Manabu helps corporations with capacity-building in the area of Artificial Intelligence by conducting in-person AI workshops. Every session is hands-on, job-role or industry-specific, and led by practitioners — designed to help business teams in HR, Marketing, Finance, Supply Chain, and other functions actually work with AI, not just learn about it.
In Japanese, Manabu means to learn.
It carries the spirit of lifelong curiosity – the idea that learning isn’t an event, but a way of being. There was a time when what we learned in school was enough to last a lifetime. Not anymore. Technology moves faster than our syllabi. To stay relevant, learning has to shift from being an occasional task to a constant rhythm – part of our professional DNA.
When personal computers arrived, we all had to learn PowerPoint, Excel, and Word. Then came the Internet, and we learned browsers, search, and email. Each wave demanded fresh learning, until those skills became second nature.
AI — and generative+agentic AI in particular is the third great wave. And just like before, we must learn again – not just to use new tools, but to think differently, to work smarter, to collaborate with technology itself. That’s what Manabu exists for – to help professionals and organizations learn how to effectively use AI.
This is how corporate AI training works at Manabu.
Knowing isn’t Doing ; Doing is Doing.
You don’t learn carpentry from a deck – or swimming by watching others. Real learning begins when you try. At Manabu, we teach by doing. Every module ends with a live, hands-on exercise. The only way to learn AI is to use it.
Online courses are useful – but in-person learning is transformative. It sharpens focus, builds accountability, and allows instant dialogue. Our programs are deliberately face-to-face, led by facilitators who engage, challenge, and guide in real time.
Learning Together
Collaboration multiplies learning. In a Manabu session, participants learn as much from one another as from the instructor – through shared questions, collective problem-solving, and group discovery. Learning becomes social, not solitary.
Platforms evolve; principles endure. First we had Yahoo as a search engine. And then in become Alta-Vista. And then Google. So also ChatGPT and Gemini will evolve too. Our focus is on skills that outlast tools – how to frame problems, prompt effectively, and apply AI in your context. Once you know how to drive, the car matters less.
Job-role–focused Design
AI is not one-size-fits-all. A finance professional, a recruiter, and a factory manager will each use AI differently — and so will teams working in different industries and different geographies, where business contexts differ. Our programs are designed by role and function, making every exercise directly relevant to your day-to-day decisions.
Each course includes eight focused modules, about 90 minutes each.Four modules fit neatly into a day; all eight span a two-day workshop. Organizations can mix and match modules to meet specific goals – blending depth with flexibility.
Manabu is a corporate AI training practice that runs in-person workshops for business teams. Sessions cover HR, Marketing, Finance and Supply Chain — built around real workflows, not theory.
Every session is run by Hareesh Tibrewala and Khushboo Sehgal — practitioners with hands-on experience delivering AI training to business teams, industry bodies and corporate leadership teams.
We believe that real-learning happens when it is hands-on and collaborative. Our workshops have live group exercises, and also encourage real-time dialog with the faculty. These are the things that make AI skills actually stick.
It means AI training built around how your business actually works — not a generic curriculum. Manabu designs sessions around the role, the function, and the decisions that your team makes every day.
The method is the same — hands-on, in-person, role-specific. But the examples, case studies and workflow contexts are adapted to the business environment your team operates in.
The Manabu Method is built on five principles — learning by doing, in-person delivery, collaborative learning, skills not platforms, and role-specific design. Together they ensure AI upskilling translates into real habit change.