In this fireside chat with Giuseppe Ianni, Marc Kase, CIO, Altman Plants, shared how repeated AI experimentation, stronger engineering practices, and a test-and-learn mindset helped the company solve a complex EDI challenge and eliminate most incoming transaction errors.
Key Takeaways
Experimentation Turns Setbacks into Progress: Altman Plants attempted its EDI challenge multiple times before finding an effective solution, demonstrating that AI adoption often requires iteration. Treating unsuccessful experiments as learning opportunities creates the foundation for continuous improvement.
AI Solves Complex Matching Problems: By combining large language models with curated data and well-designed APIs, Altman Plants can identify product matches that traditional character or fuzzy matching could not reliably resolve. This enables the company to address nuanced data challenges with greater accuracy.
Engineering Discipline Makes AI Scalable: The breakthrough came from pairing AI capabilities with the right technical foundation, including ERP customizations and structured APIs. This combination allows experimentation to become an engineered process that can deliver measurable operational improvements.
Kieron Allen
Analyst
Cloud Wars, Agent and Copilot
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