The Trust Paradox in AI Adoption
Most data leaders (96%) say their staff need more training to use AI responsibly. Yet employees often trust AI tools and the underlying data without having the necessary skills – a phenomenon the report calls the “trust paradox.”
Key Findings from the Informatica Report
Key statistics highlight the current state of AI readiness:
- Data literacy is a higher priority (82%) than AI literacy (71%).
- By Q1 2026, 79% of European firms expect to have generative AI in their workflows.
- 68% plan to pilot agentic AI.
- 77% admit AI visibility and governance lag behind employee usage.
- 55% are buying off‑the‑shelf AI agents rather than building their own.
Challenges Facing European Companies
Leaders cite four main concerns:
- Data quality and security.
- Lack of expertise in agentic AI.
- Insufficient observability and safety guardrails.
- Poor AI governance and visibility.
These issues hinder the ability to implement “responsible AI” at scale.
Priorities for Future Investment
Upcoming budgets are shifting to address the gaps:
- 23% of firms expect a significant increase in AI spending.
- Upskilling employees in data and AI literacy.
- Strengthening privacy, security, and governance frameworks.
- Investing in tools that improve AI observability and trust.
Chief Product Officer Krish Vitaldevara stresses that reliable data, rigorous governance, and a skilled workforce are essential for AI ROI.
Conclusion: Building Trust in AI
Deploying AI quickly is no longer enough. Success will be measured by how confidently organizations can trust their AI systems. By prioritising data reliability, governance, and employee upskilling, businesses can turn AI from a risky experiment into a trusted, revenue‑generating asset.