Historically, cyber-attacks were labor-intensive, meticulously planned, and needed extensive manual research. However, with the advent of AI, threat actors have harnessed their capabilities to orchestrate attacks with exceptional efficiency and potency. This technological shift enables them to execute more sophisticated, harder-to-detect attacks at scale.

GPT’s debut created a buzz, democratizing AI beyond tech circles. While its language expertise offers practical applications, security threats like malware and data leaks pose challenges. Organizations must carefully assess and balance the benefits against these security risks. Ensuring your safety while maximizing the benefits of Large Language Models(LLMs) like ChatGPT involves implementing practical actions and preparing for current and future security challenges.

Legacy data leak prevention (DLP) solutions are failing. Simply put, they weren’t built for business environments rooted in SaaS apps and generative AI (GenAI) tools. Meanwhile, security threats are evolving at a breakneck pace, with as many as 95% of enterprises experiencing multiple breaches a year. New attack surfaces are unfurling at a rapid rate following the switch to hybrid and cloud-based workspaces.

The rise of ChatGPT and Generative AI has swept the world by storm. It has left no stone unturned and has strong implications for cybersecurity and SecOps. The big reason for this is that cybercriminals now use GenAI to increase the potency and frequency of their attacks on organizations. To cope with this, security teams naturally need to adapt and are looking for ways to leverage AI to counter these attacks in a similar fashion.

With the proliferation of AI/ML enabled technologies to deliver business value, the need to protect data privacy and secure AI/ML applications from security risks is paramount. An AI governance framework model like the NIST AI RMF to enable business innovation and manage risk is just as important as adopting guidelines to secure AI. Responsible AI starts with securing AI by design and securing AI with Zero Trust architecture principles.

Artificial intelligence (AI) has revolutionised the field of cyber security, offering unparalleled advantages in detecting and preventing sophisticated cyber threats. From detecting anomalies in network behaviour to automating threat response, AI has become an indispensable tool for organisations looking to strengthen their defence against cyber-attacks.

A recent report reveals a significant discrepancy in the priorities of mid-market IT departments when it comes to addressing cyber threats. It's somewhat ironic that IT professionals find themselves entangled in a logical paradox when responding to surveys, as demonstrated by Node4’s Mid-Market IT Priorities Report 2024.

The integration of Artificial intelligence (AI) is forcing a significant transformation in the business operations landscape. Through automation, data analysis and predictive capabilities, AI is reshaping how businesses operate as companies look to spur productivity.