Shadow AI presents a $670,000 dilemma that many organizations are unaware they are facing.

The IBM 2025 Cost of a Data Breach Report, published today in collaboration with the Ponemon Institute, reveals that breaches involving unauthorized employee use of AI tools average a cost of $4.63 million for organizations. This figure is nearly 16% higher than the global average of $4.44 million.

Based on 3,470 interviews with 600 organizations that experienced breaches, the research highlights the rapid adoption of AI outpacing security measures. While only 13% of organizations reported AI-related security incidents, a staggering 97% of those breached did not have adequate AI access controls. An additional 8% were unsure if AI systems had been compromised.

“The data indicates a growing divide between AI adoption and oversight, which threat actors are beginning to exploit,” said Suja Viswesan, Vice President of Security and Runtime Products at IBM. “The report underscores a deficiency in basic access controls for AI systems, leaving sensitive data exposed and models vulnerable to manipulation.”

Shadow AI and Supply Chains: Prime Targets for Attacks

The report identifies that 60% of AI-related security incidents led to compromised data, and 31% disrupted daily operations. Customer personal identifiable information (PII) was compromised in 65% of shadow AI incidents, significantly higher than the 53% global average. Governance is a major weakness in AI security, with 63% of breached organizations either lacking AI governance policies or still developing them.

“Shadow AI is akin to doping in the Tour de France; people seek an edge without considering long-term repercussions,” Itamar Golan, CEO of Prompt Security, told VentureBeat. His company has cataloged over 12,000 AI apps, detecting 50 new ones daily.

VentureBeat continues to observe adversaries' strategies surpassing current defenses against software and model supply chain attacks. The report highlights supply chains as the primary attack vector for AI security incidents, with 30% involving compromised apps, APIs, or plug-ins. It states: “Supply chain compromise was the leading cause of AI security incidents. Security incidents involving AI models and applications varied, but supply chain compromise (30%) including compromised apps, APIs, and plug-ins topped the list.”

The Rise of Weaponized AI

All forms of weaponized AI, including LLMs designed to enhance tradecraft, are rapidly expanding. Sixteen percent of breaches now involve attackers using AI, particularly for AI-generated phishing (37%) and deepfake attacks (35%). Models such as FraudGPT, GhostGPT, and DarkGPT are available for as low as $75 a month, tailored for attack strategies like phishing, exploit generation, code obfuscation, vulnerability scanning, and credit card validation.

The more refined an LLM, the higher the likelihood it can be directed to produce harmful outputs. Cisco’s The State of AI Security Report notes that fine-tuned LLMs are 22 times more likely to produce harmful outputs than base models.

“Adversaries are not just using AI to automate attacks; they’re using it to blend into normal network traffic, making detection harder,” Etay Maor, Chief Security Strategist at Cato Networks, recently told VentureBeat. “The real challenge is that AI-powered attacks are not single events; they’re continuous processes of reconnaissance, evasion, and adaptation.”

As Shlomo Kramer, CEO of Cato Networks, warned in a recent VentureBeat interview: “Companies have a short window to avoid being caught with fragmented architectures. Attackers are moving faster than integration teams.”

Governance: A Vulnerability Exploited by Adversaries

Among the 37% of organizations claiming to have AI governance policies, only 34% conduct regular audits for unauthorized AI. Just 22% perform adversarial testing on their AI models. DevSecOps emerged as the top factor in reducing breach costs, saving organizations an average of $227,192.

The report’s findings illustrate how deprioritizing governance affects long-term security. “A majority of breached organizations (63%) either don’t have an AI governance policy or are still developing one. Even with a policy, less than half have an approval process for AI deployments, and 62% lack proper access controls on AI systems.”

The majority of organizations lack essential governance to mitigate AI-related risks, with 87% acknowledging the absence of policies or processes. Nearly two-thirds of breached companies do not regularly audit their AI models, and over three-quarters fail to conduct adversarial testing, leaving critical vulnerabilities exposed.

This delayed response pattern to known vulnerabilities extends beyond AI governance to fundamental security practices. Chris Goettl, VP Product Management for Endpoint Security at Ivanti, emphasizes a shift in perspective: “What we currently call ‘patch management’ should more aptly be named exposure management—or how long is your organization willing to be exposed to a specific vulnerability?”

The $1.9M AI Dividend: The Value of Smart Security

Despite the increasing prevalence of weaponized AI, the report provides optimism for combating adversaries’ advancing tactics. Organizations fully leveraging AI and automation save $1.9 million per breach and resolve incidents 80 days faster. According to the report: “Security teams extensively using AI and automation shortened their breach times by 80 days and reduced average breach costs by USD 1.9 million compared to organizations not using these solutions.”

The contrast is striking. AI-powered organizations spend $3.62 million on breaches, compared to $5.52 million for those without AI, resulting in a 52% cost difference. These teams identify breaches in 153 days, compared to 212 days for traditional approaches, and then contain them in 51 days, versus 72 days.

“AI tools excel at rapidly analyzing vast amounts of data across logs, endpoints, and network traffic, detecting subtle patterns early,” noted Vineet Arora, CTO at WinWire. This capability transforms security economics: while the global average breach cost is $4.44 million, extensive AI users operate 18% below that benchmark.

Yet, adoption remains challenging. Only 32% use AI security extensively, 40% deploy it in a limited way, and 28% do not use it at all. Mature organizations evenly distribute AI across the security lifecycle, typically with the following allocation: 30% prevention, 29% detection, 26% investigation, and 27% response.

Daren Goeson, SVP Product Management at Ivanti, reinforces this: “AI-powered endpoint security tools can analyze vast amounts of data to detect anomalies and predict potential threats faster and more accurately than any human analyst.”

Security teams aren’t lagging; however, 77% match or exceed their company’s overall AI adoption. Among those investing post-breach, 45% choose AI-driven solutions, with a focus on threat detection (36%), incident response planning (35%), and data security tools (31%).

The DevSecOps factor further amplifies benefits, saving an additional $227,192, making it the top cost-reducing practice. Combined with AI’s impact, organizations can cut breach costs by over $2 million, transforming security from a cost center to a competitive differentiator.

Why U.S. Cybersecurity Costs Reach Record Highs While Others Save Millions

The 2024 cybersecurity landscape revealed a notable paradox: as global breach costs fell to $4.44 million, marking their first decline in five years, U.S. organizations saw their exposure soar to an unprecedented $10.22 million per incident. This divergence signals a fundamental shift in how cyber risks manifest across geographic boundaries. Healthcare organizations continue to bear the heaviest burden, with an average cost of $7.42 million per breach and resolution timelines extending to 279 days—five weeks longer than their peers in other industries.

The operational toll is equally severe: 86% of breached organizations report significant business disruption, with three-quarters requiring more than 100 days to restore normal operations. Perhaps most concerning for security leaders is the emergence of investment fatigue. Post-breach security spending commitments have dropped from 63% to just 49% year-over-year, suggesting organizations are questioning the ROI of reactive security investments. Among those achieving full recovery, only 2% managed to restore operational status within 50 days, while 26% required over 150 days to regain operational footing. These metrics highlight a harsh reality: while global organizations improve their ability to contain breach costs, U.S. enterprises face an escalating crisis that traditional security spending alone cannot resolve. The widening gap demands a fundamental rethinking of cyber resilience strategies, especially for healthcare providers operating at the intersection of maximum risk and extended recovery timelines.

IBM’s Report Highlights the Critical Nature of Governance

“Gen AI has lowered the barrier to entry for cybercriminals. Even attackers with low sophistication can leverage GenAI to write phishing scripts, analyze vulnerabilities, and launch attacks with minimal effort,” notes CrowdStrike CEO and founder George Kurtz.

Mike Riemer, Field CISO at Ivanti, offers hope: “For years, attackers have been utilizing AI to their advantage. However, 2025 will mark a turning point as defenders begin to harness the full potential of AI for cybersecurity purposes.”

IBM’s report provides actionable insights for organizations:

1. Implement AI governance now – With only 45% having approval processes for AI deployments
2. Gain visibility into shadow AI – Regular audits are essential when 20% suffer breaches from unauthorized AI
3. Accelerate security AI adoption – The $1.9 million savings justify aggressive deployment

As the report concludes: “Organizations must ensure chief information security officers (CISOs), chief revenue officers (CROs), and chief compliance officers (CCOs) and their teams collaborate regularly. Investing in integrated security and governance software and processes to bring these cross-functional stakeholders together can help organizations automatically discover and govern shadow AI.”

As attackers weaponize AI and employees create shadow tools for productivity, the organizations that thrive will embrace AI’s benefits while rigorously managing its risks. In this evolving landscape, where machines battle machines at speeds humans cannot match, governance isn’t just about compliance; it’s about survival.