Over the past two years, e-commerce has experienced a rapid surge of experimentation with AI. Agencies, brand owners, and even small boutique sellers rushed to build their own scripts, models, and GPT-powered apps. This first wave was exciting, but it also exposed a harsh reality: maintaining AI solutions in-house is harder than it looks.

A telling example comes from a recent conversation I had with the founder of a boutique Amazon agency that has been in the marketplace for over a decade. Founded and run by a veteran software developer with two decades of engineering experience, the agency even still employs a developer to build internal tools. Despite their technical depth and e-commerce expertise, they still found that maintaining AI-driven listing systems in-house was an impossible lift.

Amazon's algorithms, policies, and compliance requirements shift constantly. What worked last quarter was suddenly obsolete. As the founder summarized, "I realized I can't do everything best in-house. I need to focus."

This story repeats across the industry. Sellers and agencies found themselves bogged down in maintenance rather than execution. Internal AI projects became "dead tools", frozen in time while the market moved forward.

Between the collapse of in-house tools and the rise of reliable platforms came what can only be called Wave 1.5: the era of self-declared AI "experts." These consultants promised agencies and sellers success through clever prompt engineering and quick hacks, selling playbooks and templates as if they were scalable solutions.

For many, this phase produced short-term wins but little lasting infrastructure. The expertise was often overstated, and without robust systems, sellers found themselves once again chasing after the latest trick instead of building sustainable growth.

This middle wave was less about building technology and more about outsourcing belief. Trusting individuals who claimed they could bend large language models to Amazon's will. It lacked the needed embedding into users' workflows: there was no data integration, no system of record, and no ability to scale or adapt to changes in the marketplace.

The outcome was uneven at best and often led to frustration when those tricks stopped working.

We call this The Second Wave of AI in E-Commerce. This is not simply about specialized, maintained platforms, it is about a bold new era where AI solutions are built by true experts, integrated with ecosystem data sources, and designed to serve users' workflows so effectively that they can function as the system of record, embedded directly into the workflows of brands, agencies, and aggregators.

It is about scalable, continuously evolving infrastructure that adapts as fast as Amazon's own marketplace changes.

At the heart of this Second Wave is Flowin AI. Built natively for Amazon sellers, Flowin AI is continuously maintained, integrates with core data sources like Search Query Performance, and enforces compliance guardrails to protect against suppression. More than a tool, it is an operating system for brand managers, removing manual friction, embedding insights into daily decision-making, and automating optimization at scale.

This wave is about focus and leverage:

Focus: Agencies and brands concentrate on what differentiates them: strategy, storytelling, and client relationships, while delegating catalog management and optimization to Flowin AI.

Leverage: Instead of juggling prompts and spreadsheets, they plug into a platform that syncs across marketplaces, flags restricted keywords, generates compliant listings, and scales optimization from a handful of hero ASINs to the entire catalog.

Amazon's latest changes: Cosmo, Rufus, and increasingly strict catalog hygiene requirements make static listings and manual fixes obsolete. Indexing windows are shorter, compliance risks are higher, and the black box of Amazon search rewards catalogs that are continuously optimized. The Second Wave is the answer.

Leaders who adopt Flowin AI can:

• Launch new SKUs and expand internationally faster

• Reduce risk of listing suppression with automated compliance alerts

• Replace manual keyword wrangling with AI-driven research and optimization

• Scale catalog optimization across 100% of listings, not just the top 20%

The First Wave of AI in e-commerce was about experimentation. Wave 1.5 was hype and reliance on self-styled experts. The Second Wave, led by Flowin AI, is about embedding AI into the very fabric of e-commerce operations, creating reliability, scalability, and trust.

Even agencies with decades of Amazon experience and technical talent cannot keep pace with marketplace complexity on their own. The Second Wave provides the leverage to adapt, grow, and win.

Those who embrace Flowin AI today will not only gain a competitive advantage, they will help define the future of AI in e-commerce.