How to Navigate the Trust Paradox in AI Adoption: Insights from Informatica’s 2026 CDO Report

How to Navigate the Trust Paradox in AI Adoption: Insights from Informatica’s 2026 CDO Report

From Don't Panic! It's Just Data by EM360Tech

March 18, 2026 · 28 min · Season 1 · Episode 59

About this episode

The episode discusses the findings of Informatica’s 2026 CDO Report, highlighting the trust paradox in AI adoption amidst uneven data foundations.

Enterprise AI budgets are climbing, but the data foundations beneath them remain uneven. In this episode of  Don’t Panic, It’s Just Data ,  Kevin Petrie , VP of Research at  BARC , and  Nathan Turajski , Senior Director, Product Marketing at  Informatica , examine the findings of the  CDO Insights 2026  report , which argues that executive confidence in AI may be outpacing organisational readiness. The study centres on what it describes as a growing “trust paradox” as Chief Data Officers are accelerating AI initiatives even as data quality, governance maturity, and AI literacy struggle to keep up.  The Trust Paradox The report exposes a striking disconnect. Turajski points out that while around 65 per cent of data leaders believe employees trust the data powering AI, 75 per cent say upskilling in data and AI literacy is essential. In other words, confidence is high, but readiness is lagging. This is the trust paradox where employees increasingly rely on AI outputs, while data leaders remain cautious about the quality, governance, and lineage behind those results. The risk is not scepticism but rather overconfidence. When AI-generated…

People in this episode

Guests: Kevin Petrie, Nathan Turajski

Topics covered

  • AI adoption
  • data governance
  • trust paradox
  • data quality
  • executive confidence

Keywords

  • CDO Insights 2026
  • enterprise AI budgets
  • data foundations
  • AI literacy

Mentioned in this episode

Products: Informatica

Books & works: Don’t Panic, It’s Just Data, Understanding the Trust Paradox in AI Adoption, Building Trusted Context for AI, The Importance of Data Quality and Completeness

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