Rocket Software Study Reveals 94% of Financial Services Leaders Rank AI as a Top IT Priority
According to the new “Mainframe AI Study,” AI is now a top priority within enterprises, with 94% of financial services IT leaders ranking the enhancement of IT operations with AI as a high or top priority. Commissioned by Rocket Software, a global technology leader in modernization software, the Study surveyed organisations from the U.S., UK, France, Germany, and the Netherlands, in the banking and financial services industry.
The research reveals a maturing market, with 83% of respondents increasing their AI investments for IT operations and cybersecurity in the past year, with 38% reporting significant increases. Having moved beyond the hype cycle, 42% of organisations say they are running AI in production at scale across multiple teams and systems.
However, the study also reveals points of friction, as organisations work to expand their AI adoption. Indeed, while starting out appears less of an issue, 40% of organisations say initiatives stall while scaling organisation wide.
This is often due to security, compliance and governance considerations, which appear to be the primary guardrails for enterprise AI deployment:
- Regulation is still the brake pedal: 78% of respondents say that regulatory considerations significantly or extremely limit their ability to deploy AI
- Auditability isn’t optional: 88% rate auditability as very or extremely important when adopting AI for IT operations and security
- Governance controls top the trust checklist: Strong governance controls and approval workflows are cited as the number one requirement organisations look for before trusting AI in production
The Rise of Agentic AI
43% of respondents say conversational AI is too dependent on prompt quality and user expertise for practical operational use. To bridge this gap, 43% of firms say they are already blending conversational and agentic AI, with usage skewing further agentic at larger enterprises (47% of $1B+ firms). Half of the organisations surveyed are ready to deploy agentic AI to detect anomalies and correlate signals across systems, making it the top-cited use case in the market.
The Mainframe Skills Gap
Amid a significant skills shortage, with 81% of leaders calling their mainframe systems skills gap very or extremely significant, organisations are turning to AI. In fact, 87% of respondents believe AI will significantly or dramatically close the mainframe skills gap within the next two years. Most organisations report that mainframes strengthen their AI outcomes rather than limiting them. This positions the mainframe as an advantage when it comes to AI, dispelling the myth that legacy infrastructure hinders progress.
As for the financial ROI of these deployments, 91% of respondents find AI-driven diagnostics credible for reducing mean-time-to-resolution (MTTR), expecting a 20%+ reduction when implemented well. When it comes to justifying further funding, compliance beats traditional cost-cutting, with 44% citing reduced compliance risk and easier audits as the top investment triggers.
“Enterprise AI has clearly moved beyond the pilot phase, but scaling is where many organisations hit a wall, with regulatory, auditing and governance considerations common barriers,” said Neil Fowler, SVP of hybrid cloud engineering at Rocket Software. “As we move beyond the chatbot, advanced agentic AI solutions are proving they can support mission-critical systems.
“What’s more, while the mainframe skills gap is a known challenge, this Study shows that the mainframe itself is an AI advantage. With the right AI partner and agentic platform in place, organisations can confidently scale their AI initiatives, reduce operational complexity, and modernise without disrupting existing systems.”
Source: Rocket Software
IBM Study: One in Four Malicious Breaches are AI-Enabled, Costing Companies $6 Million on Average
One in four malicious breaches were AI-enabled – a 56% increase over last year – and these breaches cost an average of $6 million, roughly $1 million more than the global breach average of $4.99 million, according to IBM’s 2026 Cost of a Data Breach Report.
These attacks, compromised of mostly deepfake impersonation and AI-enabled malware, are reshaping breach economics. Attacks are getting faster and cheaper to launch, while breaches keep getting more expensive to find and fix. Companies that reported using AI and automation in security operations cut breach costs by an average of almost $2 million dollars, yet one in four organizations have still not adopted these tools in their security operations.
This growing imbalance—where attacks can be launched for thousands while breaches cost millions—is fundamentally changing the economics of cyber risk.
Frontier AI Threats Driving Earlier Action
Organizations are starting to act on future risk, rather than waiting for an incident. In separate follow-on research conducted by Ponemon Institute, 85% of organizations said they plan to increase security spending after becoming aware of advanced frontier AI cyber capabilities – compared to just 64% that reported in the initial research that they plan to increase security spend after experiencing a breach.
But a gap remains where attackers are moving fastest. While more than 50% reported using agents for threat detection and containment, only 18% apply agents to vulnerability management, leaving known exposures to linger even as AI shortens exploit windows. Three quarters of organizations say frontier AI threats are prompting them to rethink how agents are deployed across their security operations.
“What’s changing is the economics of cyberattacks. AI is making attacks faster and cheaper, while breaches keep getting more expensive. When organizations have an extended gap between discovery and remediation, that imbalance shows up directly in breach costs,” said Suja Viswesan, VP, IBM Security Software. “The priority now is to eliminate that lag—building remediation into development workflows, securing identity at runtime, and fixing risks at the speed attackers are already moving.”
Critical Infrastructure Face Higher AI-Driven Risk
Most AI-driven attacks reported in the study targeted critical infrastructure sectors (62%), with financial services and energy organizations experiencing the highest concentration, raising the risk of broader systemic disruption. Financial services breaches were reported to cost, on average, $6.3 million, while energy breaches cost on average $5.2 million. The concentration of attacks across these sectors increases the potential for cascading impacts across economies, supply chains, and essential services.
Other Key Findings:
- AI’s Weakest Link. More than 20% of organizations reported a breach targeting AI models or applications. The most common causes were weaknesses in surrounding systems: compromised APIs, applications, or plug-ins (27%) and cloud misconfigurations affecting AI workloads (27%).
- Encryption Gaps Persist as Quantum Risk Looms. Core weaknesses in encryption and cryptographic management continue to expose organizations, even as quantum-safe investments grow. Only 37% of breached organizations stated that they encrypt sensitive data both at rest and in transit, and just 34% have visibility into cryptographic assets.
- Ransomware Actors Weaponize Reputation. Reported ransomware incidents rose compared to the year prior (39% vs. 34%), with attackers increasingly using AI to automate and scale. While operational disruption still plays a role, attackers are shifting toward higher-impact pressure—most commonly exploiting brand reputation (41%), followed by employee data (35%) and intellectual property (31%).
- The 2026 report, conducted by Ponemon Institute and sponsored and analyzed by IBM, is based on breaches experienced by 602 organizations globally between March 2025 and February 2026. The follow-on study was conducted in May 2026, when 456 of the 602 organizations from the CODB research responded. Of these organizations, 78% (356) were aware of recent reports about highly advanced frontier models such as Mythos.
Source: IBM
IBM and Red Hat Offer Lightwell at No Cost to Universities, NGOs and Think Tanks
IBM and Red Hat have announced a new program providing Lightwell—which combines AI-driven automation with human engineering expertise to identify, validate and remediate vulnerabilities in open source software—at no charge to over 185 leading research universities and 100 major nongovernmental organizations (NGOs) and think tanks. Eligible institutions can access Lightwell’s library of validated fixes for open source software vulnerabilities, helping them secure the software and focus resources supporting research, education, humanitarian programs and other public-interest work.
Open source software underpins university research environments, teaching platforms and campus operations, as well as the systems NGOs and think tanks use to conduct policy research and serve communities around the world. Yet many of these institutions lack the resources and specialized engineering capacity required to keep pace as AI accelerates the discovery and potential for exploitation of software vulnerabilities.
Through this initiative, eligible institutions will receive access to Lightwell, including a growing library of remediated, digitally signed and validated open source dependencies that can be integrated into existing software pipelines. Lightwell is designed to deliver validated fixes for the specific software versions organizations already run, helping them address vulnerabilities without forcing disruptive upgrades or requiring access to their proprietary code, data or research.
“Lightwell combines automated remediation with deep open source engineering expertise and contributes fixes back upstream,” said Matt Hicks, President and Chief Executive Officer, Red Hat. “Expanding access will help strengthen both participating institutions and the open source communities on which they depend.”
Source: IBM
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