Building the Future of Enterprise AI: Lessons from 15 Years at the Intersection of Product, Strategy, and Scale | Anna E. Molosky

Over the past 15 years, I’ve built my career at the nexus of artificial intelligence, enterprise product strategy, and large-scale innovation. As a seasoned AI Product Management and Strategy Executive, I’ve led global initiatives that transformed how organizations build, scale, and commercialize AI platforms—delivering measurable, multi-billion-dollar business impact.

My work spans Amazon Web Services (AWS), Goldman Sachs, and global markets across the United States, United Kingdom, Europe, India, Japan, China, Brazil, and the Middle East. And if there is one thing these environments have taught me, it’s this:

AI-driven product strategy succeeds when technology, market need, and revenue discipline move in lockstep.

Below, I share the core principles that guide my approach to building AI products that redefine markets—and deliver real financial outcomes.

AI as a Revenue Engine, Not Just a Technology Bet

During my tenure at AWS, I architected a new AI-powered internal and external eCommerce Platform—designed not just to elevate customer experience, but to fundamentally transform how AWS generates and captures value.

By identifying unmet customer needs and uncovering net-new business opportunities, I developed a platform strategy that became one of AWS’s fastest-growing revenue engines.

Impact to date:

This reinforced a principle that shapes all my work:
Generative AI and agentic AI become transformative when tied directly to measurable business outcomes—not when adopted for novelty.

Product-Led Growth in an AI World

I specialize in using cutting-edge AI technologies to identify market-defining opportunities and convert them into high-value, revenue-driving products. My product-led growth (PLG) approach centers on:

This structure consistently unlocks market share, drives new customer segments, and accelerates ARR expansion across enterprise portfolios.

From Vision to Execution: Full Lifecycle Product Leadership

Great AI products require more than ideas—they require disciplined execution.

I lead the product lifecycle end-to-end, including:

My hallmark has become delivering hyperscale initiatives ahead of schedule and under budget, even in ambiguous, high-stakes enterprise environments.

Unlocking New Revenue Through Data: Lessons from Goldman Sachs

Earlier in my career, I founded and monetized a new Data Solutions & Analytics Business at Goldman Sachs by identifying and commercializing previously untapped proprietary datasets.

Financial impact:

This experience cemented one of my core beliefs:
Every organization sits on dormant value. Product leaders unlock it.

Leading Global Teams Through Complexity

My leadership style is inclusive, hands-on, and execution-driven. I’ve led globally distributed product, engineering, and strategy teams across:

I motivate teams by providing clarity, empowering innovation, and ensuring psychological safety—while staying relentlessly focused on outcomes.

My teams know me for navigating complexity with confidence and delivering transformative solutions faster than the organization expects.

A Recognized Global Voice in AI, Product Strategy & Product Management

Alongside my enterprise work, I am a widely recognized thought leader and a LinkedIn Top Voice in:

I contribute frameworks, insights, and perspectives that help organizations and practitioners understand the true path to building scalable, responsible, and revenue-generating AI.

Looking Ahead: AI as the Operating System for Modern Enterprise

We are entering an era where AI no longer enhances business—it runs it.

I believe the next generation of industry leaders will be defined by how effectively they:

My mission is to continue building the platforms, strategies, and teams that will shape this future.


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