Generative AI In Practice: How Coursera Built and Implemented Its Foundational GenAI Learning Strategy (2024)

Written by Coursera • Updated on

Learn how Coursera developed a Generative AI learning strategy to upskill their workforce through personalized learning initiatives, leadership alignment, and employee recognition.

Generative AI In Practice: How Coursera Built and Implemented Its Foundational GenAI Learning Strategy (1)

Key takeaways

  • Coursera's CEO championed the GenAI initiative, making it a company-wide priority and not just an L&D program.

  • Coursera created the Generative AI Academy, offering tailored content for various roles (everyone, executives, specific functions).

  • Learning went beyond theoretical knowledge, emphasizing practical application and experimentation with GenAI tools in a safe environment.

  • Coursera utilized various tactics to motivate employees, including cross-functional leadership nudges, recognition programs, and playful social campaigns.

  • Coursera emphasizes continuous learning through workshops, knowledge sharing, and the development of new, role-specific training content.

With generative AI (GenAI), many company leaders can not afford to sit back and wait.

It’s understandable why some leaders may be tempted to do so. GenAI transformation is a massive undertaking to roll out company-wide GenAI education, policies, and tools. However, even if company leaders decide to hold off on embracing GenAI, employees could still choose to use the GenAI resources provided to them in inefficient or even unethical ways.

Meanwhile, organizations that integrate GenAI into their business practices are likely to outpace those that do not. A 2024 Deloitte study found that organizations with “high” or “very high” levels of generative AI expertise reported much greater success in strategic and growth-related areas.

At Coursera, we created a thoughtful GenAI strategy by recognizing the technology’s power to revolutionize the EdTech industry. Then, we moved full-speed ahead to upskill our Courserians.

In this article, you’ll learn how to set up an effective GenAI strategy based on the success we’ve seen so far. You’ll learn from expert Courserians themselves, Trena Minudri, VP & Chief Learning Officer, and Morgan Law, GenAI Learning Program Manager, and walk away with new ways to drive organizational alignment and communication for company-wide GenAI adoption.

(Note: For more insights on building and implementing a GenAI strategy, read the How to Lead through Generative AI Transformation playbook.)

Exploring GenAI’s potential: The foundation

For over a decade, Coursera has been on a mission to provide everyone with access to high-quality education from thought leaders, leading institutions, and experts. When GenAI arrived on the scene, we knew we wanted to continue leading from the forefront of professional learning.

Gartner research found that while 45% of companies have increased their investment in AI in the wake of ChatGPT, only 19% of organizations have designed a pilot program or implemented GenAI.

Action has to follow investment. In late 2022, our CEO Jeff Maggioncalda was inspired by ChatGPT and its potential. He created accounts on ChatGPT, Copilot, Microsoft Edge, and Gemini to understand the capabilities of large language models (LLMs) from a leadership lens.

Since everyone with an internet connection has access to GenAI, business leaders found themselves with a unique challenge: designing engaging and impactful learning that harnesses the business opportunities presented by this technology. Coursera leadership aligned to create GenAI action plans rooted in business strategy.

The key to the success of our GenAI initiative was that it was owned by our CEO and led by our learning and development (L&D) team. Because the initiative was owned by our CEO, it became more than just a learning initiative—it became a business imperative.

Creating a plan for GenAI upskilling: The first steps

“We always want to be the first and best users of our product,” shares Morgan Law, GenAI Learning Program Manager at Coursera.

On the product side, Jeff Maggioncalda assembled a small cross-functional task force known as Project Genesis to determine where Coursera could experience the most impact from infusing GenAI into offerings.

Within Coursera, we wanted our Courserians to develop the GenAI skills they’d need to stay on the cutting edge of its development and progress. Our first initiatives focused on providing them with a foundational understanding of GenAI, ChatGPT, and best practices so they could use these tools on the job.

As Courserians experimented, our L&D team designed learning initiatives that took the following steps into consideration:

1) Align learning with company culture

Trena Minudri, Coursera’s VP & Chief Learning Officer, believes that a critical aspect of Coursera’s GenAI strategy is integrating it with company culture:

“We have a very innovative growth mindset: move fast, fail fast, learn fast, and pivot. Our GenAI strategy follows what our culture holds as most valuable. Likewise, your executive team should consider, ‘How does this align with our culture and our people?’ And ‘what will be the most appropriate way to proceed?’”

Our learning initiatives focus on this mindset of experimentation and growth within individual job functions and across teams.

Coursera’s leadership also devised five key principles for guiding our exploration of GenAI—Positive Impact, Safety and Security, Fairness, Transparency, and Accountability.

2) Tailor learning to your employees

“Why does GenAI matter to me?” It’s only natural for employees to ask this question—and like employees at almost every other global company, Courserians asked it, too.

Coursera created Generative AI Academy as the answer—curated collections of trusted content and hands-on practice taught by the most innovative leaders in generative AI including Microsoft, Google, Stanford Online and IBM. These materials are organized into three pillars:

  • GenAI for Everyone: Building foundational GenAI skills across the company for a shared understanding and application of GenAI principles.

  • GenAI for Executives: Empowering senior leaders to develop and execute impactful GenAI business strategies, inspiring teams through a new era of transformation.

  • GenAI for Teams: Equipping functional teams to understand and adopt GenAI best practices unique to their business function, unlocking innovation and productivity.

When the time was right, we launched a dedicated GenAI training program and upskilled employees using Coursera’s GenAI content catalog.

3) Create a space for experimentation

To make sure that the training in Generative AI Academy was engaging, we knew that we needed to create a space for employees to experiment. Working with our technical teams, Coursera leadership developed a secure environment for employees to try out different LLMs and ways of working with them without the risk of exposing sensitive data. A version of this secure LLM environment then made its way into Generative AI Academy for use by all Coursera learners.

“In GenAI Academy, you’re learning from a professor or an expert in the field through videos, content, or hands-on exercises,” shares Trena Minudri. “We are then incorporating this training into a hybrid approach within the organization where the learning varies. We teach theories and concepts, and then create a space where employees can apply it to their work.”

4) Define measurable goals for learning

At the launch of Generative AI for Everyone pillar of GenAI Academy in Q4 2024, leadership aligned to create a goal: Each Courserian would enroll in one GenAI course of their choosing along with our CEO’s foundational course for navigating GenAI by the end of Q1 of 2024.

To monitor our progress toward this goal, we tracked:

  • Enrollments and starts across all GenAI courses

  • Total course completions

  • Hours spent learning

Knowing that our pilot wouldn’t be successful if we didn’t succeed in engaging Courserians, the L&D team focused on tracking metrics related to adoption. Moving forward, the team plans to study the correlation between GenAI learning and broader productivity and impact on business results.

Generative AI In Practice: How Coursera Built and Implemented Its Foundational GenAI Learning Strategy (2)

Coursera x Harvard Business School: Case Study

Harvard Business School explored our GenAI strategy by detailing our progress since the advent of ChatGPT. In this case study, you’ll learn:

  • How Project Genesis, our small GenAI task force, identified impact-ready projects including building GenAI education for individual learners, executives, and teams
  • The influence of cross-functional leadership on organization-wide GenAI initiatives
  • The five fundamental Coursera principles that guided GenAI initiatives
  • Coursera’s four initial projects for increasing competitive advantage with GenAI

Read the full case study on the Harvard Business Review Store.

Read case study

Driving employee adoption of GenAI: Our ongoing priority

We believe that shifting learning from the what to the how makes GenAI education more dynamic and more valuable.

Here’s what we mean: A lot of learning focuses on the what. What do I need to know to do my job? But the essence of GenAI is around the how: How do I use GenAI to transform my job?

A week before the launch of Generative AI Academy, we engaged Courserians with posts on our Slack channels. We shared a Zoom background to build excitement (and provided a great backdrop for company selfies). And we asked them to share jokes written by using ChatGPT.

These playful entry points paved the way for leadership to drive learning adoption:

  • Jeff Maggioncalda shared his sentiments around GenAI in all-hands meetings

  • Letters from the CEO were given to managers to share with their teams

  • At every all-hands meeting, cross-functional would share nudges to join Generative AI Academy

Of the different tactics we used to drive leaner adoption, nudges from cross-functional leadership proved to be most effective and sparked the highest engagement compared to social campaigns.

Morgan Law shares how Courserians started their GenAI learning path:

“Individual learners chose what was the best fit for them. We had a wide variety of experience levels, like folks in Engineering who were already using these tools and building them into our product, so we didn’t want to get too prescriptive about what course they should be taking because we wanted Courserians to take a course that applies to their own skill set.”

Courserians chose from courses like Introduction to Large Language Models by Google Cloud, Generative AI Fundamentals by IBM, Generative AI for Everyone by DeepLearning.AI, and Prompt Engineering for ChatGPT by Vanderbilt University.

We continued to motivate Courserians through positive reinforcement. At our all-hands meeting, we showed a video of LinkedIn posts Courserians shared after they finished their course. We highlighted top courses weekly. Plus, we recognized early adopters: The first 20 Courserians who completed a course were given a shoutout in a dedicated Slack channel called #customer-zero that was created specifically for sharing updates on Coursera’s internal learning initiatives. This celebratory message was one of Coursera’s most-liked messages in the channel.

To celebrate learners, we showcased how Courserians were sharing their completion of courses on LinkedIn.

Generative AI In Practice: How Coursera Built and Implemented Its Foundational GenAI Learning Strategy (3)

The next essential step in developing our GenAI strategy was measuring the results of our pilot.

Measuring the results of our GenAI strategy: The outcomes

After launching Generative AI Academy and asking Courserians to each complete one course, we’re excited to share that 83% of Courserians completed a course by the end of Q1 2024. They also logged more than 4,000 hours of learning content.

Want more ideas for how to increase GenAI adoption throughout your org? Review our white paper, How to Lead through Generative AI Transformation.

Read white paper

For those 17% who didn’t complete their first course in January, Morgan Law kept an eye on additional success metrics:

“I consider total enrollments, even if they aren’t completing the courses. Are they interacting with the course? What do our learning hours look like? I look at behind-the-scenes metrics beyond completions because learners can develop skills even if they’re not finishing the courses.”

In terms of business impact, this learning initiative supported the organization in achieving several key goals, including:

  • Reducing the time and cost it takes Coursera customers to produce high-quality content through the development of the AI-driven content curation tool Course Builder

  • Translating 4,000+ courses, 600+ Specializations, and 55+ Professional Certificates from partners like IBM, Meta, and Microsoft into up to 17 languages using a machine learning-powered approach.

  • Driving learner engagement and outcomes with the development of Coursera Coach which can answer questions and share personalized feedback through interaction with learners in real-time.

These early successes mark just the beginning for Coursera’s internal GenAI training. “At a foundational level, our employees are actively engaged in learning and continuing to increase their GenAI skills,” says Trena Minduri. “This is not a one-and-done type of game. It’s not about finishing a program—this is a journey.”

Here’s how we will continue to learn and lead with GenAI, both individually and with L&D initiatives.

Building on the momentum: What’s next for Coursera’s GenAI Strategy

Now that we’ve gained more and more GenAI expertise, we’re ready to completely redefine what GenAI learning initiatives could look like.

“We’re creating small, targeted workshops around GenAI.” shares Morgan Law. “These workshops will be guided by our leaders. Teams will ideate on how GenAI can influence their tasks and learn by experimenting.”

For example, here’s how our L&D team is putting GenAI into practice:

  • Building courses. The L&D team has used our GenAI-assisted Course Builder along with other GenAI tools to create course outlines and develop a series of upskilling courses for managers.

  • Generating outlines and frameworks. Our learning leaders use GenAI to build presentation outlines. When they host panels, they use LLMs like ChatGPT to help draft and iterate on the talking points. These tasks traditionally took L&D leaders a long time to perfect.

  • 360 reviews. L&D leaders have led a new process for GenAI-assisted performance reviews. This process—which was rolled out during Coursera’s last annual review cycle—has managers input peer feedback and employee self-assessments in Coursera’s secure LLM environment, and then use L&D-created prompts to deliver coaching points for employees.

  • Prompt-sharing. In the spirit of continuous learning, the L&D team shares well-designed prompts that lead to impactful outputs in company Slack channels.

In the coming months, the L&D team is looking forward to rolling out leadership- and role-specific courses, so learning can continue to be relevant and authentic to each employee’s daily work experience.

How to develop your gold-standard GenAI strategy

As a business leader, you’re in a unique position to bring GenAI to life at your organization. But you can’t do this without aligning with L&D leaders, managers, and cross-functional teams. If you’re holding back, it’s important to recognize that this is new and that we’re all experimenting together. There’s much that we can learn from one another as we continue to do so.

How to Lead through Generative AI Transformation

To learn more about how you can build a generative AI transformation from experts at leading institutions like Salesforce.AI, DeepLearning.AI, and Stanford University, read our recent playbook: How to Lead through Generative AI Transformation.

Get playbook

Written by Coursera • Updated on

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Generative AI In Practice: How Coursera Built and Implemented Its Foundational GenAI Learning Strategy (2024)

FAQs

What is GenAI and how does it work? ›

GenAI uses machine learning technology to optimize results by exploring more possibilities than traditionally humanly possible. This can be done on the fly when operation on a design, or through a large language model that has been trained on a wide variety of design data.

How does Coursera use AI? ›

AI-ASSISTED COURSE BUILDING POWERED BY GENERATIVE AI – Based on a few simple inputs from a human author, a new set of AI-powered features can auto-generate course content — such as overall course structure, readings, assignments, and glossaries — to help authors dramatically reduce the time and cost of producing high- ...

How to use generative AI? ›

The most common way to train a generative AI model is to use supervised learning - the model is given a set of human-created content and corresponding labels. It then learns to generate content that is similar to the human-created content and labeled with the same labels.

What are the capabilities of GenAI? ›

Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data.

How is generative AI built? ›

Generative AI models work by using neural networks to identify patterns from large sets of data, then generate new and original data or content.

How is GenAI different from AI? ›

One of the key differences between AI and Gen AI is that traditional AI excels in analyzing and automating, while Gen AI pioneers in creative content generation. Both AI and Gen AI are key players in industry transformations, from healthcare to finance.

What are generative AI Coursera answers? ›

Answer:- Generative AI is a type of artificial intelligence (AI) that can create new content, such as text, images, audio, and video. It does this by learning from existing data and then using that knowledge to generate new and unique outputs.

Which course is best for AI in Coursera? ›

Best of Machine Learning & AI
  • Machine Learning. Stanford University, DeepLearning.AI. ...
  • Deep Learning. DeepLearning.AI. ...
  • Prompt Engineering. Vanderbilt University. ...
  • IBM AI Developer. IBM. ...
  • AI in Healthcare. Stanford University. ...
  • Mathematics for Machine Learning. Imperial College London. ...
  • Natural Language Processing. ...
  • IBM AI Engineering.

Is Coursera good for learning machine learning? ›

I've already taken more than 35+ courses at Coursera. I've also been a long-term member of platforms like Udemy, Pluralsight, Udacity. I can definitely say that the quality of the Machine Learning course is one of the best I've seen.

What is an example of generative AI? ›

Based on the brief, the AI can generate as many assets as needed, including emails, case studies, Facebook and Google ads, press releases, and more. One generative AI example that can be used in marketing is Jasper Campaigns.

Which is the best generative AI tool? ›

Among the best generative AI tools for images, DALL-E 2 is OpenAI's recent version for image and art generation. DALL-E 2 generates better and more photorealistic images when compared to DALL-E. DALL-E 2 appropriately goes by user requests.

How to start generative AI learning? ›

The following step-by-step guide will pave the way for a comprehensive understanding and proficiency in Generative AI:
  1. Step 1: Understanding the Basics of Machine Learning. ...
  2. Step 2: Mastering Python Programming. ...
  3. Step 3: Exploring Data Science and Deep Learning. ...
  4. Step 4: Introduction to Generative AI.
Mar 20, 2024

What makes GenAI unique? ›

Unlike traditional AI, which follows strict rules and data patterns, GenAI can create original outputs based on what it has learned from training data. GenAI learns from large data sets and then uses this knowledge to create new things.

What is the primary goal of GenAI? ›

The main goal of generative AI is to boost business productivity by automating repetitive tasks, freeing up time for employees to focus on more strategic and fruitful activities.

What is GenAI vs ChatGPT? ›

ChatGPT is a kind of generative AI that makes content creation and information retrieval easier. Stated differently, generative AI is a broad field of study, while ChatGPT is a specific application of AI.

What is the primary function of GenAI? ›

Generative AI models can take inputs such as text, image, audio, video, and code and generate new content into any of the modalities mentioned. For example, it can turn text inputs into an image, turn an image into a song, or turn video into text.

How does GenAI work for images? ›

AI Images are created through a complex process of adding and removing noise, while also leveraging inputs- for example text prompts. NOISE is used throughout the AI image creation process. You can think of it similar to blurring effects and also the "Fuzz" you see on images.

How does ChatGPT actually work? ›

ChatGPT works by attempting to understand a text input (called a prompt) and generating dynamic text to respond. It can do this because it's a large language model (LLM). It's essentially a super-sized computer program that can understand and produce natural language.

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