Adam Buhler

I work at the translation layer where enterprise AI actually becomes useful: messy workflows, trusted data, governance constraints, product gaps, and user adoption.

I’m a Manager in PwC’s Assurance Innovation & Technology / Data Enablement Team with about 12 years across ERP data acquisition, data transformation, audit analytics, platform adoption, and global enablement. My foundation is SAP/general ledger data, SQL, common data models, extraction/transformation workflows, and the operational side of making data products stick.

My recent AI work has focused on practical, responsible enablement rather than AI theater: supporting an AI-enabled master-data standardization engagement using Databricks and LLM tooling; serving on on the Data Enablement AI Catalyst team; training colleagues on system prompts, RAG/tool patterns, context windows, and responsible enterprise AI use; coaching AI project teams; and prototyping AI-assisted workflows that translate request specs into code and pull requests.

I’m especially interested in AI systems that improve real business workflows: data readiness, agentic work patterns, governance, adoption, and measurable value.