Gartner Predicts AI Applications Will Drive 50% of Cybersecurity Incident Response Efforts by 2028
Fifty per cent of all enterprise cybersecurity
incident response efforts will focus on incidents involving custom-built
AI-driven applications by 2028, according to Gartner, Inc., a business and
technology insights company.
“AI is evolving quickly, yet many tools –
especially custom-built AI applications – are being deployed before they’re
fully tested,” said Christopher Mixter, VP Analyst at Gartner. “These systems are
complex, dynamic and difficult to secure over time. Most security teams still
lack clear processes for handling AI-related incidents, which means issues can take
longer to resolve and require far more effort.”
Gartner recommends security leaders get involved
early in custom-built AI application projects to ensure sufficient time exists,
resources are planned and expectations are managed for adequate security
controls.
This is one of Gartner’s top cybersecurity predictions that Gartner recommends cybersecurity leaders to factor into their security strategies over the next two
years, along with the following
predictions.
By 2028, more
than 50% of enterprises will use AI security platforms to secure third-party AI
service usage and protect custom-built AI applications.
AI security platforms give
organizations a unified way to manage the new risks associated with rapid AI
adoption, such as prompt injection, data misuse and more. Centralizing
visibility and control, these platforms help CISOs enforce use policies, monitor
AI activity and apply consistent security guardrails across third-party and
custom AI applications. Security leaders must evaluate AI security platforms to
ensure they can secure both forms of applications.
Through 2027, manual AI
compliance processes will expose 75% of regulated organizations to fines
exceeding 5% of their global revenue.
Despite the distinct
approaches to regulation globally, AI regulations converge on a universal
demand for a systematic risk management approach. Even if CISOs can keep ahead
of security, privacy and cyber risk management regulations and standards, new
regulations covering AI safety call everything into question. For greater
success, Gartner recommends establishing cyber governance risk and compliance,
and enabling compliance through technology.
Through 2030, 33% of IT work
will be spent remediating AI data debt to secure AI.
Most organizations’ data is
not AI‑ready, with poorly
secured and unstructured data a major barrier to AI adoption. In response,
cybersecurity leaders are expanding data loss prevention to monitor and
restrict data flows triggered by GenAI and agentic AI data
access events and requests. Gartner recommends they collaborate with data and
analytics and AI leaders to define a structured program of data discovery,
assessment and access control remediation.
By 2027, 30% of organizations
will require comprehensive sovereignty of their cloud security controls to
address continued geopolitical turmoil.
Geopolitical turmoil and local regulations are
creating untenable data risks, which require many organizations to make
sovereignty a key part of their cyber resilience approach. This will
necessitate changes in vendor selection for cloud-tethered offerings and prioritization
efforts as geopatriation requirements intensify. Cybersecurity leaders must
play an active role in defining organizational sovereignty requirements,
including those required by local regulations.
By 2028, 70% of CISOs will use identity
visibility and intelligence capabilities to shrink the IAM attack surface,
reducing the risks of credential compromise.
Identity has become a primary attack surface as
organizations struggle to manage the rapid growth and complexity of human and
machine identities. This leaves visibility gaps left by isolated identity and
access management (IAM) tools and increases the risk of misconfigurations.
Gartner recommends these blind spots be addressed by integrating unified, AI‑powered
identity visibility and intelligence platforms to improve detection and
remediation.





























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