Artificial Intelligence and Cybersecurity

It’s on business leaders and their IT teams to empower their workforce to confidently use AI tools while ensuring they are protected.

Hype and FOMO around generative AI are hijacking crucial discussions around cybersecurity in many firms between CISOs and senior execs

GenAI is evolving rapidly, and codifying internal governance allows your security teams to stay two steps ahead, making the use of GenAI consistent across the business, and identifying risk ahead of time.

As AI becomes integral to systems brought into the enterprise ecosystem it is increasingly critical for security teams to know where it is and reduce its risks.

The survey of global CEOs from PwC brings to light what global executives aim to achieve with generative AI in the near and long term.

Organizations must consider the security implications of using ChatGPT, as well as large language model (LLM) and LLM-based apps.

Why enterprises must be aware of the risks AI and ML present in the OT environment and learn how to safely leverage them and reap benefits.

AI is a crucial ally in proactively identifying and addressing hybrid cloud threats, streamlining compliance processes and establishing robust governance frameworks.

The conversation around AI in the workplace often generates fear. In fact, 65% of IT workers cite the rise of generative AI as a direct threat to their job security.

While businesses shouldn’t shy away from using generative AI in operations, it’s important to implement it with security top of mind.

Recent technological advances in hardware-based cybersecurity enable an “oversight system” to monitor and guarantee the integrity of incoming data and the confidentiality of outgoing data.

Generative AI could be the holy grail of DevSecOps, from writing secure code and documentation to creating tests. But it could be a major point of failure if not used correctly.

To realize the importance of prioritizing cybersecurity, it’s helpful to understand the cyber risks to AI safety.

Including security concerns at the beginning of any generative AI adoption discussion is key, but meanwhile the good news is cybersecurity budgets for AI are rising.

It's time to get real about what it takes to set and enforce cybersecurity and resilience standards for AI risk management in the enterprise.

Organizations need guardrails in place for AI tool data governance, specifically for their SaaS environments. This requires comprehensive SaaS security tooling and proactive cross-functional diplomacy.