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

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examinations. These innovative approaches allow institutions to focus on continuous behavioral data and situated skill application through AI personas, moving away from high-stakes, one-time testing. The research emphasize that building resilient assessment systems requires institutional investment in expertise and a cultural shift toward assessment for learning. Ultimately, the research suggests that AI democratizes access to sophisticated evaluation tools that better measure genuine human capability and professional readiness. This transition addresses a long-standing validity crisis by aligning educational outcomes with real-world complexities.

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examinations. These innovative approaches allow institutions to focus on continuous behavioral data and situated skill application through AI personas, moving away from high-stakes, one-time testing. The research emphasize that building resilient assessment systems requires institutional investment in expertise and a cultural shift toward assessment for learning. Ultimately, the research suggests that AI democratizes access to sophisticated evaluation tools that better measure genuine human capability and professional readiness. This transition addresses a long-standing validity crisis by aligning educational outcomes with real-world complexities.

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examinations. These innovative approaches allow institutions to focus on continuous behavioral data and situated skill application through AI personas, moving away from high-stakes, one-time testing. The research emphasize that building resilient assessment systems requires institutional investment in expertise and a cultural shift toward assessment for learning. Ultimately, the research suggests that AI democratizes access to sophisticated evaluation tools that better measure genuine human capability and professional readiness. This transition addresses a long-standing validity crisis by aligning educational outcomes with real-world complexities. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examinations. These innovative approaches allow institutions to focus on continuous behavioral data and situated skill application through AI personas, moving away from high-stakes, one-time testing. The research emphasize that building resilient assessment systems requires institutional investment in expertise and a cultural shift toward assessment for learning. Ultimately, the research suggests that AI democratizes access to sophisticated evaluation tools that better measure genuine human capability and professional readiness. This transition addresses a long-standing validity crisis by aligning educational outcomes with real-world complexities. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This research explores how generative artificial intelligence has disrupted traditional educational and corporate testing by exposing the flaws of outdated, easily automated evaluation methods. Rather than signifying the end of assessment, the research argues that AI enables a transition toward more authentic and scalable alternatives, such as process-oriented evaluation and AI-driven oral examinations. These innovative approaches allow institutions to focus on continuous behavioral data and situated skill application through AI personas, moving away from high-stakes, one-time testing. The research emphasize that building resilient assessment systems requires institutional investment in expertise and a cultural shift toward assessment for learning. Ultimately, the research suggests that AI democratizes access to sophisticated evaluation tools that better measure genuine human capability and professional readiness. This transition addresses a long-standing validity crisis by aligning educational outcomes with real-world complexities. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Abstract: The emergence of generative artificial intelligence has fundamentally disrupted traditional assessment practices in higher education and corporate learning and development. This article examines how AI has simultaneously destabilized century-old assessment methods while enabling more authentic, scalable alternatives. Drawing on recent empirical evidence and organizational case examples across education and industry, we analyze four major shifts reshaping assessment design: process-oriented evaluation, AI-enhanced oral examinations, AI personas for situated skill assessment, and continuous behavioral assessment. Rather than representing assessment's demise, AI has exposed the inherent limitations of conventional methods while dramatically reducing the cost barriers to implementing more valid alternatives. We synthesize evidence-based organizational responses and propose a framework for building assessment systems that leverage AI to better measure learning, skill development, and performance. The findings suggest that AI has not broken assessment—it has broken the economics of inadequate assessment, creating unprecedented opportunities to align evaluation methods with learning outcomes that matter. 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 Larry Durham about his new book, The Judgment Void: How AI Is Dismantling the One Human Capability It Cannot Replace. Larry Durham is President of St. Charles Consulting Group and a recognized leader in enterprise learning and talent development. Over 30years, he has partnered with large professional services firms and Fortune 500companies to build innovative talent solutions that deliver measurable results. Before founding St. Charles, Larry spent a decade at PwC as Learning Practice Leader within Human Capital Advisory Services. He is also co-author of The Talent-Fueled Enterprise.

This research examines Meta’s recent decision to reduce manager workloads by capping the number of direct reports, signaling a retreat from using AI as a substitute for human leadership. The research explores how excessive span of control leads to organizational "chaos," including managerial burnout, stifled innovation, and diminished employee engagement. Research suggests that while technology can assist with administrative tasks, it cannot replace the relational and developmental coaching essential for complex, creative work. To maintain healthy teams, the research advocates for right-sizing leadership structures based on task difficulty rather than cost-cutting alone. Ultimately, the source serves as a cautionary case study on the limits of digital management and the enduring necessity of human connection in organizational design.