AI and the Erosion of Judgement

AI and the Erosion of Judgement

Jelena Marjanović, an AI adoption strategist and learning expert, explores the growing risk of AI and the erosion of human judgment. Drawing on more than 15 years of experience in learning and development, she explains why relying too heavily on AI can weaken critical thinking and why organizations need to teach people to think with AI—not simply accept its answers. Tune in to hear her insights on the dangers of AI over-reliance, the difference between polished outputs and quality outcomes, and how businesses can build the judgment and decision-making skills needed to thrive in an AI-driven world. Connect with Jelena on LinkedIn [https://www.linkedin.com/in/marjanovicjelena/] or by email [info@jelenamarjanovic.com] to continue the conversation. Show Notes [00:26] Introducing Jelena MarjanovićJelena Marjanović is an AI adoption strategist and learning expert with more than 15 years of experience in learning and development. She helps organizations implement AI in ways that improve workflows while keeping people, learning, and long-term adoption at the center of the process. [03:19] The Risk of Cognitive DecayJelena explains why growing reliance on generative AI can gradually weaken critical thinking. While AI offers significant efficiency gains, she warns that delegating judgment to polished AI outputs without careful evaluation can lead to cognitive decay, particularly for leaders making high-stakes decisions. [05:33] Understanding the AI Over-Reliance Curve She introduces the "over-reliance curve," describing how many users move from initial excitement to over dependence before reaching a turning point. The most successful users, she explains, learn to question AI outputs and use the technology to strengthen their own thinking rather than replace it. [10:29] Why Critical Judgment Still MattersJelena emphasizes that domain expertise alone isn't enough when working with AI. Even experienced professionals must deliberately analyze and challenge AI-generated content instead of accepting polished responses at face value. [12:15] Recognizing Quality Beyond Polished ContentShe discusses why effective learning requires more than well-written outputs. Without a clear understanding of what quality looks like, organizations risk producing training that appears professional but fails to improve performance or achieve business goals. [16:08] Learning and Development as a Strategic PartnerJelena argues that organizations achieve better outcomes when learning and development is treated as a strategic business function rather than simply a training provider. Embedding L&D into organizational strategy helps improve AI adoption, workforce capability, and long-term performance. [19:37] Teaching People to Think With AIShe explains that successful AI adoption requires much more than learning prompts or new tools. Organizations should build competencies around judgment, delegation, quality standards, and critical thinking so employees can collaborate effectively with AI while maintaining strong decision-making skills. [22:15] Where to Connect with Jelena MarjanovićJelena shares that listeners can connect with her through LinkedIn⁠ [https://www.linkedin.com/in/marjanovicjelena/] or by ⁠email⁠ [info@jelenamarjanovic.com], where she regularly discusses AI adoption, workplace learning, and practical strategies for helping organizations implement AI in a thoughtful, human-centered way.

Human Trust Is the New Intelligence

Ron Shah, founder and CEO of Bizly [https://www.bizly.com/] and Perch [https://www.perch.so/], explores why the future of work will depend as much on human connection as it does on artificial intelligence. A former venture capitalist and CNBC host, Ron shares his perspective on how AI will transform routine work while making trust, relationships, and collaboration more valuable than ever. Tune in to hear his insights on collective intelligence, the importance of meaningful networks, and why the biggest opportunities of the future may come from connecting people—not just advancing technology. Connect with Ron at Bizly [https://www.perch.so/], Perch [https://www.perch.so/], on LinkedIn [https://www.linkedin.com/in/mrronakshah/], or through his Substack newsletter, Rising Sun. Show Notes [00:26] Introducing Ron Shah Ron Shah is the founder and CEO of Bisly, a platform designed to facilitate in-person connections through events, and Perch, a professional networking platform focused on building deeper relationships. A former venture capitalist and CNBC host, he now focuses on creating technology that strengthens human connection in an AI-driven world. [01:33] AI Will Replace Tasks, Not Human Challenges He predicts that AI agents will eventually handle most routine tasks, from administrative work to everyday chores. By 2042, however, the greater challenges facing society will extend beyond automation to issues such as climate change, social upheaval, and evolving government systems. [02:44] The Missing Human Layer in AI Discussing the current limitations of AI, he argues that most systems operate in isolation from the human networks that drive opportunity and collaboration. While AI can generate ideas and automate workflows, it lacks awareness of the relationships, connections, and communities that help people achieve their goals. [05:44] Unlocking Human Collective Intelligence Ron introduces the concept of collective intelligence, describing it as one of the greatest untapped opportunities of the coming decades. Rather than focusing solely on advancing machine intelligence, he believes society must find better ways to combine human knowledge, perspectives, and expertise to solve complex challenges. [07:57] Expanding Human Potential Through Connection Reflecting on the future of work, he emphasizes that humans possess far more capacity than they currently utilize. Meaningful collaboration, diverse perspectives, and shared experiences will play a critical role in unlocking greater creativity, insight, and innovation. [08:46] Creating the Conditions for Better Thinking He explores how environments, experiences, and relationships influence human performance. Whether through meaningful conversations, unique settings, or exposure to different perspectives, these human elements can help uncover insights that technology alone cannot provide. [10:17] What It Means to Be Future-Ready Acknowledging the likelihood of job displacement as AI advances, he encourages individuals to identify and clearly communicate their unique expertise. Making skills, knowledge, and accomplishments visible will become increasingly important in an AI-enabled economy. [11:11] Trust as the Currency of the Future Ron predicts that trust will become one of the most valuable assets in a world filled with synthetic content and AI-generated information. As confidence in online information declines, people will increasingly rely on trusted personal and professional relationships. [11:52] Building Deeper Networks in an AI Era He argues that success will depend less on broad networks and more on meaningful connections. Re-engaging with people we already know and trust may become one of the most effective ways to find opportunities, collaborate, and navigate uncertainty. [12:49] Where to Connect with Ron Shah Listeners can learn more through Bizly⁠ [https://www.bizly.com/], ⁠Perch [https://www.perch.so/], LinkedIn⁠ [https://www.linkedin.com/in/mrronakshah/], and his Substack newsletter, Rising Sun.

The Hyper Adaptive Enterprise

Melissa Reeve explores why the biggest barrier to AI adoption is not technology, but outdated organizational systems. Drawing from her book Hyper Adaptive, she breaks down how legacy structures and silos limit adaptability and innovation. Tune in to hear her insights on AI-native organizations, value streams, AI activation hubs, and how companies can rewire roles, learning, and workflow for the future of work. Show Notes [00:25] Introducing Melissa Reeve Melissa’s book Hyper Adaptive: Rewiring the Enterprise to Become AI Native is available through major bookstores and online platforms. Listeners can also learn more about her work and insights at hyperadaptive.solutions and connect with her on LinkedIn. [01:24] The Legacy of Taylorism and Functional Silos She explains the “ghost of Frederick Taylor” and how Taylorism, originating in 1911, introduced the idea of management dictating the “one best way” of doing work. She reflects on how this mindset still exists in modern organizations and how it evolved through World War II-era functional specialization, which created silos such as sales, marketing, and finance. [03:33] AI Learning Systems and Activation Hubs Melissa explains the shift toward AI-native organizations, focusing on how roles, processes, and learning systems need to be rewired. She introduces the AI learning flywheel, where AI power users are supported to become change agents rather than working in isolation. She also describes AI activation hubs that track AI developments and distribute simplified insights across the organization to improve learning flow and break down silos. [07:04] Breaking Down Silos Through Networked Learning She explains that AI activation hubs can connect across departments, enabling knowledge to flow not only top-down but also across the organization. Insights from one area, such as legal, can be shared with finance or HR. She emphasizes that this creates a more deliberate learning system and addresses what she calls a “distribution problem” in how organizations share knowledge. [08:10] From Doing Work to Managing AI Systems Melissa explains that as organizations move toward automation, jobs shift from doing tasks to building, monitoring, and maintaining the systems that perform those tasks. She uses the washing machine analogy to show how technology changes the nature of work rather than eliminating it. She introduces the AI Impact Hub, which focuses on upskilling and helping employees transition into roles supporting AI-driven systems. [10:09] Defining AI-Native Organizations She defines AI-native as the ability to sense and respond in near real time. She explains that organizations will shift toward orchestrated value streams—cross-functional groups focused on delivering end-to-end customer value. Using a banking example, she shows how teams aligned to customer segments can respond faster and more effectively with AI support. [11:28] AI-Native Companies and Embedded AI She explains that AI-native companies, unlike legacy organizations shaped by Taylorism and silos, are structured around direct customer value delivery. In these organizations, AI agents are embedded into workflows, enabling more seamless and adaptive execution. [11:55] A Blueprint for Transformation Melissa explains that organizations already structured around value delivery and embedded AI agents may not need a full transformation model. However, for legacy enterprises, governments, and nonprofits, her framework provides a five-stage blueprint to gradually rewire people, processes, and roles to become more AI-native and remain competitive in a rapidly evolving landscape. [13:00] Where to Learn More About Melissa Reeve Melissa’s book Hyper Adaptive: Rewiring the Enterprise to Become AI Native is available through major bookstores and online platforms. Listeners can also learn more about her work and insights at hyperadaptive.solutions [https://hyperadaptive.solutions/]and connect with her on LinkedIn [https://www.linkedin.com/in/melissamreeve/].

Is Critical Thinking Overrated?

Richa Kulkarni [https://www.linkedin.com/in/richa-kulkarni-502360386/], a secondary school student in Mississauga and DECA chapter president, shares her perspective on how work, learning, and thinking may evolve by 2042. She explores a future shaped by freelancing, remote work, and project-based careers, where individuals have more freedom and flexibility in how they design their lives and careers. Tune in to hear her thoughts on AI as an extension of human thinking, the changing role of critical thinking, and why real-world experiences—from extracurriculars to everyday interactions—may become the most important foundation for future success. Show Notes [00:26] Richa Kulkarni on the Emerging Shape of Work in 2042 Richa Kulkarni is a secondary school student in Mississauga, Ontario. She is president of her DECA chapter and also active in competitive dance, balancing academics, leadership, and extracurriculars. [01:00] Why the Traditional 9–5 Model May Fade Away She believes the 9–5 job will decline, replaced by freelancing, flexible work, and multiple income streams, giving people more control over how they work. [01:31] The Rise of Remote and Flexible Work Remote and virtual work will continue growing, allowing people to design lifestyles around their careers and choose where they live. [01:56] A Shift Toward Project-Based Careers She predicts more project-based or hourly work instead of fixed salaries, along with rising entrepreneurship, especially among children of immigrants. [04:47] Rethinking Critical Thinking Critical thinking is defined as questioning, analyzing, and interpreting information rather than accepting it at face value. Its role is evolving in an AI-driven world. [05:11] AI as an Extension of Thinking AI already supports analysis and decision-making, meaning parts of thinking may be increasingly augmented by AI tools. [05:30] Building Inclusive Learning Through AI AI and wearable tech can support different learning needs and enable more personalized education. [06:00] When Skills Become Obsolete She compares critical thinking to survival skills like fire-making, noting that as technology evolves, humans shift toward higher-level thinking. [07:57] Living in an AI-Driven World AI is compared to electricity—already deeply embedded in daily life and becoming essential infrastructure. [09:42] Reimagining Education: Ideas Over Execution Students can use AI for structure and formatting so they can focus more on ideas, reasoning, and deeper thinking. [10:48] Why AI May Not Be Making Us Lazy Richa argues AI does not reduce effort, as generating ideas requires more cognitive work than mechanical execution. [11:45] The Boundaries of Machine Creativity AI accelerates existing thinking but does not create truly new ideas. Human imagination and lived experience remain essential. [15:53] Short-Form Content and Initiative Short-form content is shaping attention spans and reducing initiative among young people. [16:40] Initiative as a Key Skill Success depends on initiative—actively seeking opportunities and taking ownership of growth. [17:30] The Growing Gap in Outcomes A widening gap is forming between highly driven individuals and those who disengage. [18:08] The Real Issue The issue is not intelligence, but lack of real-world engagement and experience. [18:34] Why Real-World Experience Matters Clubs, work, and social interaction are key for developing creativity and problem-solving skills. [19:58] Declining Offline Engagement Reduced real-world engagement may weaken skill development and idea generation. [20:21] Where Creativity Comes From Creativity comes from boredom, silence, and real-world exposure. [21:51] Extracurriculars as Training Ground DECA, co-op, and sports build real-world skills through practice and interaction, not theory alone. [23:14] Experience as the True Foundation Future readiness depends less on critical thinking alone and more on lived experience shaping how people think and act.

Don’t Surrender Your Thinking

John Bennett, a lifelong entrepreneur with more than 37 years of experience, shares his perspective on how AI is reshaping the way we think and work. Having witnessed multiple waves of technological change—from e-commerce and social media to today’s AI revolution—he now focuses on helping people cut through the noise and understand how to use AI thoughtfully. Tune in to hear his insights on productive skepticism, the risk of losing critical thinking skills, and why AI should be treated as a tool—not a substitute for human judgment. Connect with John at formidably.com [https://www.formidably.com/] or explore his book Don’t Surrender Your Thinking, available through major online booksellers. Show Notes [00:26] Introducing John Bennett John Bennett is an entrepreneur with more than 37 years of experience. His journey began selling cans of Coke to classmates at school and has spanned decades of technological change—from the rise of e-commerce and social media to today’s AI revolution. Today, he focuses on helping people understand AI and cut through the noise surrounding it. [01:30] How AI Could Change Judgment at Work John believes the biggest shift AI will bring is not just automation but how people respond to it. If we “mindlessly accept what AI gives us,” we risk losing our ability to think, decide, and apply judgment. But when used critically, AI can save time and strengthen human thinking. [03:23] The Rise of “Productive Skepticism” John says critical thinking will become both more valuable and less common. He describes the skill needed in the future as productive skepticism—being open to AI outputs while still evaluating them carefully. [04:04] The Risk of Thinking Skill Atrophy John compares today’s reliance on AI to how GPS replaced map-reading skills. In the past, people mentally planned routes; today, most rely on automated directions. The same risk exists for decision-making and critical thinking if we rely too heavily on AI. [05:06] Start with Human Intent John recommends approaching AI with clear intent. Instead of treating AI responses as answers, they should be seen as drafts—refined through human expertise, judgment, and accountability. [06:22] Rebalancing AI with Human Interaction Alongside learning to work with AI, John emphasizes the importance of human connection. Conversations with colleagues, communities, and peers help validate ideas and keep work grounded in human perspective. [07:31] AI as an Amplifier John describes AI as an amplifier. If we approach work thoughtfully and critically, AI can strengthen those abilities. But if we seek shortcuts or minimal effort, AI will amplify that as well. [09:22] Choosing the Level of Thinking Working with AI requires deciding how much thinking and intervention to apply each time. Sometimes, a minimal review is enough, but the key is making a conscious choice rather than accepting outputs blindly. [11:58] Understanding What AI Really Is John explains that generative AI models are essentially pattern-prediction machines. They generate responses based on probabilities from vast datasets—they don’t truly understand the world the way humans do. [14:00] Strengthening Critical Thinking Skills The good news is that critical thinking grows through use. Curiosity, questioning assumptions, and maintaining a growth mindset help build stronger thinking over time. [15:41] Where to Learn More from John Bennett John’s book Don’t Surrender Your Thinking is available through major online booksellers. Listeners can also learn more about his work at formidably.com⁠ [https://www.formidably.com/].