66% of IT leaders cite data infrastructure and data quality issues as barriers to agentic AI adoption

66% of IT leaders report uncertainty around data lineage, timeliness, and quality

40% of organizations report errors in data inputs ingested by AI.

45.9% of organizations cite data quality and schema issues as a barrier to automation

Security teams anticipate higher productivity (48%), faster response times (41%), and better data accuracy (40%) from intelligent workflows.

64% of governance leaders in Asia cite data quality and privacy concerns as top risks associated with agentic AI.