The world changed on November 30, 2022 when OpenAI released ChatGPT. The pioneering chatbot shocked users with its ability to engage in eerily human-like conversations that were clear, relevant, and context-sensitive. Within five days of launch, it garnered one million users, and within two months, it surpassed 100 million users. ChatGPT adoption blew away social media sensations TikTok and Instagram – which took nine months, and two and a half years, respectively, to reach the same milestone.
Over the following months, it became clear to anyone who has interacted with generative AI models (genAI) just how remarkable they are—unlike anything we’ve seen before. However, while the potential for AI and learning is undeniable, the truly game-changing impact has been slower to materialize and remains largely on the horizon. Despite the astonishing breadth of capabilities and roles genAI can adeptly perform such as copywriter, editor, personal research assistant, idea generator, creative partner, tutor, auto-translator, data analyst, and more, the full transformation these tools can bring to our work and personal lives is still emerging.
Our perspective on the transformative impact of AI in learning and development
At Intrepid, our focus has always been on driving business impact through effective learning solutions. Starting as a learning research company, we evolved into a professional services business and then developed a collaborative learning platform that makes digital learning experiences more human, connected, and applied to real work. Throughout this evolution, we have obsessed over delivering learning experiences that are smart, simple, and scalable while driving transformative learner impact and meaningful business outcomes.
Historically, the gold standard of learning has long been one-on-one tutoring and hands-on practice with personalized feedback, but these practices are clearly challenging to scale. For example, a major stumbling block to delivering expert feedback to learners practicing new skills is the time (and expense) of expert reviewers. Machine intelligence, through genAI, now makes scalable one-on-one tutoring and expert feedback to hands-on practice possible for the first time.
genAI enables incredible capabilities to personalize hands-on practical learning experiences with interactions such as roleplays, simulations, Socratic dialogues, scenarios, tutoring and more – cumulatively, to make learning experiences “smarter.” In addition, genAI offers tremendous opportunity to improve learning administration as well. GenAI has great promise to support learning program creation and to simplify and scale administrative processes related to course management, communications, translation, learner feedback, insights, reporting and more.
At Intrepid, we are pushing ourselves to consider how genAI could help us extend the unique value we provide customers through our platform – e.g., enhancing learner collaboration, innovating new forms of practice, and surfacing valuable insights from learner-generated content. Already, we’ve released genAI features that are delivering this value, for example:
- AI-generated Video Coach helps learners hone their skills by providing instant, constructive insights on user-generated video assignments. By analyzing submitted videos, the video AI coach feature offers personalized suggestions at scale to help learners refine their skills and improve their performance, ensuring they receive feedback targeted to the specific learning objectives.

- AI Mission (aka “Assignment”) Creator acts as your personal brainstorming partner for authoring assignments. It helps authors craft robust practice exercises with simple prompts, offering creative suggestions and ideas to build engaging and effective assignments. Whether you’re starting from scratch or refining an existing concept, this tool simplifies the process by providing innovative ways to reinforce key learning objectives. With its support, authors can effortlessly generate interactive missions that not only challenge learners but also enhance their overall learning experience.

- Universal AI Text Editor streamlines content creation by simplifying tasks like drafting discussion prompts, writing introductory statements, crafting abstracts, creating summaries, and converting technical jargon into learner-friendly language. This tool accelerates course development, helping authors produce high-quality content quickly and efficiently.

Our genAI features have been embraced by Intrepid customers and partners, and we’re excited to see them continue to innovate their programs using these capabilities.
Where Intrepid is headed with generative AI in our platform
The genAI-powered features above are just the beginning for us! We see ourselves as fellow travelers with the rest of the world on this epic AI learning and development journey, and as such we are approaching it with a learning mindset and a spirit of humility. We are eager to learn alongside our customers, partners and the broader learning community to determine the best opportunities for genAI to add value to the Intrepid learning experience!
However, while genAI is an exciting new technology that unlocks many new capabilities, it doesn’t change our focus on helping organizations connect, practice, and upskill. And the North Star guiding our strategic product direction is consistent with our roots — we will lead the future of cohort learning by empowering organizations to create and deliver learning experiences that are smart, simple, and scalable.
- Smart. Creating the tools that power better learning experiences is our raison d’être – we know that collaborative, applied and engaging learning is effective learning. We’re going to double down on this strength, and we’re going to use genAI to do it – for example, we’ll build features that deliver personalized feedback and enable realistic roleplays.
- Simple. We’re committed to simplifying our customers’ experience working in Intrepid and amplifying their impact. Each interaction in our platform—whether by admins, instructors, or learners—should be effortless and efficient. That’s why we’ll be using genAI to deliver features that deliver business insights, streamline authoring, and simplify the user experience.
- Scalable. We’re committed to making it easy and frictionless for our customers to scale learning experiences across the organizations they support. This means delivering new features that simplify learning administrative processes—such as auto-translation, reporting, and integrations that enable enterprise scale with ease.
Beyond the hype: Taking the challenge of genAI learning impact seriously
AI for learning and development offers tremendous potential for driving transformative learning experiences, and we’re excited to keep pioneering creative and innovative uses of this technology to deliver smarter, simpler, and more scalable solutions for our customers. Yet we also know that any emerging technology should be met with a healthy dose of skepticism. Like many professions, L&D is prone to the breathless hype that comes with each new technology wave. Virtually every learning technology today claims to offer groundbreaking, “AI-powered” capabilities – thanks to a bit of genAI pixie dust sprinkled on top.

There are genuine success stories that demonstrate the transformative potential of genAI when applied thoughtfully. For instance, consider a scenario where genAI is used to create dynamic roleplay simulations for leadership training. Immersive simulations can develop skills like resolving conflicts or coaching for performance, by adapting in real-time to the learner’s responses, providing personalized feedback and allowing for the practice of complex decision-making skills in a risk-free environment.
This type of practical AI application not only engages learners but also enhances their ability to apply what they’ve learned in real-world situations. We invite you to check out these Intrepid Roleplays we created powered by GPT technology!
However, not all uses of genAI are as effective. Many platforms are rushing to automate course creation with genAI, promising rapid content production. While enticing for organizations aiming to save time and costs, simply creating more content faster doesn’t necessarily improve learning outcomes. As one colleague, JR Burch, humorously pointed out through a masterful meme he created, producing more content isn’t the same as delivering learner value.

Even thoughtfully implemented genAI solutions can face challenges. A recent study from the Wharton School showed that while students benefited from genAI tutors in practicing math, their performance on actual tests worsened compared to those who didn’t use the tutors. This suggests that genAI, in some cases, may provide answers too readily, leading to overconfidence without deep understanding.
It appears that students may build a false sense of confidence by studying with a genAI tutor whose prompts often provide answers to students too readily without challenging them to think for themselves. We are in very early innings with genAI and learning and it’s important that we approach new use cases with curiosity and an opportunity to adapt based on what we learn.
What we’re learning about using AI in learning and development
We’ve been actively listening to our customers and engaging with industry leaders to understand the critical trends and challenges of genAI adoption in enterprises. Through interviews with CLOs, CEOs, and industry analysts, we explored their approach to developing genAI skills and capabilities. Additionally, discussions with senior technology executives and investors revealed key struggles in supporting AI transformations in large companies:
1. Governance
Companies are working hard to define their genAI policies because they see the importance of enabling workplace experimentation while ensuring responsible use. IT organizations within companies aren’t just being reflexively conservative to be difficult or to slow business innovation. They are proceeding with caution as they are trying to figure out effective governance models that support individual privacy, data security, the safeguarding of intellectual property, and evolving and distributed government compliance.
2. Strategy
Many companies are struggling to define their business and technology strategies to effectively generate value from genAI adoption. Key questions they are facing include:
- Organizing models: Should they pursue a centralized, federated, or open model for pursuing genAI initiatives?
- Centers of excellence: Should they establish centers of excellence to vet, prioritize, and resource genAI projects?
- Utilization options: What are the best ways to leverage genAI within organizations? For example, options may include:
- Leveraging third-party software applications with genAI productivity features (e.g., MS CoPilot, Salesforce, Zendesk)
- Conducting genAI proof of concepts and experiments focused on improving internal processes
- Implementing a private large language model (LLM) to support multiple organizational use cases
- Investing in technology infrastructure to connect disparate company data, enhancing genAI “chain of action” capabilities
- Embedding genAI features into customer products and solutions
- Leveraging third-party software applications with genAI productivity features (e.g., MS CoPilot, Salesforce, Zendesk)
Many organizations are hitting roadblocks when it comes to scaling their genAI proof of concepts. While individual experiments often succeed as discrete, self-contained initiatives, companies are struggling to extend them in ways that deliver enterprise-wide impact. Most organizations find themselves at the very beginning of a multi-year journey to learn from their experiments, connect data sources, and build the infrastructure necessary to enable enterprise transformations powered by genAI.
According to Deloitte, while organizations are eager to expand genAI, only about 30% of their experiments move into full production, primarily due to data quality and integration challenges. Research also indicates the primary obstacles are tied to risk management, with 36% of organizations concerned about regulatory compliance, 30% struggling with risk management, and 29% lacking a solid governance framework.
3. Expertise
90% of tech leaders plan to implement AI initiatives this year, but 48% cite a lack of AI-skilled staff as the main challenge, according to Robert Half. With most companies having less than two years of experience with AI, recruiting alone won’t solve this gap. Instead, organizations need to partner with AI experts and invest in developing in-house talent. In interviews with global learning leaders, many emphasized that building AI skills internally is mission critical. Yet, 88% of employees don’t feel confident their employer will support their AI learning—highlighting a key opportunity.
What can you do now with AI and learning? Experiment!
Sound daunting? We understand, it is equal parts exciting, and gnarly. So what can you do and where should you start? The answer is simple: start learning and experimenting.
1. Start learning
There are loads of courses, websites, and even a few worthwhile books out there. Because genAI is such a recent phenomenon (and changing so fast), all the books I recommend have been published in just the last few months:
- For a good overview of the power and promise of AI for business, I recommend starting with Co-Intelligence: Living and Working with AI by Ethan Mollick.
- For a focus on the application of AI for education and learning, check out Salman Khan’s Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing). At times it can feel like a commercial for Khanmigo, but you’ll learn a lot about how he’s approached the opportunity to personalize learning at scale.
- And for an inspiring book focused on AI and skill building without killing the timeless value of the apprenticeship model, read The Skill Code by Matt Beane.
In addition to this blog post, the Intrepid team has been active sharing our perspective on AI and learning. Recently, I was interviewed for the podcast series “Performance Matters” hosted by GP Strategies – the episode is titled Navigating AI Integration in Learning Organizations. And you can learn some great practical tips on utilizing AI for learning design in an on demand webinar hosted by my colleague, JR Burch – AI Applications to Ignite the Learner Experience.
There are many useful courses, videos, articles, and blogs available to accelerate your learning. Following is a small sampling of recommended resources:
- Collection | AI for Leaders (MIT Sloan Management Review)
- Course | Coursera: AI for Everyone
- Course | LinkedIn Learning: AI Foundations – Machine Learning
- Course | edX: Generative AI for Business Leaders
- Course | Udemy: GenAI Courses
- Video | Tech Target: Ultimate Guide to GenAI for Businesses
- Blog | Ethan Mollick: One Useful Thing
- Blog | OpenAI Blog
Finally, a word of caution as you research learning resources; the market is awash in generic genAI course offerings which are becoming rapidly commoditized and outdated as LLMs and business applications quickly change. Look at the publication date of any course you’re considering to ensure the content hasn’t reach its expiration date.
2. Learn by doing
Embrace your inner hacker and start experimenting with the tools at your fingertips. Get a subscription to ChatGPT, Claude, Gemini, or utilize your company’s CoPilot subscription, and start playing and creating GPTs. Want to see what they look like? Check out our free Roleplay GPT (and tell us what you think!). When it comes to your daily work, try using genAI to help you with some of your mundane tasks – e.g., summarizing meetings, drafting emails, editing correspondence, converting an article to a Slack post, generating ideas to help with brainstorms, and so on. Treat it like your personal intern, and as such, don’t accept what it suggests without scrutiny.
Once you’ve developed your own familiarity with genAI tools to enhance your personal productivity, start tinkering with some work processes or learning experiences, and imagine how they might be done more easily and impactfully. And yes, I know, you need to respect governance and policy, and you won’t have your data organized and accessible in all the ways you want it to be. But don’t let that stop you from experimenting.
3. Partner with Intrepid
Need a thought partner? We’ll pull up a chair and listen to your ideas, share our tools, and collaborate with you to leverage the power of genAI to help you create customized, effective, and engaging learning experiences without the need for extensive in-house AI expertise. We’ll meet you where you are, and respect your governance, policies, and LLM preferences. We’ll bring tools, templates, and GPTs – combined with AI and learning expertise – to help you get started and bring these innovative experiences to life.
And remember, you’re not too late to the party. There are very few “experts” out there, most of them are self-proclaimed and likely just a step or two ahead of you, so don’t be bashful. Your genAI journey starts by taking the first step, so roll up your sleeves, get started and start experimenting.
Shaping the future of learning together
As we navigate the evolving landscape of generative AI in learning and development, Intrepid is committed to creating learning experiences that are smart, simple, and scalable. We view genAI as more than just a tool; it’s a transformative force that strengthens our mission to enable organizations to connect, practice, and upskill.
The challenges we all face—whether in governance, strategy, or expertise—are opportunities for innovation. By embracing experimentation and a learner’s mindset, we can harness genAI to build impactful solutions. We’ll continue to share our insights and we’re eager to hear from you as well. If you have questions about our approach to AI or are interested in exploring potential partnerships, we invite you to reach out.
Together, we can shape the future of learning. Onward!
Frequently asked questions: The Intrepid Platform and generative AI
View our genAI FAQ page for answers to commonly asked questions regarding our approach to AI integration.