Tim Banting
Enterprises often assume that deploying AI will automatically transform customer experience (CX). Yet, without a unified data layer linking systems of record and systems of engagement, AI simply magnifies underlying data fragmentation.
Customer information scattered across CRMs, HR systems, and legacy databases prevents organizations from maintaining a single, reliable customer profile.
When AI attempts to draw insights from inconsistent or duplicated data, the result is mis-routed inquiries, invalid contact information, and poor personalization.
The reality is clear: AI doesn’t fix broken data – it amplifies it.
Why CX programs are stalling
Many AI projects have stalled because organizations underestimated the work required to cleanse, classify, and govern their data.
Enterprises are now realizing that robust data hygiene and clear taxonomies must precede AI integration. Until that happens, investment in advanced CX platforms risks compounding technical debt – delaying transformation and eroding ROI.
Four lenses for evaluating CX and AI vendors
With this in mind, buyers should examine four core dimensions when assessing CX platforms:
- Data Architecture: Does the solution unify systems of record and engagement into one profile?
- Explainability: Can AI decisions be traced and audited? Enterprises must see the “workings out.”
- Openness: Does it support emerging interoperability standards such as MCP for agentic AI integration?
- Governance: Is the platform audit-ready, with clear compliance trails for regulators?
Our analysis suggests that by 2027, organizations that unify CX and communications data could reduce service costs by up to 25 percent and improve customer retention by 10–15 percent.
Action point for buyers
CX leaders should treat data unification as a strategic investment, not a technical afterthought. Every delay compounds technical debt and pushes AI value further out of reach.
Unifying data is not just about integration; it’s about creating the conditions for AI to finally deliver on its promise.
Find more data-driven business intelligence
Read my full analysis on topic, including the breakdown of the regulatory, financial, and operational pressures affecting CX data strategy, in this interview for CX Today.
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