Terracon’s Head of Business Transformation, David Harwood, makes a clear case: before AI, fix data and process.

He outlines how Terracon audited ERP/CRM issues (synonyms, homonyms, duplicates), moved project files from office servers to a SharePoint backbone with auto-tagging and taxonomy, and now governs intranet content to curb “old vs. new” confusion. David shares his “data lake districts” metaphor (lake house, warehouse, trailer park, homeless) to triage sources and describes assigning owners to the data store and its APIs. We cover no-/low-/pro-code AI tiers, internal vs. client-facing apps, and the human side—reducing fear of change, protecting creativity, and preventing burnout when lower-level tasks get automated.

If you need a roadmap to get from scattered files to AI-ready data with process clarity and cultural buy-in, this episode shows what it looks like at enterprise scale.

In this episode:

• Why “data + process” are the real foundations of AI
• File migration, taxonomy, and practical governance
• ERP realities: duplicates, synonyms, and messy definitions
• A roadmap from no-code → low-code → pro-code AI
• The human risk: adoption fatigue and burnout

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