IBM announced the general availability of three new Z software tools designed to enhance security and operational efficiency for critical infrastructure. The new tools, IBM zSecure Detection, IBM zSecure Secret Manager, and IBM Z Database Assistant, aim to address evolving technological challenges such as frontier model attacks and the need for agentic AI in data operations. This announcement underscores IBM's commitment to innovating its mainframe offerings to meet modern sovereignty and regulation requirements.

New Security and Operational Tools

The release includes three distinct tools tailored for the IBM Z and LinuxONE environments. These solutions are intended to help enterprises monitor threats, manage certificates, and optimize database performance using AI.

IBM zSecure Detection

IBM zSecure Detection provides enterprises with a comprehensive tool to detect, investigate, and respond to threats on z/OS. It monitors system activity for ransomware and suspicious behavior, helping organizations strengthen their security posture amidst evolving threats.

IBM zSecure Secret Manager

Addressing the burden of certificate management, IBM zSecure Secret Manager offers a secure and automated solution for z/OS and LinuxONE environments. Powered by IBM Vault Self-Managed for Z, it helps teams manage shortened certificate lifecycles and fragmented management strategies.

IBM Z Database Assistant

The IBM Z Database Assistant leverages agentic AI to optimize database administrator (DBA) performance. This tool is designed to accelerate tasks and ensure trusted data remains continuously available, catering to the shifting needs from data access to data intelligence.

IBM Z continues to be recognized for its resiliency, with an average yearly downtime of less than a third of a second and 99.999999% uptime according to the ITIC 2025 Global Server Hardware, Server OS Reliability Report. The new software tools are part of IBM's broader strategy to innovate and defend the full stack for the future.

A new global study by the IBM Institute for Business Value, published on June 17, 2026, finds that as enterprises embed AI deeper into core business operations, most surveyed organizations remain locked into AI systems they cannot easily change—reinforcing the growing importance of AI sovereignty to maintain business continuity and performance. Titled The Calculus of AI Sovereignty, the study is based on insights from 1,000 senior executives responsible for AI, data, technology, or related enterprise capabilities across 16 countries and 17 industries.

Key Findings: Dependency and Lack of Visibility

The study highlights a widespread inability among enterprises to adapt or switch AI systems, creating significant operational constraints. A majority of surveyed executives report challenges across multiple dimensions of AI control, as summarized below:

Surveyed leaders report an average of six AI-related disruptions over the past two years, largely driven by vendor services. Respondents also cite unexpected changes across the AI ecosystem, including price increases, usage restrictions, model deprecations, and performance degradation.

The Cost of Lost Control

IBM Senior Vice President and Chair, EMEA and APAC, Ana Paula Assis, said in the study foreword: "AI has introduced new forms of dependency that evolve faster than traditional governance, procurement, or technology cycles were designed to handle. That is why AI sovereignty has become one of the most defining leadership issues of this moment. The stakes are no longer technical; they are economic. Any loss of control can translate directly into margin pressure, compliance exposure, or outright business disruption."

Performance Gap Between Leaders and Laggards

The study identifies a significant performance divide between organizations that have built advanced AI control capabilities and those that have not. Key findings on this gap include:

• Organizations with the most advanced AI control capabilities see less AI downtime and protect 55% more operating profit from AI-driven disruptions.
• Only 7% of surveyed organizations operate at this advanced level, signaling a widening gap between those building adaptable AI systems and those constrained by dependency.
• 72% of surveyed executives say they would accept a 20% cost increase to maintain AI vendors if it improved strategic flexibility.

Multi-Vendor Environments: Strategy vs. Reality

Most surveyed organizations (73%) describe their AI environments as intentionally multi-vendor. However, vendor diversity in practice appears to be driven less by deliberate strategy and more by internal and operational realities. The leading drivers cited by respondents are:

• Independent business unit decisions and geographic necessity, each cited by 69% of respondents.
• Legacy complexity—reflecting mergers, acquisitions, and historical decisions—cited by 57% of respondents.

Study Methodology

The IBM Institute for Business Value, in collaboration with Oxford Economics, conducted a global survey between February and April 2026 to examine how organizations structure control across the AI stack and how these choices relate to resilience, performance, and operating economics. The study is based on responses from 1,000 senior executives across 16 countries and 17 industries. Additional analysis identified distinct AI control profiles by segmenting organizations based on how they structure control across data, models, infrastructure, and applications.