Meet Altaviva: A Carnegie Mellon University spinout built to prepare the workforce for an AI-powered future. Its platform delivers interactive, project-based learning grounded in more than a decade of pedagogical research from CMU’s TEEL Lab, giving learners hands-on experience with workflows in AI mediated workplaces in different industries.
Today, Altaviva builds experiential learning pathways for careers in cloud computing, data, and artificial intelligence, helping organizations develop a workforce with humans and AI agents working together in practice, not just in theory. While 86% of employers are preparing for AI to transform their business, most AI-impacted roles still come with few real training options. Altaviva closes that gap, giving learners the confidence to apply what they’ve learned to real problems on the job.
Our conversation with Co-Founder & CEO, Ramji Raghavan, explores how Altaviva is helping organizations move beyond basic AI literacy toward genuine operational readiness, and what that shift will mean for how people learn and work over the next five years.
What did you see happening in AI education that led you to build Altaviva?
We saw a growing gap between learning and workforce capability at Carnegie Mellon’s TEEL Lab several years ago, where much of our founding team, including my co-founder, who was the founding director of the lab, were working directly on this problem. Organizations were investing heavily in training, but completing online courses did not consistently translate into better performance on the job or ROI for the enterprise. AI has magnified this challenge, given the massive investment enterprises are making and the fast-changing landscape. It is no surprise that a recent MIT study found only 5% of early integrated GenAI pilots have resulted in measurable, impactful outcomes for enterprises. Current training options focus on IT professionals or tactical GenAI tool use. Organizations need people who have a practical understanding of AI, including its limitations, vulnerabilities, and how it can complement human decision making. An operationally ready AI workforce isn’t one just trained on tools, because tools change continually. You need a workforce that can work effectively with AI in their daily workflows, practicing decisions, solving complex problems, and more. That is the future Altaviva is enabling.
How has your work with Carnegie Mellon influenced the way Altaviva designs AI and its learning pathways?
Altaviva’s underpinning is over a decade of research from the TEEL Lab at Carnegie Mellon University, focused on scaling experiential learning through technology. It’s been proven that learning is most effective when it is iterative, interactive, and grounded in real-world contexts. We teach learners not just concepts, but the complexity and ambiguity of real-world decision-making. People develop lasting skills by actively applying knowledge, receiving timely feedback, and reflecting on their performance, not simply by consuming content. As we look ahead to enterprises integrating AI, judgment and human-in-the-loop decision making are going to be crucial. Every learning pathway in Altaviva is built around authentic workplace scenarios where learners solve realistic problems, make decisions, and receive personalized feedback powered by AI. AI is what we teach, but AI is also how we deliver experiential learning at scale. The goal is not just to help people know more. It is to help them do more.
What differences are you seeing in how small and mid-sized companies approach AI upskilling after working with Altaviva?
One of the biggest differences we see is that small and mid-sized organizations cannot afford AI learning that is disconnected from day-to-day work. They need people to become productive quickly, apply new skills immediately, and deliver measurable business value.
For smaller organizations, every employee has an outsized impact. They are looking for maximum ROI for their AI investments. Businesses that have governance, audit, and regulatory requirements need to worry about data coherence, security, explainability, etc. Basic tool training and literacy isn’t sufficient. They want workforce capability that translates into faster execution, better decisions, and business outcomes with AI. That is the problem Altaviva is solving.
We are still early in our journey, but in the few engagements we have done, we have worked with training cohorts across different industries. What we have seen with training cohorts is that Altaviva equips learners with the ability to evaluate capabilities and risks of AI. We have seen learners move into new technical roles. We have also seen an increase in confidence among non-technical users within an organization to use the AI tools that their own IT group has built.
One notable example involved an IT group that had built its own AI tools. That group sponsored Altaviva specifically to educate and instill confidence among its non-technical users. Even when employees trust that their own team built a tool, people working in regulated, audited environments are often still fearful of using AI. Altaviva helped close that gap, ensuring the tools were adopted responsibly and successfully deployed into production, rather than left unused out of caution.
What’s the biggest change you hope someone experiences after completing an Altaviva program?
The biggest change we hope to see is a shift from understanding to confidence and capability. We want learners to finish an Altaviva program knowing they can apply what they have learned to solve real problems in their jobs.
That confidence comes from practice. By working through realistic scenarios, making decisions, and learning from mistakes in a safe environment, learners develop the practical skills and judgment that transfer directly to the workplace.
To be clear, even a basic understanding of AI is still valuable. It’s a powerful tool, and people use it every day for things like market research and general problem-solving. But as businesses invest in AI and compete to use it well, basic familiarity won’t be enough to set people or organizations apart.
Ultimately, success is not measured by course completion or a certificate. It is measured by whether someone can perform more effectively, take on new challenges, and create greater value for their organization. The vision is not AI literacy; it is AI operational readiness. We want people to feel about AI the way they feel about Microsoft Word or Excel today: not a separate skill to master, but simply part of how they do their jobs.
How do you see workplace AI skills evolving over the next 5 years, and how is Altaviva building with that in mind?
We’re already seeing this shift happen. Over the next five years, AI skills will evolve from knowing how to use individual tools to knowing how to work effectively with AI as a collaborative partner. As AI becomes embedded in every role, the most valuable skills will be problem-solving, critical thinking, judgment, effective communication, and the ability to integrate AI into everyday work.
That means learning can no longer be a one-time event. We’re already working to bridge how AI functions in real time with how real jobs actually work, and that will only become more important as people need to continuously adapt to evolving AI capabilities and business processes.
We also believe AI will fundamentally transform how people learn. Rather than following the same path, every learner will receive experiences that adapt to their role, prior knowledge, goals, and day-to-day work. AI makes it possible to provide personalized guidance, timely feedback, and authentic practice at a scale that was never before possible. At Altaviva, we are building for that future by creating learning experiences that are personalized, contextual, experiential, and continuously aligned with the capabilities organizations need most.
Learn more at Altaviva’s website here.