I was tasked with identifying private PET recycling companies for a client conducting market due diligence in the circular economy/rPET space. The specific requirements were detailed:

Who: Company names and ownership structures
Where: Geographic locations (headquarters, facilities)
What: Input materials (types of PET waste they accept) and output products (recycled pellets, rPET flakes, fiber, etc.)
When: Company establishment dates and operational history
Business Model: Pure recyclers vs. integrated manufacturers

The deliverable was a comprehensive database with company profiles—essentially a complete market map of the private PET recycling industry.

Why AI?

The challenge with private companies is they don't appear in standard databases. Information is fragmented across trade publications, obscure industry websites, and regional directories. Manually, this would take 3-4 days or perhaps a week of searching, cross-referencing, and verification. I knew AI could systematically search these scattered sources, but the key would be instructing it properly.

My Starting Point

I'm somewhere between novice and intermediate with AI tools—actively exploring how to efficiently integrate AI into research workflows. I've learned that the most critical factor isn't just using AI, but spending time upfront to craft the right instruction (prompt).