Security and privacy identified as the top concerns for AI buyers
07:00 · July 5, 2026 · RSS APP - AI Security and Privacy
AI platforms must move beyond generic market data and provide insights that are specifically tailored to an organisation's unique internal context, according to technology intelligence firm IDC. While current artificial intelligence platforms can rapidly process broad information regarding market trends and vendor landscapes, they often struggle when faced with specific…
Summary
IDC research highlights that AI platforms often fall short when organizations seek insights tied to their own internal roadmaps, staffing models and operational constraints, instead defaulting to generic market data that offers limited strategic value. This shortfall contributes to broader adoption hurdles, as evidenced by the IDC Future Enterprise Resiliency and Spending Survey.
More than 75 percent of AI projects stall between proof-of-concept and production deployment. The dominant obstacles are not technical shortcomings but trust-related issues: 27 percent of organizations cite risks of exposing sensitive data, while 23 percent point to inadequate data governance. Security, privacy and governance concerns consistently outrank budget limits, skills gaps and integration difficulties for buyers evaluating AI solutions.
These findings underscore that successful scaling depends on platforms delivering context-specific analysis rather than broad trends, directly addressing the trust deficit that currently blocks most initiatives from reaching operational use.
Why it matters
Directly highlights actionable security and privacy risks for AI deployment that Dutch and EU practitioners must address under GDPR and emerging AI regulations. Provides clear data on governance gaps relevant to security professionals evaluating AI platforms.
