Organizations currently use an average of 112 SaaS applications. This is a number that continues to grow. In a 2024 survey, 49% of the 644 respondents who frequently used Microsoft 365 thought that there were less than 10 apps connected to the platform, despite the fact that over 1,000 Microsoft 365 data showed over 1,000 SAAS and SAAS connections per deployment. And it is one major SaaS provider. Imagine other important, unexpected security risks:
Each SAAS app has a unique security configuration. You misunderstand the incorrect risk. Business-critical apps (CRM, finance and collaboration tools) store huge amounts of sensitive data and make them the main target for attackers. Third-party integration with shadows introduces hidden vulnerabilities that are often not noticed. Large and small third-party AI service providers (such as audio/video transcription services) may not comply with legal and regulatory requirements or may properly test and review the test and review code.
Thousands of developers push changes every day to major SaaS providers. Understanding each SAAS app, assessing risks and ensuring configuration is overwhelming and inhumane. And much of it is just noise. Perhaps nothing malicious or massive has happened, but small details can often be overlooked.
Traditional security approaches cannot simply be expanded to meet these requirements, and organizations are exposed to potential violations.
AI: The only way to maintain
The complexity of SaaS security outweighs the resources and efforts needed to ensure it. AI is no longer an option, it’s essential. AI-driven security solutions such as Askomni with Adpomni, which combines Generated AI (or Genai) with Advanced Analytics, translate SaaS security into:
✓ Provides instant security insights through conversational AI.
✓ Efficiently investigate security events.
✓ Turn complex SaaS security questions into clear and practical answers.
✓ Visualize risks for a deeper understanding.
✓ Break language barriers – Comprehensive support allows security teams to interact with Japanese, French and English AI. Multilingual support allows teams around the world to interact with security data in their native language. Increased accessibility and response times.
For example, the ability to sew contexts from heterogeneous data points allows Askomni to notify administrators of issues caused by over-assistance of privilege and guide the remediation process, taking into account access patterns, sensitive data, or compliance requirements. Beyond typical threat notifications, Askomni alerts administrators to new threats, explains potential consequences, and provides prioritized remediation procedures.
The power of AI + data depth
High quality data is the fuel that drives Genai, but it is often lacking. Genai is increasingly used to create synthetic data for simulation, detection testing, or red team exercises, but the quality of that data determines the effectiveness of the results.
Generation models require clean, relevant, and unbiased datasets to prevent inaccurate or misleading results from being produced. This is a major challenge in the cybersecurity domain where high fidelity threats, logs, and labeled incident data are rare or siloed.
For example, building a Genai model to simulate a cloud violation scenario requires access to detailed, contextual telemetry. This is not always available due to privacy concerns or lack of standardized forms.
However, Genai is a powerful tool that can automate threat research to accelerate incident reporting and streamline workflows for both researchers, engineers and analysts. However, its success depends on first solving the gap between data quality and availability.
With SaaS security, finding a fast and practical answer traditionally means sifting through your data. This takes time and requires expertise.
AI is just as effective as the data you analyze. The ability to analyze security events allows AI to provide deeper visibility into the SAAS environment, allowing threat detection with more accurate accuracy. Security teams benefit from the ability of AI to prioritize risks, correlate complex security observations, and provide recommendations based on real expertise.
With over 110 million users protected and over 200 million security events processed every day, Appomni guarantees:
Deep Visibility into SAAS Environments Accurate Risk Detection and Prioritization Based on Practical Security Insights
Real-world Impact: AI Behavior
Global Enterprise recently leveraged AI to evaluate its complex SaaS environment. At just a few prompts, Askomni efficiently analyzed the system, highlighting key areas of focus. Askomni provided the following insight that one customer can act quickly and revise:
Applications bypassing IP restrictions: Serious misconceptions. Unauthorized Self-Acceptance in Salesforce: Key Security Gap. Obsolete, high-risk applications: Flagged before being exploited.
Without AI, identifying these risks would have taken several hours or been completely missed.
The present and future belong to AI-driven SaaS security
AI not only enhances security for SaaS applications, but also redefines what is possible. Organizations using AI-powered security tools will gain a critical advantage in protecting their data and staying ahead of cyber threats.
Stop searching and start asking. Get SaaS Security Answers on Appomni.
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