Securiti

2 weeks ago | securiti.ai | Ankur Gupta

Across industries, AI systems are no longer just tools acting on human prompts. The AI landscape is evolving rapidly, and AI systems are gaining more and more autonomy. Your virtual assistant can easily reschedule a meeting based on your previous habits. Or a customer service chatbot can simply offer you a refund without escalation. These are AI systems capable of adapting to new information and making decisions on their own.

3 weeks ago | securiti.ai | Ozair Malik

Enterprise security teams navigate a complex security stack, relying on a diverse suite of specialized yet siloed security tools. Picture a typical enterprise SOC where dashboards glow for CSPM, SIEM, DLP, CNAPP, IAM, etc. Alerts stream in from every console and analysts often struggle to identify critical data risks hidden within the noise of constant alerts.

1 month ago | securiti.ai | Ozair Malik

AI copilots and agents embedded in SaaS are rapidly reshaping how enterprises work. Business leaders and IT teams see them as a gateway to AI-driven efficiency for the enterprise, while security teams warn about data security concerns. Enterprise-grade AI copilots like Microsoft 365 Copilot, Dropbox’s Box AI, and GitHub Copilot empower employees to query vast datasets, generate documents, and write code at scale.

1 month ago | securiti.ai | Ankur Gupta

The fundamental truth of today’s competitive landscape is that businesses harnessing data through AI will outperform those that don’t. Especially with 90% of enterprise data being unstructured, including emails, documents, and customer interactions, making sense of it is more critical than ever. Enterprise AI does more than traditional analytics to tap into the potential of unstructured data, unlocking unprecedented opportunities.

2 months ago | securiti.ai | Ankur Gupta

AI is rapidly moving from test cases to real-world implementation like internal knowledge agents and customer service chatbots, and a PwC report predicts 2025 will bring exponential AI growth. As organizations rush to embrace the AI revolution on a large scale, they encounter several issues across technological, operational, and regulatory levels.