Can businesses stay compliant with security regulations while using generative AI? It’s an important question to consider as more businesses begin implementing this technology. What security risks are associated with generative AI? It's important to earn how businesses can navigate these risks to comply with cybersecurity regulations.
Just last week the UK’s NCSC issued a warning, stating that it sees alarming potential for so-called prompt injection attacks, driven by the large language models that power AI. The NSCS stated “Amongst the understandable excitement around LLMs, the global tech community still doesn‘t yet fully understand LLM’s capabilities, weaknesses, and (crucially) vulnerabilities.
AI has already revolutionized the way we work. ChatGPT, GitHub Copilot, and Zendesk AI are just a few of the tools that are taking over day-to-day tasks like generating customer support emails, de-bugging code, and much, much more. Yet despite all of these advancements, security teams are under more intense pressure than ever to mitigate rapidly evolving risks. Paired with a growing shortage of over 3.4 million cybersecurity workers, security teams are in need of a solution—and fast.
We’ve seen how technology can evolve at warp speed, and AI has emerged as both a revolutionary force and a tantalizing enigma. Whether you're a seasoned developer seeking to expand your toolkit or a security enthusiast on a quest for clarity in the realm of AI, embarking on the journey to demystify this dynamic field can be both exhilarating and overwhelming.
The term artificial intelligence is used to describe an IT system’s simulation of human intelligence processes, such as the ability to adapt, solve problems or plan. Artificial intelligence systems cover several of these features at present and, with the advent of ChatGPT, their use has become widespread in everyday life. However, this has also resulted in organizations exploiting the term "artificial intelligence," seeking to capitalize on its appeal.
