Inside Cisco's skills intelligence engine: How Marci Paino is rebuilding learning for 86,000 employees
At Cisco, learning strategy starts with a data model.
Marci Paino, Cisco’s Chief Learning Officer, has spent the past several years building what she calls Cisco skills intelligence, a system that pulls in external labor market data and combines it with internal workforce data to map skill supply, skill demand, and forecasted needs across more than 86,000 employees.
The goal is precision at scale. Generic catalogs cannot keep pace with how quickly required skills change, so Paino built an engine that can.
“If we can get our intelligence down to kind of the skill particle base, then we can then create more personalized learning experiences at scale,” she says.
The skills flywheel: cutting production time from months to a week
Skills intelligence feeds what Paino calls the skills flywheel, a repeatable process that turns a single signal into a finished learning experience in days, not months.
Here is how it works.
- Catch the signal. A skill signal, essentially a ping that a new capability is emerging across the business, surfaces through Cisco's skills intelligence data.
- Route it to the right team. The signal triggers either Cisco's learning team directly or its network of internal subject matter experts, known as the pacesetter network.
- Capture the expertise. Agentic AI collects and structures what the pacesetters know, turning scattered expert knowledge into a usable content base.
- Ship the learning experience. What used to take roughly three months to produce now takes about a week.
The same intelligence also drives workforce planning, through a framework Paino calls build, boost, automate, or borrow.
- Build: always-on baseline learning available to every employee.
- Boost: targeted development for employees with adjacent or transferable skills.
- Automate: flags work that should shift to AI instead of a person.
- Borrow or buy: covers stretch assignments, apprenticeships, and external hiring.
An 11-company consortium racing to keep up with AI
Beyond Cisco, Paino leads the AI Workforce Consortium, a coalition of 11 companies, including Accenture, Coursera, Cornerstone, Eightfold, Google, IBM, Indeed, Intel, Microsoft, Pearson, and SAP, studying how AI is reshaping work and publishing the findings publicly.
The group's first report, in 2024, projected that around 92 percent of in-demand technology roles would see moderate to high transformation from AI. A year later, more than 72 percent of job postings for those roles required foundational AI skills.
The consortium has also built a shared skills glossary and a public library of more than 200 learning resources mapped to specific skills and job roles, with over 85 percent available to anyone at no cost.
“The power of the collective for us coming together to really discuss the challenges that we’re all facing and the best practices, what’s working, what isn’t,” Paino says, “we see that as being kind of industry game changing.”
Values that connect to specific, measurable skills
Cisco recently redefined its guiding principles: think big, play to win, and drive durable growth.
What sets the framework apart is that each principle is tied to a specific, named set of skills rather than left as inspirational language.
“Part of the premise of skills is that that is an actionable, demonstrable thing that I can develop and that I can work on,” Paino says. “That makes the abstract more tangible.”
The skills underneath each principle are treated as living, not fixed, and are reassessed regularly as priorities shift.
Cisco reinforces the model through what Paino calls a hum, sing, shout cadence: always-on access to a self-serve skill studio, layered with recurring touchpoints like monthly all-hands meetings, quarterly learning labs, and a new program called Time to Grow, a calendared four-hour monthly block dedicated entirely to learning.
Four personas, one shared AI curriculum
Cisco's flagship AI program, AI for Everyone, is built around four personas: user, leader, builder, and enabler. Every employee starts with the user pathway, learning how to apply AI to their own work. From there, people managers move into the leader pathway, learning to analyze team workflows and model AI adoption for others.
Paino notes that leaders who use AI themselves see their teams adopt it at roughly twice the rate, and the same pattern holds true for learning more broadly. The structure builds self-awareness before authority. Leadership starts with the self, so every leader learns to use the tools before being asked to lead anyone else through them.
Progress over perfection
Asked what she would tell her younger self, early in her path from instructional designer to consultant to enterprise learning leader, Paino circled back to a theme that runs through everything she described: there is no fixed destination.
“Embrace the progress over the perfection,” she says. “A lot of other people have really great experiences and expertise that can help you mold your idea into something better than you could have ever thought of on your own.”
For an organization built around skills intelligence, adjacencies, and constant recalibration, that mindset is not a personal philosophy on the side. It is the operating system.
Resources
Connect with Marci Paino on LinkedIn
Learn more about Cisco's AI Workforce Consortium
Explore Growthspace for precision skill development at scale
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