This interview analysis is sponsored by Securiti and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
The promise of enterprise AI meets a reality where models and agents can access sensitive data faster than organizations can see, govern, or explain that access — a gap that leaves leaders unable to prove compliance, contain exposure, or defend how AI is using their data.
Stanford HAI reports 88% of organizations now use AI in a business function, while documented AI incidents jumped to 362 in 2025, up from 233 the year before. The GAO found that AI use in financial services introduces data quality, privacy, and cybersecurity risks regulators are actively examining.
The Cloud Security Alliance reports that only 35% of organizations have full visibility into where unstructured data resides. Just 9% have real‑time scanning capabilities, and 23% cannot scan unstructured data for risks at all — structural limits that constrain what any AI system can do well.
Emerj’s Yolandi de Weerdt recently hosted a conversation with Chris Joynt, Director of Product Marketing at Securiti; James Dean, AI Specialist at Google Cloud; Mark Crean, Regional Vice President of Sales at Securiti; Dr. Oscar Rodriguez, Vice President, Data Analytics at Citi; and Todd Vancil, Vice President of Veeam’s Securiti AI Sales Engineering Team.
