Synthetic Intelligence &, Machine Learning, Cloud Security, Next-Generation Technologies &, Secure DevelopmentForrester Report Highlights Generative AI’s Control on Cloud Security Yamini Kalra • February 14, 2025  ,  ,
For years, sky safety has been playing catch up. Traditional security equipment, built on stable law sets and signature-based recognition, are struggling to keep pace with the level and elegance of modern fog threats. To counter this, security officials are turning to conceptual AI for intelligence-driven protection that you forecast, detect and respond to risks in real time.
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Gen AI is poised to enhance surveillance for cloud infrastructure-native and third-party security solutions and software-as-a-service, or SaaS game protection, according to a Forrester .
Being able to create scripts and understand how to fix problems is probably the biggest benefit that we see out there, according to Andras Cser, vice chairman and principal analyst for safety and risk control at Forrester Research and the report’s lead author, to Information Security Media Group.
LLMs and GANs to Boost Cloud Security
One of the most powerful developments is AI-driven multi-signal knowledge. Where tradition safety models process specific security signals in isolation, gen AI ingests, correlates and contextualizes data from diverse sources- including endpoint telemetry, network traffic, encrypted communications and yet dark web intelligence. This holistic approach helps security teams focus on the most pressing threats, reducing false positives, and ensuring more accurate threat detection.
Gen AI algorithms are generally used in identity and access management, security analytics, security information and event management, or SIEM, and fraud management, including detection of deepfakes and other AI-generated cyberthreats. Forrester anticipates that cloud security solutions will use large transaction models for threat detection, large transaction models for copilots and copilots, and generative adversarial networks to combat AI-driven attacks by pitting AI against AI.
According to the report, cloud workload security providers are integrating gen AI to improve threat detection and response. The technology will improve security investigations ‘ query generation, automate remediation, and improve policy enforcement for cloud infrastructure. Additionally, it will make it easier to create guest OS-level threat detection and network policy creation, giving you more proactive protection from threats that are developing.
Gen AI Aids Shadow SaaS Detection
” We see certain aspects of gen AI being applied in this space- particularly in understanding how applications, especially SaaS platforms, connect and interact”, Cser said.
As SaaS configurations get more complex and interconnected, human insight and traditional rules-based methods for detecting cloud risks lose effectiveness. Forrester anticipates that gen AI will contribute the most to cloud security through shadow and approved SaaS application detection and risk assessments, enhancements of data security posture management, and copilots for policy management, investigation, and reporting.
Although “detection is relatively straightforward and deterministic,” he said,” the real challenge lies in remediation- addressing over-permissioned or misconfigured environments in a controlled and effective way. Gen AI can add the most value by automating corrective actions and improving security postures in this area.
Gen AI Promises to Lower Costs
Beyond its security benefits, gen AI could reshape the economics of cybersecurity operations. Security teams frequently have too many tasks to handle, with more alerts, compliance requirements, and more sophisticated adversaries. By automating time-consuming tasks such as threat detection, policy generation and remediation, gen AI frees up security teams to focus on strategic initiatives.
” It is essentially another way to gain better understanding of labor and how to conduct that labor,” Cser said. For organizations grappling with shrinking budgets and increasing workloads, this is a game-changer.
Additionally, the Forrester report made a point about how key exchanges and cryptographic algorithms are traditionally a resource-intensive field.
The Risks of Gen AI in Cloud Security
Governance is a significant hurdle. Gen AI models are more complicated than traditional AI systems, making them more difficult to govern. The risk of hallucinations, privacy protections, and intellectual property protection are urgent issues. He claimed that the general AI’s explainability and decision-making quality are lacking in the required degree.
A new generation of AI systems are also susceptible to adversarial attacks. The security of these systems may be compromised by model poisoning and exploitation risks, which could give rise to unauthorized access to model-based security measures.
For cloud security professionals who want to use gen AI in production, “avoiding hallucinations and ensuring decision quality are prerequisites,” said Cser.