It is now well understood that integrating AI into an organization’s digital infrastructure will unlock real-time insights for decision-makers, streamline internal workflows by automating repetitive tasks, and enhance customer service interactions with AI-powered assistants. This technology will accelerate everything from purchases to personalized service requests. These benefits have made AI an essential component of modern digital ecosystems, accelerating growth, operational efficiency, and competitive advantage.
However, we have seen that in the rush to deploy these transformative AI technologies, security is often initially sacrificed for speed and functionality. This rush to implement AI-driven applications cambodia rcs data without the correct protections often exposes a raft of vulnerabilities that cybercriminals could be quick to exploit if the right corrective measures are not quickly taken. The risks are real and significant with the effects of attacks on these applications extending far beyond the AI systems themselves to harm the broader infrastructure in which they operate. While we have yet to see a major enterprise breach attributed to an overly liberal adoption of AI, this eventuality is only a matter of time.
Time and again, reports across industries confirm that threat actors are drawn to environments where security is considered an afterthought. These adversaries thrive in the digital sprawl that accompanies rapid growth and capitalize on the unintended expansion of the organization’s attack surface. AI is no different. As companies scale their use of large language models (LLMs) and AI-driven applications, the entry points for malicious actors proliferate.