Fortanix® Inc., a global leader in data and AI security and a pioneer of Confidential Computing, today released the results of a new survey examining the current state of enterprise AI deployment and how regulated enterprises are balancing the security and compliance challenges of deploying AI. Among the findings: 93% of AI leaders understand that traditional encryption does not protect data while it is being processed by AI, and recognize security and compliance concerns, even as organizations send sensitive data to AI services they are concerned may expose proprietary information.

That tension is having real consequences: 59% of organizations have delayed an AI project in the past year due to data security or privacy concerns, and 41% have completely blocked a deployment over security. Regulatory compliance now ranks as the single biggest obstacle to deploying AI on sensitive data, cited by 46% of respondents, ahead of data exposure and exfiltration risk.

The survey found that many organizations are moving forward despite the above concerns: 61% of organizations still send sensitive data to public cloud AI services, even though 93% say they’re concerned about exposing proprietary prompts, models or intellectual property to AI infrastructure providers. Nearly 40% described themselves as “very concerned.”

“It’s clear that AI leaders in regulated industries have become educated about the fact that their data is at risk when a model starts processing it,” said Anand Kashyap, CEO and co-founder of Fortanix. “What they need is proof that the environments their models and data are processed in are secure and untampered. Confidential Computing gives organizations the proof and cryptographic assurance that their data and models stay protected while AI is running.”

Organizations Are Moving AI Closer to Their Data

Conducted by Atomik Research among 300 AI leaders across banking, financial services, healthcare, insurance and government, the survey suggests that enterprises are increasingly looking to change where and how AI is deployed rather than simply accept the risks of public cloud AI. 64% of organizations have deployed closed-weight frontier AI models on-premises, while 97% are at least somewhat likely to adopt leading AI models if they’re securely available on-premises.

Sovereignty is also becoming a strategic consideration: 95% say sovereign AI is important or critically important to their AI strategy. AI leaders expect hybrid environments to be their primary inference location over the next 24 months, ahead of hyperscaler cloud, fully on-premises deployment and neoclouds or AI factories combined.

Confidence in how AI inference is secured remains limited. Just 44% of AI leaders describe themselves as “very confident” that data is protected during inference, while 52% are only “somewhat confident.” When asked what would increase their confidence in deploying AI on sensitive data, advanced infrastructure security like Confidential Computing came out on top, cited by 38% of respondents, more than any other single answer.

Other key findings included:

  • 93% say they’re concerned about exposing proprietary prompts, models or intellectual property to AI infrastructure providers.

  • 61% of organizations send sensitive data to public cloud AI services.

  • 64% of organizations have deployed closed-weight frontier AI models on-premises.

  • 97% are at least somewhat likely to adopt leading AI models if they’re securely available on-premises.

  • 95% say sovereign AI is important or critically important to their AI strategy.

  • AI leaders expect hybrid environments to be their primary inference location over the next 24 months, ahead of hyperscaler cloud, fully on-premises deployment and neoclouds or AI factories combined.

The full report, “State of Enterprise AI Deployment,” is available for download at https://www.fortanix.com/resources/reports/state-of-enterprise-ai-deployment.

Methodology

The survey was commissioned by Fortanix and conducted by Atomik Research among 300 AI leaders, including heads of AI, chief AI officers, vice presidents of machine learning, ML engineering leaders, security leadership, data science leaders and applied AI leaders, at U.S. enterprises in banking and fintech, government, healthcare and life sciences, and insurance with 500 or more employees and at least $500 million in annual revenue. The survey was fielded July 17-29, 2026, with a margin of error of plus or minus 5.6 percentage points at a 95% confidence level.

About Fortanix

Fortanix is the global leader in data and AI security and a pioneer of Confidential Computing, delivering a unified platform to protect sensitive data, AI models, and applications across on-premises and multi-cloud environments—at rest, in transit, and in use. Built on hardware-enforced security, Fortanix enables workloads to run in tamper-proof, isolated enclaves, protecting against data leakage, model extraction, and unauthorized access, even from privileged insiders.

As enterprises scale modern AI factories, Fortanix provides a Confidential AI foundation built on attestation-based trust, secure key release, and zero-trust enforcement. This ensures AI systems remain verifiable, auditable, and trustworthy—while enabling crypto agility and long-term resilience through post-quantum cryptography (PQC).

Trusted by leading enterprises and sovereign entities in highly regulated industries and powered by an industry-standard approach to Confidential Computing supported by leading technology providers, including Intel, Microsoft, and NVIDIA, Fortanix enables organizations to safely use sensitive data and drive AI adoption with confidence.

Media gallery

About The Author
Business Wire