Insight Jam Launches Mesh Lab to Frame Learning and Work for AI

Insight Jam announced the launch of Mesh Lab, a year-long series of monthly expert panel discussions dedicated to re-engineering how humans learn and work in this AI moment.

Insight Jam officially announced the launch of its Mesh Lab, a year-long, monthly series of expert panel discussions focused on re-engineering how humans learn and work as artificial intelligence becomes embedded across society. The forum launched today with episode 1 and will run through the December of 2026.

The rapid acceleration of AI is exposing a growing structural gap between how humans are educated, how work is organized, and how value is created. Frameworks that once governed learning, assessment, credentialing, and workforce development were designed for a pre-AI world—one in which knowledge was scarce, memorization signaled mastery, and career readiness followed a linear path. As AI increasingly automates and augments cognitive tasks, these systems will quickly become obsolete.

Mesh Lab was created to address this challenge at a foundational level. Rather than reacting to individual tools or short-term trends, the series is designed to initiate a sustained, cross-sector conversation about how human capability itself must be re-architected in an AI-first world. The goal is to build the intellectual groundwork required to navigate the next decade responsibly.

“AI is moving faster than our frameworks”, said Solutions Review President Doug Atkinson. “The future of work and learning depends on whether we redesign the models that shape human development before the technology defines them for us.”

The series intentionally focuses on three domains where the strain on legacy systems is most visible and urgent.

This includes Grades 6+ education, where traditional approaches to assessment, curriculum, and readiness no longer reflect real human capability in an AI-present environment. It also includes higher education, where credentials, instruction, and institutional value are being challenged by AI-mediated access to knowledge and skills. Mesh Lab addresses the corporate workforce as well, where reskilling, upskilling, and leadership development must evolve from episodic training models to continuous capability building.

By bringing these domains into a single, ongoing conversation, Mesh Lab aims to surface shared challenges and avoid siloed solutions that fail to scale across education and enterprise.

The inaugural Mesh Lab session, titled Re-Engineering Learning & Work in the Age of AI, establishes the intellectual foundation for the series, and is available to watch free on Insight Jam now. The opening discussion convenes leaders whose work spans K–12 education, higher education, enterprise learning, AI-enabled curriculum design, and human-centered leadership.

Episode 1 is moderated by Michelle Ament, Co-President and Chief Academic Officer at ProSolve and Co-President of the Human Intelligence Movement, whose work focuses on rethinking assessment, learning design, and readiness beginning in middle school and extending through adulthood.

The first panel also includes T. Scott Clendaniel, LinkedIn Learning Instructor and AI Research Mentor at the Wharton School and Chief Learning Officer at Nautilus AI; Sandra Watts, PhD, Academic Director at the UNC Charlotte School of Professional Studies; Ben Tasker, Senior AI Learning Strategist at National Grid and former AI Technical Product Manager at Southern New Hampshire University; Paul Carney, AI Educator and Founder of The AI Klatch and ishtot inc; and Evan Harrel COO from Centers for Compassionate Leadership, bringing a human-centered leadership and ethics perspective to the discussion.

Together, the panel will explore where current learning and workforce models are breaking down, where early signals of more adaptive frameworks are emerging, and what principles should guide the redesign of systems that shape human development. The conversation is anchored by a central question that will guide the Mesh Lab series through 2026: What must be re-engineered first—and what must be protected—if learning and work are to remain meaningfully human in the age of AI?

Each Mesh Lab session will build on the last, allowing insights, tensions, and design principles to accumulate over time into a shared, evolving framework which Solutions Review editors will bring to market in Q1, 2027. Rather than aiming for immediate solutions or consensus, the series prioritizes clarity—surfacing structural issues, identifying human-centered priorities, and documenting emerging patterns across sectors.

Watch episode 1 of the Mesh Lab here.