In this HCI Webinar, I talk with with Shahar Botzer about the future of social impact investing and current trends and opportunities. Shahar Botzer is co-founder and managing partner at Good Company, an early-stage VC fund with a mission to back bold entrepreneurs who solve the world’s biggest challenges for people and the planet. They invest in software-driven innovations in Digital Health, Education, Energy, Circular Economy, and Agriculture because they believe these are the domains where technology can rewrite the future.

In this HCI Webinar, I talk with Jordan Hammerstad about the new report out from the Josh Bersin company, The Definitive Guide to Corporate Learning. Jordan Hammerstad is Associate Director of Research at The Josh Bersin Company, where she leads the L&D Roundtable—an executive forum driving corporate learning innovation. Passionate about the intersection of behavioral sciences and the workplace, she pursued a bachelor's degree in neuroscience before obtaining her master's in human resources. As a certified HR practitioner, Jordan brings experience from multiple industries, including commercial real estate, higher education, industrial automation, retail, and transportation. Her research focuses on learning and development—notably dynamic skilling, performance enablement, and AI-first corporate learning transformations.

In today’s fast-evolving business environment, effective leadership requires mastering two essential tools: the microscope and the telescope. The microscope focuses on immediate, urgent challenges such as supply chain disruptions, inflation, and cyber threats, while the telescope provides a long-range view of transformative trends including AI, the low-carbon transition, and shifting geopolitics. Leaders must continuously shift between managing pressing short-term risks and cultivating a strategic long-term vision. Despite rising anxiety and defensive tendencies among CEOs—manifested in cost-cutting, risk aversion, and delaying investments—dynamic reinvention is the superior path. Organizations that embrace bold, strategic bets and transformative initiatives outperform those that cling to caution. Highlights 🔬 Leaders need the microscope to manage immediate threats like supply chain disruptions and cyber risks. 🔭 The telescope enables leaders to anticipate and shape future trends such as AI and climate transition. ⚖️ Balancing urgent short-term pressures with long-term vision is crucial for sustainable success. 🚀 Dynamic reinvention through bold strategic bets outperforms cautious defense strategies. 🤖 Building an enterprise-wide AI foundation is essential for competitive advantage. 🌍 Embedding climate risk and opportunity into business decisions is becoming a material imperative. 🤝 Trust in data, AI fairness, climate impact, and workforce commitments underpins long-term resilience. Key Insights 🔬 Microscope vs. Telescope Leadership: The metaphor of the microscope and telescope encapsulates the dual focus leaders must maintain—addressing immediate operational crises while simultaneously envisioning and preparing for transformative shifts. This duality is not just a conceptual framework but a practical leadership imperative, as neglecting either focus risks organizational failure. Immediate problems demand vigilance, but long-term success requires strategic foresight. 📉 CEO Confidence and Defensive Posture: The sharp decline in global CEO confidence reflects heightened uncertainty driven by geopolitical tensions, inflation, and cyber threats. This anxiety often leads to defensive tactics like cost-cutting and risk avoidance, which may safeguard short-term stability but hinder growth and innovation. This insight highlights the need for leaders to resist reflexive defensiveness and instead embrace calculated risks. 🚀 Dynamic Reinvention as a Growth Driver: Firms that proactively reinvent themselves by making bold strategic moves, investing in transformative technologies like AI, and exploring new markets consistently achieve higher growth and profitability. This underscores that in volatile environments, the greatest risk is inertia. Organizations must transition from a reactive posture to an offensive, opportunity-driven mindset. 🤖 Enterprise-wide AI Foundation: Many organizations experiment with AI pilots but fail to scale. Treating AI as a core enterprise capability involves cleaning and integrating data, establishing robust systems, and embedding AI into workflows. This foundational work is critical to unlocking AI’s transformative potential rather than relegating it to isolated experiments. 🌐 Cross-sector Expansion: Traditional industry boundaries are blurring, enabling companies to leverage their unique strengths to enter adjacent or entirely new sectors. For example, retailers moving into healthcare or financial firms becoming cloud providers illustrates the growing importance of ecosystem thinking and platform business models. Strategic sector expansion can unlock new revenue streams and competitive moats. 🌿 Climate Integration in Strategy: Climate change represents both a significant risk and an opportunity. Embedding climate considerations into all decision-making processes—from risk management to market exploration—ensures that organizations can mitigate vulnerabilities while capitalizing on emerging green markets. This dual approach positions companies for resilience and relevance in a rapidly decarbonizing economy. 🤝 Building Trust as a Strategic Asset: Long-term success depends on cultivating trust regarding data privacy, AI fairness, climate impact, and workforce practices. Stakeholders increasingly demand transparency and accountability in these areas. Organizations that proactively build and protect trust create durable reputational capital, foster stakeholder loyalty, and reduce regulatory and social risks. If this helped, please like and share the video. #Leadership #AI #CEO #BusinessStrategy #Innovation #ClimateRisk OUTLINE: 00:00:00 - Microscope vs Telescope 00:00:42 - The Confidence Crisis and the Reinvention Imperative 00:01:40 - Five Frontiers for Long-Term Victory 00:02:40 - Practical Steps for Strategic Action 00:03:27 - Balancing the Now and the Next

This video explores the emerging phenomenon of “AI brain fry,” a specific form of cognitive exhaustion experienced by knowledge workers in the modern workplace due to the pervasive integration of artificial intelligence tools. While AI promises enhanced productivity by automating tasks such as drafting emails, generating reports, and brainstorming ideas, it simultaneously imposes unique cognitive demands that lead to mental fatigue, reduced decision quality, and diminished creativity. This mental exhaustion stems from three primary factors: the overwhelming volume of AI-generated information, the frequent context switching demanded by diverse AI tasks, and the relentless need for high-stakes oversight to catch AI errors and biases. The consequences of AI brain fry are significant, including suboptimal decision-making, increased errors, missed deadlines, stress, burnout, and erosion of collective intelligence. Highlights 🤯 Introduction of the term “AI brain fry,” describing a novel cognitive exhaustion linked to AI interaction. 📊 Three main causes of mental fatigue: information overload, task-switching, and constant oversight. 🧠 Cognitive depletion leads to poor decision-making, missed deadlines, and increased errors. ⚠️ Oversight fatigue paradoxically increases the risk of mistakes slipping through. 🔄 Recommendations include focused AI tasks, intelligent oversight, and scheduled recovery periods. 📚 Emphasis on AI literacy and understanding inherent AI biases and limitations. 🔧 Advocacy for limiting AI tools to cultivate deeper expertise and sustainable workflows. Key Insights 🤖 AI Brain Fry as a Cognitive Phenomenon: The concept of AI brain fry highlights that the integration of AI into work processes introduces a new form of mental exhaustion that goes beyond traditional tiredness. This is not just fatigue but a cognitive overload caused by the need to constantly supervise and collaborate with AI, requiring new mental faculties and strategies. Recognizing AI brain fry is crucial for designing healthier AI-human workflows. 📈 Information Overload Outpaces Human Processing: AI can generate vast amounts of information in seconds, but human cognition has not evolved to evaluate and process such volumes efficiently. This mismatch creates bottlenecks where time saved in AI generation is lost in human evaluation, leading to cognitive paralysis and decreased productivity. Organizations must rethink expectations around AI output volume and human processing capacity. 🔄 Context Switching as a Major Cognitive Drain: The frequent switching between different AI-supported tasks—such as drafting emails, legal documents, and social media plans—creates attention residue that diminishes focus and depth of thinking. This shallow engagement hampers creativity and problem-solving, revealing that AI-induced multitasking has hidden costs on cognitive coherence and mental well-being. 👁️ High-Stakes Oversight Erodes Mental Resources: Because AI outputs can be flawed or biased, humans must act as vigilant auditors. This hypervigilance is mentally taxing and ironically can reduce oversight effectiveness as fatigue sets in, increasing the risk of errors and bias slipping through. This insight urges a redesign of oversight protocols that balance thoroughness with cognitive sustainability. ⚡ Performance and Well-being are Intertwined: Cognitive depletion due to AI brain fry directly reduces decision quality, innovation, and timeliness, while simultaneously increasing stress, anxiety, and burnout risk. This dual impact threatens both individual well-being and organizational performance, making cognitive health a critical metric alongside productivity. 🎯 Targeted AI Usage Mitigates Cognitive Load: Limiting AI requests to single, well-defined tasks with clear constraints (such as tone, purpose, and audience) reduces the mental effort required for evaluation and increases output relevance. This approach promotes smarter AI-human interaction, emphasizing quality over quantity of AI-generated content. 📚 Education and Governance are Key to Sustainable AI Integration: Building AI literacy, including understanding AI’s limitations and biases, empowers users to interact with tools more effectively and critically. Moreover, limiting the number of AI tools and appointing specialized AI reviewers for quality control fosters deep expertise, reducing cognitive fragmentation and enabling a more balanced, sustainable partnership between humans and AI. Like and share if this helped your team. #AI #CognitiveLoad #WorkplaceProductivity #HumanAICollaboration #BrainFry #AIManagement OUTLINE: 00:00:00 - Defining AI Brain Fry 00:01:23 - Why Our Brains Are Short-Circuiting 00:02:35 - Tangible Effects on Performance and Well-Being 00:03:48 - Reclaiming Cognitive Sanity and Sustainable AI Partnership

This research explores the phenomenon of AI brain fry, a specialized form of mental exhaustion caused by the excessive use and management of artificial intelligence in the workplace. Research indicates that while these tools aim to boost efficiency, they often trigger cognitive overload due to the constant need for output verification, frequent task-switching, and information saturation. This strain results in significant negative outcomes, including decision fatigue, decreased employee well-being, and a higher intent to quit among staff. To combat these issues, the research suggests that organizations must prioritize human-centered design by implementing structured oversight protocols and scheduled recovery periods. Ultimately, the research argues for a shift in strategy where technology augments human capabilities rather than simply increasing the volume of work beyond biological limits. Proper AI governance and literacy are presented as essential components for maintaining a sustainable and productive modern workforce.

This research explores the strategic paradox facing modern executives who must balance immediate financial pressures with the necessity of long-term organizational transformation. According to recent survey data, leaders who embrace dynamic reinvention—specifically through artificial intelligence deployment and cross-sector expansion—achieve significantly higher profitability than those who adopt defensive postures. A critical theme is the "attention crisis," where CEOs struggle to allocate time between short-term threats like cybersecurity and the multi-year commitments required for innovation. The research also quantifies the high financial value of stakeholder trust, noting that organizations with strong digital and operational integrity see better shareholder returns. Ultimately, the research argues that future success depends on building enterprise-scale foundations for emerging technologies while cultivating an agile, purpose-driven workforce. Effective leadership in 2026 requires mastering both the "microscope" of daily operations and the "telescope" of strategic evolution.

In this podcast episode, Dr. Jonathan H. Westover talks with Jordan Hammerstad about the new report out from the Josh Bersin company, The Definitive Guide to Corporate Learning. Jordan Hammerstad is Associate Director of Research at The Josh Bersin Company, where she leads the L&D Roundtable—an executive forum driving corporate learning innovation. Passionate about the intersection of behavioral sciences and the workplace, she pursued a bachelor's degree in neuroscience before obtaining her master's in human resources. As a certified HR practitioner, Jordan brings experience from multiple industries, including commercial real estate, higher education, industrial automation, retail, and transportation. Her research focuses on learning and development—notably dynamic skilling, performance enablement, and AI-first corporate learning transformations. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This conversation explores the phenomenon of AI brain fry, a specialized form of mental exhaustion caused by the excessive use and management of artificial intelligence in the workplace. Research indicates that while these tools aim to boost efficiency, they often trigger cognitive overload due to the constant need for output verification, frequent task-switching, and information saturation. This strain results in significant negative outcomes, including decision fatigue, decreased employee well-being, and a higher intent to quit among staff. To combat these issues, they suggest that organizations must prioritize human-centered design by implementing structured oversight protocols and scheduled recovery periods. Ultimately, they argue for a shift in strategy where technology augments human capabilities rather than simply increasing the volume of work beyond biological limits. Proper AI governance and literacy are presented as essential components for maintaining a sustainable and productive modern workforce. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.