Regulated Industries Face Growing Shadow AI Risks as AI Adoption Accelerates: Nutanix Report

Healthcare, financial services and public sector organizations are rapidly increasing their adoption of artificial intelligence, but concerns over shadow AI, data sovereignty, security and infrastructure readiness are emerging as major challenges, according to new findings from Nutanix.

The findings come from Nutanix’s eighth annual Enterprise Cloud Index (ECI) research, which includes new industry-specific reports examining how organizations in highly regulated sectors are adapting their infrastructure strategies to support growing AI workloads.

The research shows that while AI adoption is accelerating across these industries, many organizations are still working to modernize their infrastructure and strengthen governance frameworks needed to deploy AI securely and at scale.

Shadow AI Becomes a Major Business and Security Concern

One of the key issues highlighted in the research is the growing risk of shadow AI—the use of AI tools by employees or business units without appropriate IT governance or security oversight.

For highly regulated organizations, unauthorized AI usage can create additional risks involving sensitive data, regulatory compliance and data sovereignty. Organizational silos between business units and IT teams can further complicate AI governance.

Healthcare Organizations Prioritize Data Sovereignty

Healthcare organizations are increasingly adopting AI to improve operational efficiency, patient outcomes and clinical and administrative workflows. However, infrastructure readiness and the protection of sensitive patient information remain key challenges.

According to the Nutanix Healthcare ECI Report, 72% of healthcare IT leaders identify data sovereignty as a top infrastructure priority, while 83% consider unauthorized shadow AI tools a critical business and data risk.

The research also found that healthcare organizations expect to increase their use of generative AI (62%), agentic AI or autonomous agents (57%), and predictive analytics or machine learning models (55%) over the next three years.

Application containerization is also becoming an important component of healthcare infrastructure as organizations seek secure and portable environments for modern applications while maintaining control over sensitive data.

Financial Services Turn to Hybrid Infrastructure

Financial institutions are expanding AI use across areas including customer service, anomaly detection, in-branch personalization and other operational applications.

However, data sovereignty and security requirements continue to influence how financial organizations deploy cloud and AI workloads.

The Nutanix Financial Services ECI Report found that 86% of financial-sector executives believe unmanaged shadow AI tools create severe business risks.

Meanwhile, 62% of financial services IT leaders expect conversational and agentic AI to materially improve customer or employee experiences.

The report also found that 90% of financial services IT leaders say AI is meaningfully accelerating container adoption, while 79% identify data sovereignty as a high-priority or must-have factor.

Public Sector Faces AI Infrastructure Readiness Gap

Government agencies and educational institutions are also incorporating AI into areas such as benefits eligibility, fraud detection and other business operations.

However, infrastructure readiness remains a significant challenge.

According to the Nutanix Public Sector Report, 91% of government and education IT leaders surveyed believe unvetted AI usage creates severe mission and security risks.

The research further found that 73% of public sector infrastructure is currently not ready to run complex AI workloads on-premises.

At the same time, 87% of public sector technology leaders expect their reliance on application containerization to increase over the next three years.

Infrastructure Modernization Key to Responsible AI Adoption

Thomas Cornely, EVP of Product Management at Nutanix, said organizations across industries are working to move AI projects from experimentation toward delivering business value, but infrastructure requirements vary depending on the sector and workload.

He highlighted the need for infrastructure and operating models that provide flexibility, resiliency and security for both traditional and AI-powered applications at scale.

Mohammad Abulhouf, Vice President & General Manager, Middle East & Africa, Nutanix, said organizations across the region’s highly regulated sectors are increasingly adopting AI to improve services, accelerate innovation and strengthen resilience.

He added that as AI moves from experimentation into everyday operations, data sovereignty, security and governance are becoming essential foundations for responsible AI adoption.

Study Covered 1,600 IT and Engineering Executives

The Enterprise Cloud Index research was conducted in November 2025 by Wakefield Research and included responses from 1,600 cloud, IT and engineering executives with at least manager-level positions.

The respondents represented organizations with 500 or more employees across Australia, Brazil, France, Germany, India, Italy, Japan, Mexico, the Netherlands, the Kingdom of Saudi Arabia, Singapore, Spain, the United Kingdom and the United States.

The findings highlight a common challenge facing regulated industries: organizations are moving quickly to adopt AI while simultaneously having to strengthen infrastructure, security and governance.

As AI becomes more deeply integrated into business and public services, healthcare providers, financial institutions and government organizations will increasingly need infrastructure capable of supporting AI workloads while maintaining strong controls over sensitive data and regulatory compliance.