Featuring scholarly and practitioner insights from HR and people leaders, industry experts, and researchers.

In this HCI Webinar, I talk with Keith Metcalfe about why AI's productivity promise isn't materializing. Keith Metcalfe, President at Acorn, is a 25-year enterprise software operator with a practical lens on scaling organizations through skill development, not just technology for its own sake. At Acorn, his philosophy centers on tying learning and performance management together, making sure that technology adoption improves capability and backs up top-down promises with measurable, positive outcomes.

This video explores the rapid transformation of the global workforce driven by technology, demographic shifts, and environmental challenges. By 2030, over 85% of workers will need to adapt to new job roles, emphasizing the importance of lifelong learning. Traditional top-down training models have become obsolete, giving way to person-centered, flexible learning approaches that empower individuals to proactively upskill and remain employable. This is vital as the workforce diversifies with growing numbers of older employees, gig workers, migrants, and displaced individuals—a range of groups facing unique barriers such as digital divides, unrecognized credentials, and lack of access to systematic training. Overcoming these challenges requires a collaborative ecosystem involving companies, communities, and governments focused on credential recognition, inclusive learning environments, and the integration of skills development into daily life. Workers are encouraged to regularly assess their abilities and cultivate continuous learning habits through a mix of online resources, mentoring, and networking. Organizations must transition from controlling access to learning to facilitating growth cultures that prioritize curiosity, psychological safety, and equitable access to both technical and human (soft) skills. Ultimately, this shift transforms workforce disruption into a shared opportunity for inclusive, lifelong growth and adaptability in the evolving world of work. Highlights 🌍 Over 85% of the global workforce will need to transition into new job types by 2030 due to technological and environmental changes. 💡 Lifelong learning is essential—people must learn, unlearn, and relearn continuously to stay relevant. 👩‍💻 Person-centered learning empowers individuals to proactively develop skills aligned with personal and professional needs. 👵 Older workers and gig workers need tailored strategies to overcome stereotypes and lack of formal training pathways. 🌐 Digital divides leave a third of the world offline, creating unequal access to upskilling opportunities. 🤝 Creating an ecosystem of companies, governments, and communities is key to inclusive, accessible lifelong learning. 🚀 Organizations must foster cultures of curiosity, psychological safety, and flexible learning to turn disruption into opportunity. Key Insights 🚀 The pace of workforce transformation demands proactive skill adaptation: By 2030, more than 85% of workers will confront new types of roles shaped by AI and other technologies. This demands not only initial training but constant adaptation, highlighting the necessity of fostering a mindset oriented around lifelong learning where individuals take ownership of their growth trajectories rather than passively waiting for employer initiatives. This proactive learning approach is crucial in future-proofing careers. 👥 Person-centered learning shifts power to the learner: Traditional workplace training, often rigid and top-down, is becoming obsolete. Instead, a paradigm where learning is flexible, personalized, and responsive to complex personal circumstances—such as caregiving or multitasking—is emerging. This shift acknowledges that workers are holistic individuals with diverse needs and learning styles, and thus require access to varied formats like mobile learning or microlearning that fit seamlessly into daily life. The example of Maria, a graphic designer using AI tools, symbolizes this personalized empowerment. 👵 Demographic changes create unique reskilling challenges for older workers: Older employees form the fastest-growing segment of the workforce, carrying valuable experience but also facing stereotypes and digital skill gaps. Effective learning initiatives must be age-inclusive, leveraging their existing competencies while addressing barriers such as prejudice or technological unfamiliarity through tailored upskilling pathways and intergenerational mentoring programs. 🧑‍💼 Gig workers constitute a significant but underserved segment regarding skill development: Over 60% of the global workforce now engages in gig or freelance work, typically without access to employer-sponsored career support and training. This group must depend on self-directed learning yet often faces time and resource constraints, underscoring the importance of accessible, affordable, and flexible learning opportunities that respect the realities of gig work. 🌐 The digital divide exacerbates inequality in lifelong learning access: Despite the growth of online education, about one-third of the global population remains offline. Even in well-resourced countries, unreliable internet limits equitable digital skill acquisition. Without addressing infrastructure gaps and digital literacy, these divides will deepen socioeconomic inequities, making universal access to online learning platforms a critical policy and corporate priority.

This research examines the necessary shift from organization-centered training to person-centered learning in response to a volatile modern workforce. It identifies five primary drivers of disruption: technological acceleration, demographic aging, climate change displacement, precarious work arrangements, and the rise of remote environments. The research argues that traditional models fail to support marginalized populations, such as gig workers and migrants, who lack access to formal corporate resources. Consequently, the research advocates for integrated frameworks that prioritize individual self-directed learning and metacognitive skills to ensure long-term employability. Finally, the research offers evidence-based recommendations for leaders and policymakers to build more equitable learning ecosystems that can withstand continuous economic and environmental change.

In this podcast episode, Dr. Jonathan H. Westover talks with Keith Metcalfe about why AI's productivity promise isn't materializing. Keith Metcalfe, President at Acorn, is a 25-year enterprise software operator with a practical lens on scaling organizations through skill development, not just technology for its own sake. At Acorn, his philosophy centers on tying learning and performance management together, making sure that technology adoption improves capability and backs up top-down promises with measurable, positive outcomes. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this HCI Webinar, I talk with Benji Wiedemann and Alex Lampe about driving organizational change from within. Benji Wiedemann is co-founder and Executive Creative Director at brand and business consultancy Wiedemann Lampe. He brings over two decades of experience to help brands and organizations unlock cultural impact at scale. Alongside co-founder Alex Lampe, Benji created Lemonade, an enterprise-grade digital platform designed to enhance collaboration and communication between teams, businesses, and communities throughout the creative process, driving deep-rooted and meaningful business transformation. Alex Lampe is co-founder and Executive Strategy & Innovation Director at brand and business consultancy Wiedemann Lampe. He brings over two decades of experience in building brands, digital ecosystems and tools that help organizations unlock transformation through design thinking, innovation, service design, and experiential design, while crafting and protecting their unique cultural identities.

The widespread narrative that artificial intelligence (AI) will eliminate human jobs and make workers obsolete is challenged by Dr. Jonathan H. Westover's research, which analyzes data from over 21,000 U.S. firms. Contrary to fears of AI-triggered job losses, companies that deeply invest in AI experience significant employment growth. These high-intensity adopters of AI integrate the technology into core operations, redesign workflows, and invest in employee training, which leads to about a 10% increase in employment within two years. Importantly, entry-level jobs are not disappearing but growing by 12% in these AI-driven firms, as automation of routine tasks frees workers for more meaningful, human-centric roles. The AI-related job growth is especially pronounced in sectors like information software, internet services, and data, where a tech-savvy culture accelerates AI integration. Highlights 🤖 Data from 21,000 U.S. firms shows AI adoption leads to employment growth, not layoffs. 📈 High-intensity AI adopters see a 10% workforce increase within two years. 👶 Entry-level jobs grow by 12% in firms deeply utilizing AI. 💼 AI automates routine tasks, freeing humans for higher-value work. 💡 The biggest AI benefits require strategic, deep integration and employee training. ⏳ Job growth effects appear 6 to 12 months after AI investment; patience is key. 🌐 Tech sectors lead AI-driven employment growth due to culture and readiness for change. Key Insights 🤝 AI as a Job Creator, Not a Job Destroyer: Dr. Westover's extensive research reveals a fundamental shift in understanding AI’s economic impact. Instead of replacing employees, companies that invest seriously in AI create new roles and expand their workforce. This runs counter to the dominant public narrative and suggests policymakers and businesses should rethink fears about AI-induced unemployment. 🎯 High-Intensity vs. Low-Intensity AI Adoption: The intensity of AI use drastically alters its impact on jobs. Firms that just dabble with AI see minimal change, but companies that commit deeply—embedding AI into workflows, training employees, and building strategy around it—unlock significantly higher employment growth (10% in two years). This implies that AI's benefits are contingent on organizational readiness and vision. 🚀 Entry-Level Job Growth and Workforce Accessibility: Rather than eliminating entry jobs, AI firms actually boost entry-level opportunities by 12%. This challenges concerns that AI displaces newcomers, instead showing that automation of routine work allows human workers to focus on higher-value, creative, or interpersonal tasks, thus expanding the foundation of career ladders. For new workforce entrants, becoming adept at working alongside AI is critical. ⏳ Delayed Impact and Integration Time: AI-driven job growth is not immediate; it typically takes 6 to 12 months post-investment before employment benefits emerge. During this period, companies undergo workflow redesign, employee training, and technology integration, shifting the perception of AI adoption from a quick fix to a long-term strategic transformation requiring patience and ongoing capacity building. 🌍 Sector-Specific Growth Patterns: The strongest employment growth associated with AI adoption is concentrated in tech-savvy industries like information software, internet services, and data. These sectors benefit from a culture of innovation, clearer use cases for AI, and openness to rapid change, which accelerates growth. Other sectors must prepare to replicate these conditions to harness similar benefits. 📚 Worker Adaptability and Continuous Learning: The new landscape demands AI literacy for all workers—not necessarily programming skills but the ability to use AI tools effectively to augment uniquely human capabilities. This shifts the paradigm of job security toward continuous upskilling and adaptability, emphasizing lifelong learning and proactive engagement with AI technologies. 🌟 Human-AI Collaboration as the Future of Work: AI is not a substitute but a partner to human labor. The future described by Dr. Westover is one of enhanced collaboration where AI handles routine or data-intensive tasks while humans take on complex, creative, strategic, or interpersonal roles. This collaboration expands opportunities and redefines human labor in an AI-driven economy, fostering a more dynamic and inclusive job market.

This research investigates how corporate AI investment affects hiring and job growth by analyzing spending data from over 20,000 American companies. The findings reveal that high-intensity AI adoption correlates with a 10% increase in employment, directly contradicting fears of immediate workforce displacement. These gains are primarily concentrated in the Information sector and among firms that move beyond experimentation to make substantial, sustained financial commitments. Interestingly, the growth extends to entry-level positions and various business functions, including sales and engineering, rather than just technical roles. However, the study notes that these positive effects emerge gradually and are currently limited to well-resourced organizations capable of supporting significant technological integration. Ultimately, the research suggests that AI acts more as a catalyst for organizational expansion than a tool for labor reduction.

This research examines the necessary shift from organization-centered training to person-centered learning in response to a volatile modern workforce. It identifies five primary drivers of disruption: technological acceleration, demographic aging, climate change displacement, precarious work arrangements, and the rise of remote environments. The research argues that traditional models fail to support marginalized populations, such as gig workers and migrants, who lack access to formal corporate resources. Consequently, the research advocates for integrated frameworks that prioritize individual self-directed learning and metacognitive skills to ensure long-term employability. Finally, the research offers evidence-based recommendations for leaders and policymakers to build more equitable learning ecosystems that can withstand continuous economic and environmental change. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.