What Sarah Briseno Sees in AI for Hazardous Waste

By Siam Sukkhee Trading Co., Ltd — 2026-09-22 — Waste360 (recycling/scrap)

I watched someone spend three days sorting through emails last week. Not for any exotic reason—just trying to find which hazardous waste manifest got approved and when. It's like that across the industry.

Sarah Briseno at WasteLinq has spent years inside this problem. She's held roles across customer service, finance, waste profiling, and product management before landing in her current job as Chief Product Officer. That's not the usual CV—it's the kind of journey that teaches you how every piece of an operation connects to every other piece.

What she's learned is simple enough: most industrial hazardous waste operations still run on disconnected systems. Emails, phone calls, PDFs trapped in review cycles that can stretch for weeks. Profiling takes years of specialized expertise to do right, and there's real consequence to getting it wrong. Regulatory mistakes in hazardous waste aren't abstract. They matter.

WasteLinq built two AI tools to handle the mechanical parts: Profile Assist and Manifest Assist. The first automates data entry for waste characterization and flags routing options. The second generates compliant manifests and shipping labels without the manual paperwork dance.

But here's where Briseno pushes back on how people talk about AI in this space.

She's not arguing the software replaces the expert. It's the opposite. She says taking the busywork—the data entry, the form-filling, the endless documentation—off someone's plate lets them focus on the decisions that actually need human judgment. The regulatory gray areas. The edge cases. The things where you have to sign your name and own what happens.

Actually, that's not quite right. It's not about making experts faster. It's about making sure experts don't waste their time on work that a machine can handle competently.

There's another layer too. Hazardous waste moves between generators and transporters and disposal facilities. That industry runs on trust—on relationships that exist between companies and people. AI can speed up the paperwork that backs those relationships, but it doesn't create the trust itself. It can't. Someone still has to stand behind the decision.

That distinction matters because it explains why the software industry has mostly failed in hazardous waste. They tried to build generic enterprise systems and wondered why waste companies kept using spreadsheets instead. The problem isn't that waste people are stubborn. It's that generic tools don't speak the language of a regulatory environment that has real teeth.

What Briseno and her team did was build something specific to this corner of the world. Not a general platform. Not a buzzword delivery vehicle. A tool that understands RCRA and DOT and the maze of state-specific rules because the people using it live inside that maze.

I think there's a lesson there for anyone selling technology into heavily regulated industries. But more specifically, there's something in how Briseno talks about AI that rings true in a way most startup pitches don't. She's not promising to replace your people or revolutionize your business with machine learning. She's promising to make the paperwork move faster so your people can do what only people can do.

Whether the market has room for that kind of thinking, or whether we'll keep chasing the bigger story, is still an open question.

Source: "The human element will always remain essential when interpreting a regulatory gray area, handling an edge case, or being accountable when something goes wrong." — Waste360

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