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Advancements in the field of Generative AI have led to an explosion of interest and hype around chatbots that can create logical paragraphs , realistic images and that can seemingly mimic the human brain .

Modern chatbots rely on two branches of AI ; natural language processing ( NLP ) and Machine Learning ( ML ). In cybersecurity , advances in the aforementioned branches of AI are driving new human-machine capabilities .

In short , AI is transforming the way that we approach cybersecurity , solving some of our most challenging problems and keeping us ahead of fast-moving threats . An essential tool in cyber-crime prevention , AI can help protect businesses 24 / 7 in ways that were previously inaccessible .

As an example of AI ’ s utility in cybersecurity , blending traditional security mechanisms with AI can result in an almost 100 % detection rate , while dramatically reducing false positives . At the same time , AI-based cybersecurity tools can be prohibitively expensive for small businesses and AI tech ’ s overwhelming popularity has transformed it into a target for hackers .

Organisations should carefully assess the advantages and limitations of implementing AI algorithms within cybersecurity programmes . Questions to consider include : ‘ Where is AI beneficial ?’, ‘ What are the drawbacks ?’ and ‘ Which types of AI-based tools truly add value ’? In this eBook , see what experts have to say and drive stronger cybersecurity outcomes for your organisation . �

Cybersecurity powered by AI is at the top of IT budget priorities . Ninety-two percent of organisations intend to use AI and Machine Learning to support cybersecurity and over half of business owners already use AI for cybersecurity and fraud management purposes . 14 www . intelligentfin . tech