Skills are changing faster than traditional learning models can keep up — especially as AI continuously reshapes jobs and work. For Cisco, a global technology company with more than 80,000 employees, that reality demanded a more agile, strategy-aligned, and unified approach to development. Enter Edge Up: the brand behind Cisco’s bold learning transformation.

In this episode, we speak with Marci Paino, Chief Learning Officer at Cisco — a 2026 HR Pacesetter Award winner — about how her team moved from fragmented legacy learning to a unified, AI-powered skilling ecosystem. Marci walks through four key pillars of Cisco’s learning transformation: AI-powered lifelong learning mindset, Cisco’s strategic capabilities, always-on modern learning, and a unified skilling environment. She also shares the results Cisco has seen: from replacing a 20-year-old tech stack three times faster than the industry average to a culture where employees embrace continuous learning.

Marci Paino is Cisco’s Chief Learning Officer, driving AI-era workforce readiness for 80,000+ employees and leading the cross-industry AI Workforce Consortium, backed by 20+ years shaping talent development and digital transformation at companies like American Express, Accenture, and Western Digital.

We awarded Marci a JBC Pacesetter award in 2026 for her leadership and strong AI-centric focus. If you have an innovative solution you’d like to share, join our Pacesetters Program.

Additional Information

Download the Pacesetter Research

Irresistible 2027: The Global HR Conference for Leaders and Teams (Sign up now: May 17-19, 2027)

Research: From Training to Dynamic Enablement

Your Learning: The Global HR Excellence Certification

Galileo goes Enterprise: The Jupiter Release

• (00:00:05) - Introduction and Guest Welcome
• (00:01:54) - Marcy's Role and Cisco Learning Priorities
• (00:03:40) - State of Learning Before Transformation
• (00:05:35) - Overview of the Four Strategic Pillars
• (00:08:06) - Defining Guiding Principles and Culture
• (00:11:01) - Building the Skills Intelligence Engine
• (00:14:38) - Modernizing the Technology Stack
• (00:17:24) - Enabling Modern, AI-Driven Learning Experiences
• (00:19:30) - EdgeUp Labs and Time to Grow
• (00:22:43) - Measuring Success and Results
• (00:27:12) - What's Next: Agentic AI and the Skills Flywheel
• (00:29:36) - Key Takeaways and Closing Thoughts

More than 70% of US workers are frontline workers and most of our workforce is worried about AI. How do we as a country and we as employers help our people reskill, upskill, and educate themselves as adults?

Well Guild, which started its life as a tuition reimbursement management company, has pioneered a new model. By working with employers and credentialed education institutions, Guild gives employers a set of solutions to train, educate, certify, and license people for new, higher paying jobs. For companies in manufacturing, healthcare, airlines, and other regulated sectors Guild also helps “up-license” the technicians and specialists we need.

The solution to this problem is complex, and Guild took on this entire problem. The company works with many types of training and learning providers and also provides coaching, career pathways, and their own learning programs to help. For any company looking to fill critical talent gaps with new skills or new licensed workers, Guild is an amazing solution. Guild also focuses on giving employees a new sense of engagement and opportunity. Clients include Amazon, Pepsico, Lowes, and many other large organizations.

Bijal explains the market and solution in a comprehensive way, this is a good conversation to help you understand the entire scale of this challenge. She also unlocks some of the secrets of broad reskilling and behavior change programs, including AI transformation.

Additional Information

Guild Jumps Headfirst Into The Corporate Learning Market

The Capability Academy: Where Corporate Training Is Going

What Is Task or Work Intelligence And Can We Decompose Every Job For AI?

The Global HR Excellence Certification: Learn to be an AI HR Expert

• (00:00:00) - Introduction to Bijal Shah and Guild
• (00:00:51) - Bijal's Background and Path to Guild
• (00:02:43) - Guild's Original Model and Evolution
• (00:03:21) - Problems Employers Are Solving Today
• (00:05:49) - The Role of Education and Degrees Today
• (00:07:59) - From Good Deed to ROI-Driven Solutions
• (00:10:00) - Coaching, Human Connection, and Fragile Workforce
• (00:11:42) - Guild's Core Solution Framework
• (00:13:56) - Guild Academy and Behavior Change
• (00:16:52) - Navigator and Local Pipeline Solutions
• (00:18:23) - Amazon Case Study: Advanced Maintenance Technicians
• (00:20:28) - Disrupting the L&D Industry Model
• (00:22:30) - Managing Complexity as a Marketplace
• (00:23:48) - Cross-Employer and Cross-Geography Aggregation
• (00:25:54) - State and Government Partnerships
• (00:27:29) - Motivation, Fear, and Career Reinvention
• (00:29:59) - Durable Jobs and Economic Rebalancing
• (00:32:46) - Stitching Together Benefits, L&D, and Talent
• (00:33:48) - The Future of L&D and Capabilities
• (00:35:16) - Closing Thoughts on AI and Behavior Change

Vijay Swami, co-founder and CEO of Draup, believes the future of workforce planning is not about studying people; it’s about studying work itself. After nearly a decade pioneering talent intelligence, Draup has pivoted toward the most urgent question every enterprise faces: how do you redesign work for the age of AI? In this episode we sit down with Vijay to find out exactly how this works and why it’s more important today than ever.

The centerpiece of this evolution is a new product called Etter — named from Norwegian mythology, meaning “always in pursuit of” — because AI transformation is never finished. Insights from Etter help companies model their workforce not around job titles and skills taxonomies, but around processes, workflows, and tasks, then simulate what AI automation would actually mean for each one — quantifying the opportunity in dollar terms for the CFO. For one hospital client, Draup sized the AI opportunity at $2.6–2.8 billion.

The interesting part of this story is that Draup reveals a data problem lurking inside most enterprises: HCM systems are disconnected from where work happens — in ERP, Salesforce, Jira, and other operational systems. Draup closes that gap by integrating across HCMs, operational systems, and an evidence layer built on Microsoft WorkIQ, which captures how people actually spend their time. But all of this is not just a technology exercise: Vijay and his team take a consultative approach to solving customer problems, supported by technology.

Vijay argues you cannot redesign work if you only know the skills people have, you have to start with understanding the work itself and then redesigning workflows and processes with the outcomes in mind. We call this dynamic work design.

Work intelligence platforms like Etter are becoming a critical part of the HR 2030 architecture, and this new market is growing quickly. It’s important to learn about solutions like Draup as you build your AI transformation strategy.

Additional Information

What Is Task or Work Intelligence And Can We Decompose Every Job For AI?

Introducing HR 2030: A Vision For Agentic Human Resources

How To Take A Pragmatic (and winning) Approach To Skills

AI Transformation From the Frontlines (pod)

• (00:00:00) - Introduction and Welcome
• (00:00:49) - Meet Vijay Swamy and Drop's Origins
• (00:02:56) - The Meaning Behind Drop and Etter
• (00:04:25) - Five Key Use Cases for Work Redesign
• (00:06:03) - AI Sandbox and Simulating Automation Costs
• (00:07:03) - Skills Architecture and Business Model Shifts
• (00:07:44) - Industry Convergence and Disruption Examples
• (00:09:03) - Building the Etrontology and Data Integration
• (00:11:19) - Integrating with Enterprise Systems
• (00:13:31) - Data Health and Hidden Enterprise Gaps
• (00:15:05) - HCM vs ERP Disconnect and Workforce Twin
• (00:16:35) - HR's New Muscle: Owning Work, Not Just Jobs
• (00:17:57) - Reframing the Story: Processes Over Tasks
• (00:20:14) - Layered Skills Framework: Root, Core, Tech, Soft
• (00:22:07) - The Future: Visual Factory Modeling
• (00:23:06) - Final Advice: Start with the Analyst, Not the VP
• (00:25:15) - Closing Thoughts and Wrap-Up