthropologist & Futurist
Biography
As a Cyborg Anthropologist, MJ Petroni studied shows like Star Trek at university, but not (just) for fun. Their field of study addresses the complex relationships between humans and machines, exploring how we shape technology and how it is reshaping us. They help organizations increase their Digital Fluency in preparation for future technologies, attending not just to tools but also the thinking, skills, data and business models which comprise new value creation.
MJ's work focuses on raising the lowest common denominator of Digital Fluency for individuals, teams and entire organizations.
As Chief Exponential Officer of Causeit, Inc., MJ builds the business and technology platforms to help companies harness the power of platforms for exponential growth as a speaker, strategist and facilitator. His academic background is in a field of study called Cyborg Anthropology, which studies the relationship between humans and technology. MJ specializes in helping others understand the mental models necessary to navigate new technologies.
Since 2006, Causeit has helped transform how hundreds of clients think about and work towards the future, including Volkswagen, Swift, Google and the Omidyar Foundation. MJ was the Cyborg Anthropologist in Residence for NTT, served as a founding advisor of the Gates Foundation's digital financial platform for poverty alleviation, and is a repeat invitee to the Accenture TechVision Advisory Board. He is an alumnus of Lewis & Clark College and is currently authoring Cybiomes: Biology, Technology and Hope.
MJ sits on the Accenture Tech Vision Advisory Board and is a faculty member at Singularity University.
Speech Topics
AI Fluency: Preparing Your Company—and Yourself—for the Future
Digital transformation is creating a world where businesses must test new, exponential strategies like generative AI/ChatGPT while maintaining incremental business functions to keep the lights on. How can we manage this balance between old and new, go beyond traditional ‘change management’ and choose which path to modernization is right for us? To lead our companies in the era of AI, we need to increase our Digital Fluency. Five key areas are critical to focus on: thinking, skills, tools, data, and business models.
Learning Outcomes:
- See what an AI future might hold for your work
- Understand what it means to be digitally fluent through a simple "five pillars" model with easy-to-understand language
- Explore the Digital Fluency strategies of leading firms and how they engage in mindset change management, not just functional change management
- Learn how to quickly launch an AI Readiness & Digital Fluency program and cultivate a network of transformative thinkers inside your business
AI as a Machine Coworker: The Future of Work & Economies
What happens if we think of tech as a coworker, instead of just a tool? The prospect is both exciting and concerning. Who hires the machine coworker? Trains it? Supervises it? Fires it? No executive would let another time manage all of their employees, but in a way, that’s what many companies are doing with AI. It’s time to re-conceive of machines, while also understanding their limits, what’s next, and what it means for the future of work.
Learning Outcomes:
- Understand how generative AI LLMs (Large Language Models) 'learn'—or don't
- Explore disruptive applications of conversational and agentic AI
- Map the ethical implications of Generative AI for privacy, truth and law
- Discuss the possibilities and risks of having machines in the org chart
Generative AI in the Enterprise: Implications, Use Cases & Adoption
Conversational AIs like ChatGPT, Copilot and Gemini seem to be in every headline and LinkedIn post today. Yet implementing conversational AI in a large organization isn't as easy as just creating a free account and asking a few questions—important consideration must be given to intellectual property, ethics, governance, value propositions and digital fluency. Learn how organizations are meaningfully integrating AI into their work—and business models.
Learning Outcomes:
- Identify conversational AI opportunities
- Explore enterprise-specific use cases
- Learn how to make build/buy/partner decisions on AIs and LLMs based on your organizational DNA
- Plan digital fluency and organizational change needs for true AI adoption
Leading Exponential Initiatives: From 10% to 10X
The journey to exponential growth requires minding the gaps between your new journey and the incremental “defaults” of your organization. First, we’ll explore what ‘exponential’ really means in practice. How do we create room for exponential innovation while still making progress on incremental innovation? Learn how to transform communications around four key gaps—in vision, expectations, accountability and resources—to ensure your exponential projects aren’t blocked by incremental thinking.
Learning Outcomes:
- The difference between incremental and exponential thinking in large organizations
- How network effects work—and how to harness them for good
- How to close four key gaps between incremental and exponential thinking
○ The vision gap: make an exponential possibility accessible
○ The expectations gap: differentiate between incremental and exponential initiatives
○ The metrics gap: make progress visible and accountability possible
○ The resource gap: prepare for exponentially-increasing needs without over-investing
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