Midsized companies are investing heavily in AI tools and digital platforms — only to realize too late that their foundation isn’t solid.
Disconnected systems, poor data quality and outdated infrastructure are causing many to redo work, spend more on back-end fixes or miss out on meaningful ROI. In a time of tightening budgets and increased scrutiny, these missteps carry real costs.
This is the challenge of digital transformation in an uncertain environment. The temptation is to move fast — but when you move without a roadmap, you lose time, trust and money. AI can absolutely drive resilience, growth and efficiency. But it has to be built on a tech stack that’s ready.
Here are five diagnostic questions to help you assess whether your infrastructure can support AI — and what foundational steps might be needed before scaling your efforts:
1. Is your data centralized and clean?
AI is only as powerful as the data you feed it. If your organization is storing information in spreadsheets, PDFs or legacy systems that don’t integrate, you’re not just limiting potential — you’re introducing risk.
What to look for:
- Duplicate records, manual data pulls or inconsistent naming conventions
- Data cleanup efforts that never seem to stick
- Separate systems for finance, HR, CRM, etc. that don’t “talk” to each other
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