Building AI Skills at Scale: Udemy’s Journey Toward AI Transformation

In late 2022, when ChatGPT was released to the public, forward-thinking organizations recognized That artificial intelligence would not remain confined to engineering and product teams. It would become a critical capability across entire enterprises. This white paper chronicles Udemy’s systematic three-year journey toward building AI skills at scale, exploring the steps and learnings along the way.

The results from 2025 speak for themselves. Udemy saw a 956% increase in AI tool usage, nearly 835 custom AI assistants created across the organization, and more than 60 identified AI champions representing every business function. But beyond the metrics lies a replicable methodology that other organizations can adapt to drive their own AI transformation and inspire innovation within their companies.

What are AI skills for enterprises?

AI skills for enterprises focus on how your employees apply AI in daily work to improve decisions, streamline workflows, and deliver measurable outcomes. These skills go beyond knowing how to access a tool. Teams need to frame problems clearly, evaluate outputs with judgment, and integrate AI into existing processes without adding complexity.

In enterprise environments, AI skills show up in execution. Marketing teams use AI to generate campaign concepts and analyze performance trends. Sales teams use AI to prepare account plans and tailor outreach. Operations teams use AI to summarize data, surface risks, and speed up reporting. Leaders use AI to support planning and decision-making. Each application ties directly to business priorities and accountability.

Effective AI skills development emphasizes behaviors workforces repeat at scale. Training works best when learning connects to real responsibilities and expectations remain clear across roles and functions.

Core AI skills for enterprises include:

• Prompt engineering: Employees should know how to write structured, high-quality prompts to guide generative AI toward accurate and relevant outputs.
• AI tool proficiency: Where teams understand how to use role-specific AI applications and low-code automation tools to streamline workflows without deep coding expertise.
• AI ethics and compliance: Employees should understand legal and safety requirements such as the EU AI Act and identify algorithmic bias early.
• Critical thinking and output validation: Teams should be able to review AI-generated content for accuracy, hallucination, and risk before integration into business processes.

Organizations see stronger adoption when AI skills training reflects real work employees already own. When learning aligns with daily execution, confidence increases and usage becomes consistent.

AI skills for enterprises succeed when development efforts tie directly to measurable outcomes, including productivity, quality, and speed of execution. This focus helps organizations move from awareness to sustained impact.

The imperative for AI skills at scale

The release of ChatGPT in November 2022 marked an inflection point in the democratization of artificial intelligence, with demand for AI skills surging throughout 2023. Data from Udemy’s 2024 Global Learning & Skills Trends Report revealed a staggering 5,226% surge in ChatGPT-related learning consumption in Q1 2023 alone, while overall AI-related skills learning grew 60% year over year [1]. With McKinsey estimating that 30% of current work hours in the U.S. economy could be automated by 2030, and Wharton estimating that AI will increase productivity and GDP by 1.5% by 2035³, the strategic imperative became clear: organizations needed to move quickly from AI awareness to AI capability [2][3].

Udemy recognized early that this transformation required more than simply purchasing AI tools and hoping for adoption, as research on the productivity J-curve and past technological advances such as the personal computer or telephone have shown [4]. Microsoft’s research reinforced this challenge, revealing that 82% of global leaders acknowledged their employees would need new skills to effectively adapt to generative AI [5]. The challenge was not just technical; it was fundamentally about changing how work gets done.

How to build AI fluency

Building AI fluency requires more than awareness or isolated training sessions. Organizations need a shared foundation so teams develop a common understanding of how AI fits into daily work and decision-making. This foundation sets the conditions for consistent adoption and prepares leaders and employees to move forward together.

Establishing foundational knowledge across Udemy

Udemy’s AI journey began with a critical insight: AI skills are essential across every function, not just technical teams. Udemy employees already had access to Udemy’s full catalog of courses, including the freshest content available on AI; however, the real breakthrough came with the development of an enterprise-wide learning strategy designed to yield capability at scale.

In late 2023, Udemy created an enterprise-wide learning path and team learning experience consisting of curated content from Udemy instructors and internal subject matter experts. This was paired with conversation guides for leaders and teams, which helped get people talking about AI and taking steps together toward becoming more fluent.

This approach served multiple purposes:

• Positioned internal leaders as thought leaders both within the organization and in the broader AI field.
• Empowered employees with confidence that the right expertise existed internally to guide the transformation.
• Demonstrated executive commitment through visible participation and role modeling.
• Helped employees learn foundations and build trust with AI as a tool.

The impact of executive sponsorship cannot be overstated. When Udemy’s former CEO and executive team championed the learning initiative, completion rates reached 80% in just six weeks. This was accompanied by a 47% increase in enterprise ChatGPT activations, demonstrating that learning was translating into actual tool adoption.

According to former Udemy Lead Learning Partner, Joshua Ehrenreich, “By focusing on driving real impact—internal tool activations—we designed learning with intent. Through executive stories, manager-led discussions, and actionable resources, this learning experience sparked an enterprise-wide cultural shift.”

Recognizing that effective AI usage requires more than technical proficiency, Udemy complemented AI tool learning with priority skills development. These areas include decision-making, coaching, and change leadership, capabilities critical to driving key business outcomes.

Role Modeling from the top

Heading into 2024, Udemy knew there was more work to be done with regard to building AI fluency. While the learning experience kick-started adoption and usage, the organization still had a long way to go. Employees were largely open to learning and talking about AI, but were not yet applying those skills to drive the transformation of work at an enterprise scale. Employees and leaders were talking about AI, but they were not yet using it.

Udemy decided to invest in intensive AI skills development, starting with the executive team. Partnering with Helen Kupp and Ketaki Sodhi, innovative AI leaders, they designed a two-part workshop series:

• Workshop 1: Focused on moving beyond basic AI usage to sophisticated prompt engineering, teaching executives to think critically about inputs and outputs rather than treating AI as an “enhanced Google search.”
• Workshop 2: Centered on building custom AI assistants, with each executive creating a practical tool for their function. For example, prior Chief Marketing Officer Genefa Murphy built an OKR assistant that helped her team develop objectives and key results properly nested within functional and organizational goals, market context, and business context.

The vulnerability and collaborative learning demonstrated by executives proved transformational. When executives shared their newly built assistants with broader teams, it sparked inspiration and role-modeled the kind of experimentation desired throughout the organization.

Now that executives had greater confidence and fluency in their own skills, they could build on the awareness and experimentation developed throughout the company and focus that energy toward leading tangible business transformation.

Build AI skills for your enterprise with Udemy’s multi-stage approach

AI skills shape how organizations turn technology into performance. When teams apply AI with clarity, evaluate outputs responsibly, and embed AI into daily workflows, adoption increases and results follow. A structured approach to AI skills development helps align teams, strengthen decision-making, and support consistent execution across the enterprise.

To learn about the complete 4-step approach to AI transformation, download the full white paper. It gives a detailed look at the complete four-stage framework Udemy used to build AI skills at scale and drive enterprise-wide transformation.

In the full white paper, you will learn how to apply the remaining three stages:

• Stage 2: Learn and experiment together
• Stage 3: Identify use cases
• Stage 4: Transform the way we work

Sources

1. Udemy “2024 Global Learning & Skills Trends Report”
2. McKinsey Global Institute “A new future of work: The race to deploy AI and raise skills across Europe and beyond”
3. Penn Wharton “The Projected Impact of Generative AI on Future Productivity and Growth”
4. McKinsey & Company “ Technology alone is never enough for true productivity”
5. Microsoft “Work Trend Index|Will AI Fix Work?”