The AI tipping point
New global research from IBM and Ponemon Institute reveals how AI-driven attacks are growing and how new threats from frontier AI models are forcing a global reckoning on security spending.
The global average cost of a data breach, in USD, a 12% increase over last year and a record high—driven by higher detection, escalation and lost business costs.
Increase in AI-driven attacks, led by AI deepfake impersonations and AI-enabled malware, which drove the highest volume of those incidents.
The global average breach cost, in USD, of an AI model inversion attack, reflecting the growing difficulty of protecting training data and sensitive information.
Cost savings, in USD, from extensive use of AI and automation in security, compared to organizations using none.
Key takeaways
Join IBM and industry cybersecurity experts as they unpack this year’s key findings, strategic takeaways and recommendations for how you can limit risk from emerging frontier AI model threats and safeguard your data, people and infrastructure.
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- Identity security
- Data security
- AI sovereignty
- Post quantum security
Secure and control agentic identities
As AI agents proliferate, security teams must transform identity access and control to secure agentic identities. They must ensure that AI agents operate safely through dynamic, identity-based access controls, tightly scoped permissions continuously enforced at runtime, human attribution and auditability.
Elevate AI data security practices
Implement strong data security fundamentals: data discovery, classification, real-time monitoring, threat response and achieve compliance simplification. Leverage AI and data security to protect data integrity and avoid compromise. These measures are essential as AI becomes both a threat vector and a security tool.
Manage and secure AI systems anywhere
As organizations scale AI across platforms, cloud and ecosystems, they can lose control over how models operate—and how data is transformed and accessed. To retain control, organizations should strengthen app, data and machine-agent security and ensure that cloud workloads are configured and monitored.
Prepare for post-quantum threats
Gaps in encryption and cryptography management expose organizations to risk. To manage cryptography in the quantum era, organizations should transition to post-quantum encryption algorithms and modernize security practices by discovering cryptography in their environments, analyzing vulnerabilities and remediating risks.
