Heena Chhatlani
I lead product strategy, roadmaps, and delivery for enterprise SaaS and AI/ML platforms, and I build the product organizations that sustain them. My edge: making governance, regulation, and responsible AI part of how great products get built, not a gate they wait at.
Responsible AI
for Product Managers
The go-to playbook for AI product leaders. It turns responsible AI frameworks, laws, and standards into decisions a product team can use next week: whether to build, what to test, when to launch, and when to stop.
- How AI products fail, and the rules that apply
- A Responsible AI Operating System for product teams
- Running and organizing for AI in production
Where I focus
I work where product strategy meets operational complexity: modernization programs, technology adoption, and the governance that decides whether either one holds up in the real world.
Enterprise platforms at scale
I own multi-year roadmaps for SaaS, analytics, and AI/ML platforms that other teams and business units rely on. Success is measured by adoption and staying power, not launch dates, and by whether the people using them are better off.
Governance that still ships
I am at ease with legal, risk, security, and engineering in the same room, and I have little patience for governance theater. Controls should give regulators and clients real confidence without stalling delivery.
Building the product function itself
Much of my work has been standing up product practice from scratch inside large consulting and transformation organizations: hiring, coaching, and putting in place the rhythms that make product management real rather than aspirational.
The right tool for the problem
I start with what the customer needs and choose the simplest approach that works. AI earns its place when it is genuinely the better answer, and I am glad to say so when it is not.
The short version
I started close to the engineering and delivery side of the business, the kind of proximity that teaches you how systems break in production, under real load, with real consequences. That grounding still shapes how I judge feasibility and risk.
From there I moved into enterprise analytics and platform leadership, where I learned that the harder problem was rarely the build. It was adoption: helping large, careful organizations trust and use what we delivered. In recent years my focus has been on AI and ML products within digital transformation programs, where regulation is a core part of the strategy, not an afterthought.
I do my best work owning a roadmap that has to balance what users need, what the technology can do, and what regulators require, and building the product function inside organizations that are ready to grow one. I care about the clients and customers on the other side of the work, and about leaving the teams I lead stronger than I found them.