And we are launched...Data Science and AI for Leaders (DSAIL) Course at Harvard Business School

Hey everyone —I have not been posting as often as I had hoped. I know, I know, all good intentions but for the last nine months I’ve been heads-down in the lab, launching a new course at Harvard Business School. And not just any course—a brand-new, AI-native course taught to all 935 MBA students as part of the required curriculum.

It’s called Data Science and AI for Leaders (DSAIL). My amazing colleagues and I have been working nonstop to design a learning experience that meets today’s urgent need for AI-savvy business leaders. In this post, I’m thrilled to share the story behind DSAIL, give you a sneak peek at how it works, and explain why I believe it marks a critical turning point for MBA education.

The Rationale: Why Now?

In every corner of the business world, executives are grappling with how to deploy AI effectively—and responsibly. Top consulting firms like McKinsey see “digital and analytics foundations” as essential skills for every employee. CEOs of companies like Walmart and Salesforce are openly declaring that AI may be the most important technology of our lifetimes.

At the same time, AI breakthroughs seem to arrive daily. Large Language Models (LLMs), generative AI, and advanced data science techniques are reshaping how we conduct research, make strategic decisions, and run operations. Even for organizations that haven’t traditionally thought of themselves as “tech” companies, AI’s potential to transform business models is enormous.

If the 20th century was defined by the MBA wielding Excel, this century will be defined by MBAs working hand-in-hand with AI agents—reimagining organizations, business models, and operating models from the ground up.

The Big Reveal: Two AI Bots to Augment Learning

DSAIL is built from the ground up to be AI-native, about AI. We didn’t want to just talk about advanced analytics and generative AI in theory—we wanted students to interact with them daily. So we developed two specialized bots to guide and amplify our students’ learning:

1. DSAIL Tutor Bot (RAG-based):

   • Trained on all the content of the course—cases, materials from my book Competing in the Age of AI, data science references, econometrics texts, and more.

   • Serves as a 24/7 tutor. Students can ask clarifying questions, review key concepts, or deep dive into advanced topics at any time.

   • Think of it as your on-demand professor’s assistant, bridging gaps in understanding and expanding on lectures and readings.

2. Julius.ai (AI Data Scientist):

   • Enables students to conduct real data analysis—without writing a single line of code in Python or R.

   • For years, MBA students have expressed reservations (to put it mildly) about learning to program. But with LLMs and natural-language AI, we can now free them from that hurdle.

   • Students simply ask Julius.ai what they want: “Run a regression comparing X and Y,” or “Visualize these customer segments,” and the system handles the computations.

   • This AI “co-pilot” ensures the real focus is on business insight, not syntax.

We believe these two bots will supercharge learning, giving future MBAs the skills they need in record time—just as generative AI starts to permeate every business discipline.

Course Structure: Four Modules, Endless Applications

Here’s how we’ve organized DSAIL:

1. AI Today (2 sessions)

   • We dive into the current generative AI landscape with real-world examples like Moderna.

   • Students explore how AI is deployed in companies for strategic advantage, from high-level transformations to subtle process improvements.

2. Data Exploration, Comparison, and Inference (4 sessions)

   • The foundational statistics and analytics every leader needs.

   • Data visualization, hypothesis testing, regression analysis, causal inference.

   • All done with the help of Julius.ai, so no coding required.

3. Machine Learning and AI Factories (6 sessions)

   • How to build, scale, and manage AI systems.

   • Covers classification, prediction, and the role of “AI factories” within firms.

   • Addresses ethical and regulatory concerns head-on: bias, fairness, privacy, data governance, responsible AI.

4. AI Strategy and Implementation (6 sessions)

   • Designing and executing an AI strategy at the enterprise level.

   • Covers adoption, scaling, and leadership implications.

   • Students cap it off by creating their own AI agent as a project—a glimpse into the near future of business.

Throughout these modules, we ground everything in real company case studies—we have created many new case studies of large and small organizations dealing with AI so students see exactly how these AI concepts translate into day-to-day leadership decisions.

Beyond the Hype: Why This Matters

Between the daily headlines and the deluge of new AI tools, the excitement can feel overwhelming. But behind that excitement lies a massive shift in the very structure of organizations and global competition. With DSAIL, we want our MBAs to:

• Master AI Literacy. Even if they never write code, they should be fluent in how AI works and what it can (and can’t) do.

• Think Strategically. AI isn’t a bolt-on feature; it changes how products get built, how data flows, how we learn from customers, and how we generate revenue.

• Lead Ethically. Issues like bias and privacy aren’t optional add-ons. They’re core to the design of AI systems. DSAIL teaches leaders to integrate ethics from day one.

Ultimately, an MBA in 2025 and beyond should feel at home working alongside AI agents—just as comfortable as previous generations were navigating Excel spreadsheets.

A Word of Thanks

This course wouldn’t be possible without my brilliant colleagues:

• Professor Iavor Bojinov—my partner in crime, co-leading the charge on everything from design to execution.

• The faculty, researchers and staff at the Digital Data Design at Harvard for keeping us on the bleeding edge of AI research and its impact on business and pushing us to rethink pedagogy

• Our entire extended team: case writers, research associates (Philip Ndikum & Ai Takahashi), HBS Digital Transformation (Andrew Jeske), MBA and IT Teams, and course coordinators. We’ve operated in full product-development sprint mode for the last six months, iterating on modules, experimenting with AI tools, testing new analytics approaches. The partnership with Julius.AI team has also been essential and Iavor and I are immensely grateful to Rahul for supporting us along the waly

I’m immensely grateful to all of them for making this ambitious project real. The energy, dedication, and ingenuity they bring have kept us all at the cutting edge.

Tying It All Together

If you’re reading this as a business leader, a prospective MBA, or a business school faculty member, I hope you sense our excitement. We stand at a frontier: the capacity to completely rethink organizations, business models, and operating models with the help of AI.

With DSAIL, we aim to give the next generation of Harvard MBAs the tools—and the mindset—to thrive in this new environment. That includes the ability to:

• Investigate data using intuitive AI tools

• Design and scale AI-driven strategies

• Anticipate and address the ethical and managerial complexities of large-scale AI adoption

I can’t wait to see what our students accomplish, both in the classroom and after they graduate. It’s a thrilling time to be working in AI—and this course is just one step toward shaping a responsible, innovative future.

A Measured Look Ahead

I appreciate your understanding during my lengthy absence. Building an AI-native course of this scope has been a complex undertaking, involving ongoing revision and collaboration with an extraordinary team of colleagues.

In the coming months, I will share more insights on DSAIL’s progress—what’s working, where we’ve had to pivot, and how students and executives alike are applying these lessons. While the potential of AI is undeniably vast, the path to successful, responsible deployment is not straightforward. Our hope is that by preparing MBAs and leaders to address AI’s technical, strategic, and ethical challenges, we’ll contribute to shaping a more thoughtful and sustainable business landscape.

Here is the course overview deck if you are intersted in learning more.

Ciao!