White paper

The Defining Role of CLOs in the AI Economy

As the impact of generative AI continues to transform work and accelerate employee productivity worldwide, chief learning officers (CLOs) are in a critical position as change agents, leading the adoption of AI within organizations.

By upskilling workers in high-impact technologies like generative AI, CLOs can reskill some of the 61% of workers predicted to need retraining by 2027.* At the same time, successful skills development can enable companies to tap into a potential $4.4 billion in productivity gains.**

The Defining Role of CLOs in the AI Economy explores how CLOs can help employees grow and organizations become agile and resilient, creating an engaged workforce that achieves business goals.

The white paper is available in English, Spanish, French, German, Arabic, Indonesian, Thai, or Portuguese. See the English preview below.

*The Future of Jobs Report 2023, World Economic Forum, 2023

**The economic potential of generative AI: The next productivity frontier, McKinsey, 2023

In this white paper, you will learn about:

- The leading role of CLOs in driving genAI transformation

- Demand for genAI skills among employees today

- Top genAI skills for your organization

- AI learning innovations to enhance upskilling and reskilling

Surging interest in AI

445% YoY increase

Searches for genAI content among Coursera for Business learners (Q3 2023)

157% YoY increase

GenAI content enrollments among Coursera enterprise learners (Q3 2023)


AI courses on Coursera

Andrew Ng

Just as electricity transformed industries a century ago, AI is reshaping our global economy. In this rapidly evolving world, leaders have a responsibility to equip the individuals they serve with the necessary AI skills, not only to enhance their employability, but also to empower them to reshape the nature of their work.

Andrew Ng
Co-Founder and Chairman and Time 100 AI Leader

Essential generative AI skills for your organization, curated by Andrew Ng

Download the article for the complete skills list

Prompt Engineering: crafting effective input instructions for generative AI models to understand and respond to

Generative AI project lifecycle: the stages involved in developing and managing generative AI projects

Natural Language Processing (NLP): a field of AI focused on enabling computers to understand, interpret, and generate human language

Deep Learning: a subset of machine learning that uses neural networks with multiple layers to represent complex patterns and features in data

Diffusion models: a class of generative models used for tasks like denoising and generating images

Responsible AI: ensuring that AI systems are developed and used ethically, fairly, and transparently

Download the full article to learn more

Every CEO and CFO should be talking to their CLO right now about how to adapt to ChatGPT and generative AI. This new technology will change every industry, every business, and how every employee does their job. At stake is more than $4 trillion of potential productivity gains and the risk of losing to more agile competitors. A well-crafted L&D strategy fosters talent agility, equipping your team to not only meet challenges but also rise to the opportunities created by an AI-first world.

Jeff Maggioncalda
CEO of Coursera